Data processing method, device, electronic device and storage medium

Abstract

The present invention provides a data processing method, device, electronic device and storage medium. A real estate question text sent by a terminal and input by a real estate agent on a questioning interface is received, and the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text are analyzed; according to the word units and the relative distribution positions, multiple first real estate question texts are screened in a real estate question text library, and multiple second real estate question texts matching the real estate personalized characteristics of the real estate agent are selected from the multiple first real estate question texts; multiple second real estate question texts and the historical adoption volume of each second real estate question text are sent to the terminal; so that the terminal displays multiple second real estate question texts on the questioning interface in the order of the historical adoption volume from large to small. In this way, the accuracy and efficiency of mining the questions that the real estate agent needs to ask can be improved.

Description

Technical Field

[0001] The present invention relates to the field of real estate technology, and in particular to a data processing method, device, electronic equipment and storage medium. Background Art

[0002] With the rapid development of the real estate business, there are more and more houses for sale or rent, and more and more users are looking for houses for rent or purchase. In this way, the real estate brokerage industry is gradually booming. At the same time, more and more people are participating in the real estate brokerage industry, for example, acting as real estate brokers to engage in real estate brokerage affairs and contribute to the real estate brokerage industry. In order to facilitate real estate brokers to engage in real estate brokerage affairs, many applications have appeared on the market, such as "XX Assistant", "XX Real Estate" or "XX Broker", etc., for real estate brokers to use at work. Real estate brokers can install applications on their mobile phones and use applications to assist their real estate brokerage work. Among them, applications often have intelligent systems, such as intelligent question and answer systems, etc. Real estate brokers may sometimes have some real estate-related questions to ask, so real estate brokers can ask real estate-related questions to the application, and the application analyzes real estate-related questions through its intelligent question and answer system and answers real estate-related questions. However, after statistics on the use of applications by a large number of real estate brokers, it was found that the intelligent question and answer system did not help most real estate brokers answer questions. Summary of the invention

[0003] The present application illustrates a data processing method, device, electronic device and storage medium.

[0004] In a first aspect, the present application shows a data processing method, which is applied to a server, and the method includes: receiving a real estate question text sent by a terminal, the real estate question text is the text that has been entered by a real estate agent on a question interface, and the question interface is an interface in an application displayed on a screen of the terminal; parsing the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; screening a plurality of first real estate question texts in a real estate question text library according to the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, wherein the real estate question text library includes a plurality of real estate question texts collected in advance; obtaining the real estate personalized features of the real estate agent; selecting a plurality of second real estate question texts that match the real estate personalized features of the real estate agent from the plurality of first real estate question texts; obtaining the historical adoption amount of each second real estate question text; sending a plurality of second real estate question texts and the historical adoption amount of each second real estate question text to the terminal; so that the terminal displays a plurality of second real estate question texts on the question interface in descending order of the historical adoption amount.

[0005] In a second aspect, the present application shows a data processing method, which is applied to a terminal, and the method includes: obtaining a real estate question text input by a real estate agent on a questioning interface; the questioning interface is an interface in an application displayed on a screen of the terminal; sending the real estate question text to a server, so that the server parses the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; according to the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, screening a plurality of first real estate question texts in a real estate question text library, wherein the real estate question text library includes a plurality of real estate question texts collected in advance; obtaining the real estate personalized characteristics of the real estate agent; selecting a plurality of second real estate question texts matching the real estate personalized characteristics of the real estate agent from the plurality of first real estate question texts; obtaining the historical adoption amount of each second real estate question text; sending a plurality of second real estate question texts and the historical adoption amount of each second real estate question text to the terminal; receiving a plurality of second real estate question texts and the historical adoption amount of each second real estate question text sent by the server; and displaying a plurality of second real estate question texts on the questioning interface in descending order of the historical adoption amount.

[0006] In a third aspect, the present application shows a data processing device, which is applied to a server, and the device includes: a first receiving module, which is used to receive a real estate question text sent by a terminal, the real estate question text is the text that the real estate agent has entered on the question interface, and the question interface is an interface in an application displayed on the screen of the terminal; a parsing module, which is used to parse the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; a screening module, which is used to screen multiple first real estate question texts in a real estate question text library according to the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, wherein the real estate question text library includes multiple real estate question texts collected in advance; a first acquisition module, which is used to obtain the real estate personalized characteristics of the real estate agent; a selection module, which is used to select multiple second real estate question texts that match the real estate personalized characteristics of the real estate agent from the multiple first real estate question texts; a second acquisition module, which is used to obtain the historical adoption amount of each second real estate question text; a first sending module, which is used to send multiple second real estate question texts and the historical adoption amount of each second real estate question text to the terminal; so that the terminal displays multiple second real estate question texts on the question interface in the order of the historical adoption amount from large to small.

[0007] In a fourth aspect, the present application shows a data processing device, which is applied to a terminal, and the device includes: a third acquisition module, which is used to acquire a real estate question text that has been input by a real estate agent on a question interface; the question interface is an interface in an application displayed on the screen of the terminal; a third sending module, which is used to send the real estate question text to a server, so that the server can parse the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; according to the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, a plurality of first real estate question texts are screened in a real estate question text library, wherein the real estate question text library The method comprises the following steps: comprising: providing a plurality of real estate question texts collected in advance; obtaining the real estate personalized characteristics of the real estate agent; selecting a plurality of second real estate question texts matching the real estate personalized characteristics of the real estate agent from the plurality of first real estate question texts; obtaining the historical adoption amount of each second real estate question text; sending the plurality of second real estate question texts and the historical adoption amount of each second real estate question text to the terminal; a third receiving module for receiving the plurality of second real estate question texts and the historical adoption amount of each second real estate question text sent by the server; and a first display module for displaying the plurality of second real estate question texts on the questioning interface in the order of the historical adoption amount from large to small.

[0008] In a fifth aspect, the present application illustrates an electronic device, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the method described in any of the above aspects.

[0009] In a sixth aspect, the present application illustrates a non-temporary computer-readable storage medium, which, when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to execute a method as described in any of the above aspects.

[0010] In a seventh aspect, the present application illustrates a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to execute the method described in any of the above aspects.

[0011] The technical solution provided by this application may have the following beneficial effects:

[0012] In the present application, a plurality of first real estate question texts are screened in a real estate question text library based on word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, wherein the real estate question text library includes a plurality of real estate question texts collected in advance, and it is more likely that the first real estate question texts screened based on the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text contain the questions that the real estate agent needs to ask.

[0013] In addition, the real estate personalized features of different real estate agents are not all the same. For example, the types of real estate business that real estate agents engage in are not all the same, and the real estate functions of applications used by real estate agents are not all the same, etc. In this way, through the real estate personalized features of real estate agents, real estate question texts related to the real estate personalized features of real estate agents can be screened out from multiple first real estate question texts, thereby making it more likely that the multiple second real estate question texts selected from the multiple first real estate question texts that match the real estate personalized features of real estate agents contain questions that the real estate agent needs to ask.

[0014] It can be seen that through this application, the questions that the real estate agent needs to ask can be accurately mined from multiple real estate question texts collected in advance based on the real estate question text entered by the real estate agent on the question interface. The questions that the real estate agent may need to ask can be mined without having multiple rounds of conversations with the real estate agent, thereby improving the efficiency of accurately mining the questions that the real estate agent needs to ask. Secondly, it can also improve the accuracy of mining the questions that the real estate agent needs to ask.

[0015] Furthermore, the greater the historical adoption volume of the second real estate question text, the greater the possibility that it is the question that the real estate agent needs to ask. In this way, displaying multiple second real estate question texts on the question interface in order of historical adoption volume from large to small can make it easier for the real estate agent to find the question that the real estate agent needs to ask among the multiple second real estate question texts more quickly and easily, thereby improving the efficiency of accurately mining the questions that the real estate agent needs to ask. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a structural block diagram of a data processing system of the present application.

[0017] Figure 2 It is a step flow chart of a data processing method of the present application.

[0018] Figure 3 It is a step flow chart of a data processing method of the present application.

[0019] Figure 4 It is a structural block diagram of a data processing device of the present application.

[0020] Figure 5 It is a structural block diagram of a data processing device of the present application.

[0021] Figure 6 It is a block diagram of an electronic device of the present application.

[0022] Figure 7 It is a block diagram of an electronic device of the present application. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] In order to make the intelligent question-and-answer system able to help most real estate agents answer questions as much as possible. The inventor analyzed the reasons why the intelligent question-and-answer system did not help most real estate agents answer questions. For example, after statistics on the use of the application by a large number of real estate agents, it was found that the intelligent question-and-answer system in the application has a high threshold for getting started, and most real estate agents are unfamiliar with the intelligent question-and-answer system in the application, which leads to most real estate agents being unable to master how to use the intelligent question-and-answer system, and then unable to accurately express their real estate-related questions to the intelligent question-and-answer system, and then leading to the intelligent question-and-answer system being unable to accurately obtain the real estate-related questions of the real estate agents. In this case, it is impossible to accurately answer the real estate-related questions of the real estate agents. Further, after trying to use the intelligent question-and-answer system to ask questions many times, the real estate agents cannot get a satisfactory answer, and then they will give up using the intelligent question-and-answer system. In this way, the intelligent question-and-answer system does not help most real estate agents answer questions. Therefore, how to accurately mine the problems of real estate agents is a technical problem that needs to be solved urgently.

[0025] Reference Figure 1 , showing a structural block diagram of a data processing system of the present application, the system includes a terminal and a server.

[0026] The terminal is installed with an application, for example, an application for assisting real estate agents in their work, such as "XX Assistant", "XX Real Estate" or "XX Agent", etc., for real estate agents to publish houses, use / provide assistance in marketing houses, provide data analysis, Q&A and other assistance during work. The application may also be an application for a real estate platform that displays house information such as houses / advertisements published by real estate agents to users, or other types of real estate applications.

[0027] The server may be a server corresponding to the application. The manufacturer that develops the application and the manufacturer that develops the server may be the same manufacturer or different manufacturers. After the terminal starts the application, the terminal may interact with the server based on the application. In addition, the terminal may also interact with the real estate platform based on the application. The manufacturer that develops the real estate platform and the manufacturer that develops the server may be the same manufacturer or different manufacturers.

[0028] The role of the real estate platform can be: to be used by real estate agents to place real estate advertisements or obtain real estate information, etc. Among them, real estate agents placing real estate advertisements includes but is not limited to publishing real estate information through the real estate platform, or publishing rental / sale information through the real estate platform.

[0029] Reference Figure 2 , showing a flow chart of the steps of a data processing method of the present application, the method is applied to Figure 1 In the system shown, the method may specifically include the following steps:

[0030] In step S101, the terminal obtains the real estate question text input by the real estate agent on the question interface.

[0031] The questioning interface is one of the interfaces in the application displayed on the screen of the terminal. For example, the real estate agent's terminal has an application installed, and the real estate agent can start the application on the terminal, and then the interface of the application will be displayed on the screen of the terminal. The application has multiple interfaces, one of which is the questioning interface, which is used for the real estate agent to enter question text on the questioning interface.

[0032] When the questioning interface of the application is displayed on the screen of the terminal, the real estate agent can enter the question text on the questioning interface. The way of entering the question text includes but is not limited to text input of the question text (for example, input through the input box on the questioning interface) or voice input of the question text (for example, input through the voice input option on the questioning interface), and the terminal can obtain the question text entered by the real estate agent on the questioning interface in real time.

[0033] It should be noted that when the real estate agent inputs the real estate question text on the question interface, the real estate question text may include multiple characters, for example, multiple Chinese characters.

[0034] When the real estate agent inputs the real estate question text on the question interface, he does not input multiple characters into the question interface at the same time, but inputs one or two characters one by one. As the input continues, the characters input by the real estate agent on the question interface will continue to increase, thereby causing the real estate question text input by the real estate agent on the question interface to change continuously.

[0035] In this way, whenever the real estate question text entered by the real estate agent on the questioning interface meets the preset conditions, the terminal can execute step S101 once to obtain the real estate question text entered by the real estate agent on the questioning interface (the most real-time real estate question text entered on the questioning interface at that time), and then can execute steps S102 to S111 accordingly. Among them, the preset conditions can be one or more of the following conditions: the characters entered by the real estate agent on the questioning interface increase within the preset time, or the real estate question text entered by the real estate agent on the questioning interface changes within the preset time, or the characters or real estate question text entered by the real estate agent on the questioning interface do not change within the preset time, or any other conditions that can be thought of by those skilled in the art. The preset time can be any set time, such as 0.5 seconds or other time.

[0036] In step S102, the terminal sends a real estate inquiry text to the server.

[0037] In step S103, the server receives the real estate inquiry text sent by the terminal.

[0038] In step S104, the server parses the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text.

[0039] Tokens are obtained through Tokenization, which is the most basic step in the task of Natural Language Processing (NLP). The smallest basic unit in the text is the lemma (or tag / token, etc.), which is used for subsequent processing.

[0040] In this application, the BERT (Bidirectional Encoder Representations from Transformers) model can be used to parse the words in the real estate question text and the relative distribution position of each word in the real estate question text, or other models can be used to parse the words in the real estate question text and the relative distribution position of each word in the real estate question text. This application does not limit the type of specific model used for the above-mentioned parsing action.

[0041] In one embodiment, the real estate question text may include a word unit, and the relative distribution position of the word unit in the real estate question text can be understood as the first position or the last position, etc.

[0042] Alternatively, in another embodiment, the real estate question text may include multiple word units, and the relative distribution positions of the multiple word units in the real estate question text may be understood as: the order in which the various word units appear in the real estate question text.

[0043] For example, suppose the real estate question text is "What is a diamond booth", which includes three tokens, namely: "what", "diamond" and "booth". The token "what" is the first token that appears in the real estate question text, so the relative distribution position of the token "what" in the real estate question text is the first. The token "diamond" is the second token that appears in the real estate question text, so the relative distribution position of the token "diamond" in the real estate question text is the second. The token "booth" is the third token that appears in the real estate question text, so the relative distribution position of the token "booth" in the real estate question text is the third.

[0044] In step S105, the server selects a plurality of first real estate question texts in a real estate question text library according to the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, wherein the real estate question text library includes a plurality of real estate question texts collected in advance.

[0045] The multiple real estate question texts collected in advance in the real estate question text library can be manually collected based on experience, etc., can be texts corresponding to real estate questions that real estate agents often ask in the historical process, or can be texts corresponding to real estate questions that real estate agents are often interested in, etc. Further, in the embodiment of the present application, the real estate question texts that the real estate agent has entered on the question interface can also enter the real estate question text library as subsequent real estate question texts. The number of the multiple first real estate question texts is less than or equal to the number of real estate question texts in the real estate question text library.

[0046] In one embodiment of the present application, this step can be implemented through the following process, including:

[0047] 1051. For any real estate problem text in the real estate problem text library, obtain the word units in the real estate problem text and the relative distribution positions of each word unit in the real estate problem text.

[0048] Among them, the word units in the real estate problem text and the relative distribution positions of each word unit in the real estate problem text can be obtained by pre-analysis (the specific parsing method can be referred to the description of step S104, which will not be described in detail here) and stored in the server, and the word units in the real estate problem text and the relative distribution positions of each word unit in the real estate problem text can be uniquely marked by the real estate problem text or the problem identifier of the real estate problem text. There are differences in the characters and / or differences in the order of the characters in different real estate problem texts. The problem identifiers of different real estate problem texts are different. In this way, the word units in the real estate problem text and the relative distribution positions of each word unit in the real estate problem text stored in advance can be obtained according to the real estate problem text or the problem identifier of the real estate problem text.

[0049] 1052. Determine whether all the words in the real estate question text are words in the real estate question text.

[0050] For example, determine whether the word-grams in the real estate question text are a subset of the word-grams in the real estate question text. If the word-grams in the real estate question text are a subset of the word-grams in the real estate question text, it can be determined that all the word-grams in the real estate question text are word-grams in the real estate question text. Alternatively, if the word-grams in the real estate question text are not a subset of the word-grams in the real estate question text, it can be determined that all the word-grams in the real estate question text are not all word-grams in the real estate question text.

[0051] 1053. When all the words in the real estate question text are the words in the real estate question text, determine whether the relative distribution positions of the words in the real estate question text are the same as the relative distribution positions of the words in the real estate question text in the real estate question text.

[0052] Alternatively, when all word units in the real estate question text are not word units in the real estate question text, the real estate question text is not determined as the first real estate question text.

[0053] Among them, for any identical word in the real estate question text and the real estate question text, if the order in which the word appears in the real estate question text is the same as the order in which the word appears in the real estate question text, and the same is true for every other identical word in the real estate question text and the real estate question text, then it can be determined that the relative distribution positions of each word in the real estate question text in the real estate question text are the same as the relative distribution positions of each word in the real estate question text in the real estate question text.

[0054] 1054. When the relative distribution positions of each word in the real estate question text are the same as the relative distribution positions of each word in the real estate question text in the real estate question text, the real estate question text is determined as the first real estate question text.

[0055] Alternatively, when the relative distribution positions of each word in the real estate question text are different from the relative distribution positions of each word in the real estate question text in the real estate question text, the real estate question text is not determined as the first real estate question text.

[0056] In step S106, the server obtains the personalized characteristics of the real estate agent's real estate.

[0057] In one embodiment, the real estate personalized features of the real estate agent may include: among multiple types of real estate businesses, the business type of the real estate business that the real estate agent is engaged in.

[0058] In one embodiment, the real estate personalized features of the real estate agent may include: among the multiple real estate functions of the application, the real estate functions used by the real estate agent. For example, in the case where the application is an application for assisting the real estate agent in his work, the multiple real estate functions may include a property marketing function, a property maintenance function, a customer source analysis function, and a real estate knowledge base function. In this case, the real estate function is a function for assisting the real estate agent in his work.

[0059] Among the multiple real estate functions of the application, the real estate functions used by the real estate agent include: the real estate functions used by the real estate agent within a preset time period before the current moment.

[0060] The end time of the preset duration may be the current time. The preset duration may be 1 day, 2 days, 3 days, 1 week, 2 weeks or 1 month, etc., which may be determined according to actual conditions, and this application does not limit this.

[0061] In one embodiment, the real estate personalized features of a real estate agent may include: a real estate platform that the real estate agent has connected to via an application, etc. For example, if the real estate agent has placed real estate advertisements on a real estate platform via an application, then this real estate platform can also be regarded as the real estate personalized features of the real estate agent.

[0062] In another embodiment, the personalized features of a property by a real estate agent include: a real estate platform designated by the real estate agent that the real estate agent needs to connect to / use, etc.

[0063] In one example, a real estate agent may maintain multiple properties (for sale or rent, etc.). In order to sell the properties maintained by the real estate agent as soon as possible, the real estate agent may place advertisements for the properties maintained by the real estate agent on the real estate platform to promote or display the properties maintained by the real estate agent so that more users can see the properties maintained by the real estate agent.

[0064] Among them, after the real estate agent submits a real estate question text at a certain time, the real estate question text can be: at least part of the characters in the question that the real estate agent needs to ask. The real estate question text itself may involve multiple platforms. For example, the real estate agent may ask "How much is the profit from my real estate advertising?" In fact, the real estate agent only places real estate advertisements on real estate platform A. However, objectively, the real estate agent can place real estate advertisements on various real estate platforms. Therefore, "How much is the profit from my real estate advertising" itself may involve multiple platforms. For example, it may be necessary to ask how much is the profit from placing real estate advertisements on a certain real estate platform. Therefore, it is necessary to accurately dig out which real estate platform the real estate agent's question "How much is the profit from my real estate advertising" is directed to. To this end, the terminal can display multiple real estate platforms for the real estate agent to choose.

[0065] However, due to the particularity of the real estate industry, most real estate agents will switch back and forth between different real estate platforms to place real estate advertisements and test the effectiveness of the placements whenever possible.

[0066] For example, a real estate agent chooses to place real estate advertisements on real estate platform A from January to April, on real estate platform B from May to June, and on real estate platform C from July to September.

[0067] This results in changes in the real estate platforms used by real estate agents at different times. Each time the real estate agent asks a question, the terminal / server needs to accurately find out which real estate platform the real estate agent's question is directed to, which is too cumbersome.

[0068] To this end, after the real estate agent selects a real estate platform, multiple marking periods for the real estate platform can be displayed for the real estate agent to choose from, and the multiple marking periods include: 1 day, 1 week, 1 month, 3 months, 6 months or 1 year, etc.

[0069] After the real estate agent selects a marking period, the terminal will send the marking period selected by the real estate agent and the real estate platform to the server, and the server will use the real estate platform as a personalized feature of the real estate agent within the marking period. In this way, there is no need to repeatedly ask the real estate agent to confirm the real estate platform for this real estate agent within the marking period, which reduces tediousness, improves intelligence, and simplifies the operation of the real estate agent.

[0070] In step S107, the server selects a plurality of second real estate question texts that match the real estate personalized characteristics of the real estate agent from the plurality of first real estate question texts.

[0071] The number of the plurality of second real estate problem texts is less than or equal to the number of the plurality of first real estate problem texts.

[0072] In one embodiment of the present application, the personalized property characteristics of a real estate agent may include: among multiple types of real estate businesses, the business type of the real estate business that the real estate agent is engaged in.

[0073] In this way, when multiple second real estate question texts that match the real estate personalized characteristics of the real estate agent are selected from multiple first real estate question texts, the business type of the real estate business involved in any first real estate question text can be obtained.

[0074] The business types of real estate business involved in the real estate question text may include: sale and purchase of second-hand residences (second-hand houses), sale and purchase of new residences (new houses), leasing or sale of residences / shops / office buildings / warehouses / apartments, etc.

[0075] In this application, a real estate question text may relate to a business type of real estate business.

[0076] The business type of the real estate business involved in the first real estate question text can be determined in advance, for example, the sale and purchase of second-hand residences (second-hand houses), the sale and purchase of new residences (new houses), the leasing or sale and purchase of residences / shops / office buildings / warehouses / apartments, etc., and the business type of the real estate business involved in the first real estate question text is stored in the server, and the business type of the real estate business involved in the stored first real estate question text can be uniquely marked by the first real estate question text or the question identifier of the first real estate question text. In this way, the business type of the real estate business involved in the first real estate question text stored in advance can be obtained according to the first real estate question text or the question identifier of the first real estate question text.

[0077] Afterwards, it can be determined whether the business type of the real estate business involved in the first real estate question text is the business type of the real estate business engaged in by the real estate broker.

[0078] The business type of the real estate business engaged in by the real estate agent may be manually selected by the agent in advance in the application and submitted to the server and stored on the server, or may be calculated by the server based on the historical operation behavior of the real estate agent and stored on the server.

[0079] The server can obtain the business type of the real estate business that the stored real estate agent is engaged in.

[0080] Among them, the real estate agent is engaged in at least one type of business in the real estate business, for example, at least one of the sale and purchase of second-hand residences (second-hand houses), sale and purchase of new residences (new houses), leasing or sale of residences / shops / office buildings / warehouses / apartments, etc.

[0081] In a case where the business type of the real estate business involved in the first real estate problem text is the business type of the real estate business engaged in by a real estate agent, the first real estate problem text is determined as the second real estate problem text.

[0082] Alternatively, when the business type of the real estate business involved in the first real estate problem text is not the business type of the real estate business engaged in by the real estate broker, the first real estate problem text is not determined as the second real estate problem text.

[0083] The same applies for each other first property problem text in the multiple first property problem texts.

[0084] Alternatively, in another embodiment of the present application, it may be determined first whether the first real estate problem text is in the real estate agent's real estate problem text blacklist.

[0085] The real estate agent's real estate problem text blacklist records the real estate problem texts that the real estate agent actively denied in the historical process. The real estate problem texts that the real estate agent actively denied are: the real estate problem texts that the real estate agent has confirmed do not need to be raised or will not be raised.

[0086] If the first real estate problem text is not in the real estate problem text blacklist of the real estate agent, it is determined whether the business type of the real estate business involved in the first real estate problem text is the business type of the real estate business engaged in by the real estate agent.

[0087] Alternatively, if the first real estate problem text is in the real estate agent's real estate problem text blacklist, the first real estate problem text is not determined as the second real estate problem text.

[0088] Alternatively, in another embodiment of the present application, the real estate personalized features of the real estate agent may include: among the multiple real estate functions of the application, the real estate functions used by the real estate agent.

[0089] In this way, when multiple second real estate question texts that match the real estate personalized characteristics of the real estate agent are selected from multiple first real estate question texts, the real estate function of the application program involved in any one of the multiple first real estate question texts can be obtained.

[0090] The application can have a variety of real estate functions, such as real estate marketing function, property maintenance function, customer source analysis function, real estate knowledge base function, etc.

[0091] In this application, a real estate question text may relate to a real estate function of the application.

[0092] The real estate function of the application involved in the first real estate question text can be determined in advance, such as a real estate marketing function, a house maintenance function, a customer source analysis function, or a real estate knowledge base function, and the real estate function of the application involved in the first real estate question text can be stored in the server, and the real estate function of the application involved in the stored first real estate question text can be uniquely marked by the first real estate question text or the problem identifier of the first real estate question text. In this way, the real estate function of the application involved in the first real estate question text stored in advance can be obtained according to the first real estate question text or the problem identifier of the first real estate question text.

[0093] It can then be determined whether the real estate function of the application program involved in the first real estate question text is a real estate function used by the real estate agent.

[0094] The real estate functions of the application used by the real estate agent can be counted by the server based on the real estate agent's historical operation behaviors and stored on the server.

[0095] The server can then obtain the business type of the real estate business that the stored real estate agent is engaged in.

[0096] Among them, real estate agents have used the real estate functions of the application, such as the real estate marketing function, the property maintenance function, the customer source analysis function, or the real estate knowledge base function.

[0097] When the real estate function of the application program involved in the first real estate question text is a real estate function used by a real estate agent, the first real estate question text is determined as the second real estate question text.

[0098] Alternatively, if the real estate function of the application program involved in the first real estate problem text is not a real estate function used by a real estate agent, the first real estate problem text will not be determined as the second real estate problem text.

[0099] The same applies for each other first property problem text in the multiple first property problem texts.

[0100] Alternatively, in another embodiment of the present application, it may be determined first whether the first real estate problem text is in the real estate agent's real estate problem text blacklist.

[0101] The real estate agent's real estate problem text blacklist records the real estate problem texts that the real estate agent actively denied in the historical process. The real estate problem texts that the real estate agent actively denied are: real estate problem texts that the real estate agent does not need to raise or will not raise.

[0102] If the first real estate problem text is not in the real estate problem text blacklist of the real estate agent, it is determined whether the real estate function of the application program involved in the first real estate problem text includes the real estate function used by the real estate agent.

[0103] Alternatively, if the first real estate problem text is in the real estate agent's real estate problem text blacklist, the first real estate problem text is not determined as the second real estate problem text.

[0104] In step S108, the server obtains the historical adoption volume of each second real estate question text.

[0105] The historical adoption volume of the real estate question text includes: the adoption volume of the real estate question text adopted by the real estate agent (the real estate agent who inputs the real estate question text) in the historical process, or the sum of the historical adoption volumes of the real estate question text adopted by multiple different real estate agents in the historical process.

[0106] Among them, after the real estate problem text is displayed or recommended to the real estate agent, the real estate agent clicks on the real estate problem text to realize the selection of the real estate problem text (equivalent to the approval of the real estate problem text), which means that the real estate agent adopts the real estate problem text once.

[0107] In step S109, the server sends a plurality of second real estate problem texts and a historical adoption amount of each second real estate problem text to the terminal.

[0108] In step S110, the terminal receives a plurality of second real estate problem texts and a historical adoption amount of each second real estate problem text sent by the server.

[0109] In step S111, the terminal displays a plurality of second real estate question texts on the questioning interface in descending order of historical adoption volume.

[0110] In the order of historical adoption volume from large to small, multiple second real estate question texts are arranged and displayed (displayed simultaneously) on the questioning interface, so that the real estate agent can view the multiple second real estate question texts.

[0111] In the present application, based on the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, a first real estate question text whose word units and the relative distribution positions of word units are the same as the word units and the relative distribution positions of word units in the real estate question text is screened out in the real estate question text library; the first real estate question text whose word units and the relative distribution positions of word units are the same as the word units and the relative distribution positions of word units in the real estate question text is more likely to contain the questions that the real estate agent needs to ask.

[0112] In addition, the real estate personalized characteristics of different real estate agents are not all the same. For example, the types of real estate business that real estate agents engage in are not all the same, and the real estate functions of applications used by real estate agents are not all the same, etc. In this way, through the real estate personalized characteristics of real estate agents, real estate question texts that are not related to the real estate personalized characteristics of real estate agents can be filtered out from multiple first real estate question texts, and real estate question texts related to the real estate personalized characteristics of real estate agents can be screened out, thereby making it more likely that the multiple second real estate question texts selected from the multiple first real estate question texts that match the real estate personalized characteristics of real estate agents contain questions that the real estate agent needs to ask.

[0113] It can be seen that through this application, the questions that the real estate agent needs to ask can be accurately mined from multiple real estate question texts collected in advance based on the real estate question text that the real estate agent has entered on the question interface. The questions that the real estate agent may need to ask can be mined without having multiple rounds of conversations with the real estate agent, thereby improving the efficiency of accurately mining the questions that the real estate agent needs to ask. Secondly, it can also improve the accuracy of mining the questions that the real estate agent needs to ask.

[0114] Furthermore, the greater the historical adoption volume of the second real estate question text, the greater the possibility that it is the question that the real estate agent needs to ask. In this way, displaying multiple second real estate question texts on the question interface in order of historical adoption volume from large to small can make it easier for the real estate agent to find the question that the real estate agent needs to ask among the multiple second real estate question texts more quickly and easily, thereby improving the efficiency of accurately mining the questions that the real estate agent needs to ask.

[0115] In the present application, the real estate agent can check whether there is a question text that is exactly what he needs to ask among multiple second real estate question texts. If there is a question text that is exactly what he needs to ask among multiple second real estate question texts, the real estate agent can input an adoption operation for the question text that is exactly what he needs to ask.

[0116] Further, see Figure 3 , the method further comprises:

[0117] In step S201, the terminal receives a target second property problem text adopted by the broker from among a plurality of displayed second property problem texts.

[0118] In step S202, the terminal sends the target second property question text to the server.

[0119] In step S203, the server receives the target second property question text sent by the terminal.

[0120] In step S204, the server generates a derivative question text associated with the target second real estate question text according to the target second real estate question text, the real estate personalized characteristics of the real estate agent, and the question generation model.

[0121] The derived question text includes at least: a question text with keywords and positive semantics, a question text with keywords and negative semantics, and a question text with keywords and involving the business type of the real estate business involved in the target second real estate question text. The keyword is a word element in the target second real estate question text that is used to describe the question topic of the target second real estate question text.

[0122] In this step, the target second real estate question text and the real estate personalized characteristics of the real estate agent can be input into the question generation model, so that the question generation model processes the target second real estate question text and the real estate personalized characteristics of the real estate agent to obtain a derivative question text associated with the target second real estate question text.

[0123] For example, the question generation model may include an LLM (Large Language Model), or may include other types of language models, which is not limited in the present application.

[0124] In the process of the question generation model generating a derivative question text associated with the target second real estate question text, the question generation model can use a self-attention mechanism. For example, the real estate personalized features of the real estate agent are used in the self-attention mechanism to increase the possibility that the generated derivative question text contains questions that the real estate agent needs to ask.

[0125] The Self-Attention Mechanism, also known as the Internal Attention Mechanism, is a mechanism widely used in deep learning models, especially in the field of Natural Language Processing (NLP). This mechanism allows the model to focus on different positions in the sequence when processing sequence data, thereby capturing the dependencies within the sequence. This mechanism enables the model to dynamically focus on the most relevant part of the input sequence to better understand the contextual information.

[0126] In an example, assume that the target second real estate question text is: "What is Qianketong". The word element in the target second real estate question text that is used to describe the question subject of the target second real estate question text is "Qianketong". The question text with keywords and positive semantics may be: "How can I increase the number of Qianketong customers". The question text with keywords and negative semantics may be: "Why do I have few Qianketong customers". The question text with keywords and involving the business type of the real estate business involved in the target second real estate question text may be: "What is the difference between Zhiketong and Qianketong".

[0127] In step S205, the server sends the derived question text to the terminal.

[0128] In step S206, the terminal receives the derived question text sent by the server.

[0129] In step S207, the terminal displays the derived question text on the questioning interface.

[0130] The real estate agent can view the derived question text on the display interface, for example, to check whether there is the question text that he needs to ask in the derived question text, and the real estate agent can input the adoption operation for the question text that he needs to ask.

[0131] Through the process of step S201 to step S207, questions that the real estate agent may need to ask can be generated based on the target second real estate question text and the real estate personalized characteristics of the real estate agent. The questions that the real estate agent may need to ask can be mined without having multiple rounds of conversations with the real estate agent, thereby improving the efficiency of accurately mining the questions that the real estate agent needs to ask. Secondly, it can also improve the accuracy of mining the questions that the real estate agent needs to ask.

[0132] In another embodiment, when the derived question text is displayed on the question interface, the disapproval options corresponding to each derived question text can also be displayed on the right side of each derived question text. For example, if the broker disapproves of a certain derived question text, the selection operation for the disapproval option corresponding to the derived question text can be input, and the terminal can receive the selection operation for the disapproval option corresponding to the derived question text, and then send the certain derived question text to the server, which can store the certain derived question text in the real estate broker's real estate question text blacklist.

[0133] In another embodiment of the present application, whenever the real estate agent inputs an adoption operation for a question text displayed on the display interface, the terminal can send the question text adopted by the real estate agent to the server. The server generates an answer to the question text based on a system for generating answers to questions and sends the answer to the terminal. The terminal can receive the answer and display the answer at the bottom of the question text displayed on the display interface for the real estate agent to view the answer.

[0134] In one embodiment of the present application, for any real estate problem text among multiple real estate problem texts collected in advance in the real estate problem text library, the real estate problem text and the historical adoption amount corresponding to the real estate problem text are stored in the correspondence relationship between the real estate problem text and the historical adoption amount of the real estate problem text (the initial value is 0, and it will dynamically increase as the real estate problem text is adopted). After the real estate problem text is adopted once, the historical adoption amount corresponding to the real estate problem text in the correspondence relationship can be increased.

[0135] The same is true for each other real estate problem text in the multiple real estate problem texts collected in advance in the real estate problem text library.

[0136] Therefore, when obtaining the historical adoption amount of each second real estate problem text, the historical adoption amount corresponding to each second real estate problem text can be found in the corresponding relationship between the real estate problem text and the historical adoption amount of the real estate problem text.

[0137] Among them, the historical adoption amount of the real estate question text in the corresponding relationship can dynamically increase as it is adopted by the real estate agent.

[0138] Furthermore, after the terminal displays multiple second real estate question texts on the question interface in descending order of historical adoption volume, a certain second real estate question text among the multiple second real estate question texts may be exactly the question that the real estate agent wants to ask. In this case, the real estate agent may adopt the certain second real estate question text, for example, input an adoption operation (such as a click operation, etc.) for the certain second real estate question text to select the certain second real estate question text.

[0139] When the terminal receives the real estate agent's adoption operation on the target second real estate problem text among multiple second real estate problem texts, the target second real estate problem text and adoption information indicating the adoption of the target second real estate problem text may be sent to the server.

[0140] The server receives the target second real estate problem text and the adoption information indicating the adoption of the target second real estate problem text, and then updates the historical adoption amount corresponding to the target second real estate problem text in the corresponding relationship according to the adoption information.

[0141] The adoption increment of the target second real estate problem text may be obtained according to the adoption information. For example, in one embodiment, the adoption increment may be a value of 1 or a value of 2. Then, the adoption increment is added to the historical adoption amount corresponding to the target second real estate problem text in the corresponding relationship.

[0142] In this application, question text has question attributes, such as:

[0143] Public real estate issues that have been reviewed and confirmed by the auditors on the server side (or reviewed and confirmed by real estate platforms other than the server side) and decoupled from the specific real estate business in the real estate field. Among them, the terminal can interact with real estate platforms other than the server side through the application.

[0144] Specific business issues of real estate that have been reviewed and confirmed by reviewers on the server side (or reviewed and confirmed by a real estate platform other than the server side).

[0145] City-related issues in the real estate sector on the server side, for example, cities where real estate services are available, etc.

[0146] Expose the Top N real estate public issues with the highest comprehensive adoption index, which are decoupled from the specific real estate business in the real estate field.

[0147] Expose the Top N real estate-specific business issues with the highest comprehensive adoption index.

[0148] And, other problem attributes and so on.

[0149] The adoption increment of real estate question texts with different question attributes may be different.

[0150] For example, the adoption increment of public real estate issues that have been reviewed and confirmed by the auditors on the server side and are decoupled from the specific business of real estate in the real estate field can be 5. The adoption increment of specific business issues of real estate that have been reviewed and confirmed by the auditors on the server side can be 3. The adoption increment of city issues of real estate on the server side can be 2. The adoption increment of the TopN public real estate issues that are decoupled from the specific business of real estate in the real estate field with the highest exposure and adoption comprehensive index can be 2. The adoption increment of the TopN specific business issues of real estate with the highest exposure and adoption comprehensive index can be 1. The adoption increment of other problem attributes can be 1. N in TopN is a positive integer, for example, it can be 5, 10, 15 or 20, etc., which can be determined according to actual conditions, and this application does not limit this. The exposure and adoption comprehensive index of the real estate problem text can be obtained by weighted summing the historical exposure and historical adoption of the real estate problem text, and this application does not limit the specific weighting method.

[0151] It should be noted that, for the method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions involved are not necessarily required by the present application.

[0152] Reference Figure 4 , shows a structural block diagram of a data processing device of the present application, which is applied to a server, and the device includes: a first receiving module 11, which is used to receive a real estate question text sent by a terminal, the real estate question text is the text that has been input by a real estate agent on a question interface, and the question interface is an interface in an application displayed on the screen of the terminal; a parsing module 12, which is used to parse the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; a screening module 13, which is used to screen multiple first real estate question texts in a real estate question text library according to the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, Among them, the real estate question text library includes multiple real estate question texts collected in advance; the first acquisition module 14 is used to obtain the real estate personalized characteristics of the real estate agent; the selection module 15 is used to select multiple second real estate question texts that match the real estate personalized characteristics of the real estate agent from the multiple first real estate question texts; the second acquisition module 16 is used to obtain the historical adoption volume of each second real estate question text; the first sending module 17 is used to send multiple second real estate question texts and the historical adoption volume of each second real estate question text to the terminal; so that the terminal displays multiple second real estate question texts on the question interface in the order of historical adoption volume from large to small.

[0153] In an optional implementation, the device also includes: a second receiving module, used to receive a target second real estate question text sent by the terminal, the target second real estate question text is a real estate question text adopted from multiple second real estate question texts displayed by the real estate agent on the questioning interface of the terminal; a generating module, used to generate a derivative question text associated with the target second real estate question text according to the target second real estate question text, the real estate personalized characteristics of the real estate agent and the question generation model; the derivative question text includes at least: at least one of a question text with keywords and positive semantics, a question text with keywords and negative semantics, and a question text with keywords and involving a business type of real estate business involved in the target second real estate question text, the keyword is a word element in the target second real estate question text used to describe the question theme of the target second real estate question text; a second sending module, used to send the derivative question text to the terminal so that the terminal displays the derivative question text on the questioning interface.

[0154] In an optional implementation, the screening module includes: a first acquisition unit, used to obtain, for any real estate question text in a real estate question text library, word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; a first determination unit, used to determine whether each word unit in the real estate question text is a word unit in the real estate question text; a second determination unit, used to determine whether the relative distribution positions of each word unit in the real estate question text are the same as the relative distribution positions of each word unit in the real estate question text in the real estate question text when each word unit in the real estate question text is a word unit in the real estate question text; a third determination unit, used to determine the real estate question text as the first real estate question text under the same circumstances.

[0155] In an optional implementation, the real estate personalized features of the real estate agent include: among multiple types of real estate businesses, the business type of the real estate business engaged in by the real estate agent; the selection module includes: a second acquisition unit, used to acquire the business type of the real estate business involved in any first real estate problem text among multiple first real estate problem texts; a fourth determination unit, used to determine whether the business type of the real estate business involved in the first real estate problem text is the business type of the real estate business engaged in by the real estate agent; and a fifth determination unit, used to determine the first real estate problem text as the second real estate problem text when the business type of the real estate business involved in the first real estate problem text is the business type of the real estate business engaged in by the real estate agent.

[0156] In an optional implementation, the real estate personalized features of the real estate agent include: among multiple real estate functions of the application, the real estate function used by the real estate agent; the selection module includes: a third acquisition unit, used to acquire the real estate function of the application involved in any first real estate problem text among multiple first real estate problem texts; a sixth determination unit, used to determine whether the real estate function of the application involved in the first real estate problem text is the real estate function used by the real estate agent; and a seventh determination unit, used to determine the first real estate problem text as the second real estate problem text when the real estate function of the application involved in the first real estate problem text is the real estate function used by the real estate agent.

[0157] In the present application, based on the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, a first real estate question text whose word units and the relative distribution positions of word units are the same as the word units and the relative distribution positions of word units in the real estate question text is screened out in the real estate question text library; the first real estate question text whose word units and the relative distribution positions of word units are the same as the word units and the relative distribution positions of word units in the real estate question text is more likely to contain the questions that the real estate agent needs to ask.

[0158] In addition, the real estate personalized characteristics of different real estate agents are not all the same. For example, the types of real estate business that real estate agents engage in are not all the same, and the real estate functions of applications used by real estate agents are not all the same, etc. In this way, through the real estate personalized characteristics of real estate agents, real estate question texts that are not related to the real estate personalized characteristics of real estate agents can be filtered out from multiple first real estate question texts, and real estate question texts related to the real estate personalized characteristics of real estate agents can be screened out, thereby making it more likely that the multiple second real estate question texts selected from the multiple first real estate question texts that match the real estate personalized characteristics of real estate agents contain questions that the real estate agent needs to ask.

[0159] It can be seen that through this application, the questions that the real estate agent needs to ask can be accurately mined from multiple real estate question texts collected in advance based on the real estate question text that the real estate agent has entered on the question interface. The questions that the real estate agent may need to ask can be mined without having multiple rounds of conversations with the real estate agent, thereby improving the efficiency of accurately mining the questions that the real estate agent needs to ask. Secondly, it can also improve the accuracy of mining the questions that the real estate agent needs to ask.

[0160] Furthermore, the greater the historical adoption volume of the second real estate question text, the greater the possibility that it is the question that the real estate agent needs to ask. In this way, displaying multiple second real estate question texts on the question interface in order of historical adoption volume from large to small can make it easier for the real estate agent to find the question that the real estate agent needs to ask among the multiple second real estate question texts more quickly and easily, thereby improving the efficiency of accurately mining the questions that the real estate agent needs to ask.

[0161] Reference Figure 5 , shows a structural block diagram of a data processing device of the present application, which is applied to a terminal, and the device includes: a third acquisition module 21, which is used to obtain the real estate question text input by the real estate agent on the question interface; the question interface is an interface in the application displayed on the screen of the terminal; a third sending module 22, which is used to send the real estate question text to the server, so that the server analyzes the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; according to the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, a plurality of first real estate question texts are screened in the real estate question text library, wherein the real estate question text The library includes a plurality of real estate question texts collected in advance; the real estate personalized characteristics of the real estate agent are obtained; among the plurality of first real estate question texts, a plurality of second real estate question texts matching the real estate personalized characteristics of the real estate agent are selected; the historical adoption volume of each second real estate question text is obtained; the plurality of second real estate question texts and the historical adoption volume of each second real estate question text are sent to the terminal; a third receiving module 23 is used to receive the plurality of second real estate question texts and the historical adoption volume of each second real estate question text sent by the server; a first display module 24 is used to display the plurality of second real estate question texts on the questioning interface in the order of the historical adoption volume from large to small.

[0162] In an optional implementation, the device also includes: a fourth acquisition module, used to acquire a target second real estate question text adopted by the real estate agent from multiple second real estate question texts displayed on the questioning interface; a fourth sending module, used to send the target second real estate question text to the server, so that the server generates a derivative question text associated with the target second real estate question text according to the target second real estate question text, the real estate personalized characteristics of the real estate agent and the question generation model; the derivative question text includes at least: a question text with keywords and positive semantics, a question text with keywords and negative semantics, and a question text with keywords and involving the business type of the real estate business involved in the target second real estate question text, the keyword is a word element in the target second real estate question text used to describe the question theme of the target second real estate question text; sending the derivative question text to the terminal; a fourth receiving module, used to receive the derivative question text sent by the server; a second display module, used to display the derivative question text on the questioning interface.

[0163] In the present application, based on the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, a first real estate question text whose word units and the relative distribution positions of word units are the same as the word units and the relative distribution positions of word units in the real estate question text is screened out in the real estate question text library; the first real estate question text whose word units and the relative distribution positions of word units are the same as the word units and the relative distribution positions of word units in the real estate question text is more likely to contain the questions that the real estate agent needs to ask.

[0164] In addition, different real estate agents have different personalized real estate features. For example, the types of real estate businesses that real estate agents engage in are different, and the real estate functions of applications used by real estate agents are different. In this way, through the personalized real estate features of real estate agents, real estate question texts that are not related to the personalized real estate features of real estate agents can be filtered out from multiple first real estate question texts, and real estate question texts related to the personalized real estate features of real estate agents can be screened out, thereby making it more likely that the multiple second real estate question texts selected from the multiple first real estate question texts that match the personalized real estate features of real estate agents contain questions that the real estate agents need to ask.

[0165] It can be seen that through this application, the questions that the real estate agent needs to ask can be accurately mined from multiple real estate question texts collected in advance based on the real estate question text entered by the real estate agent on the question interface. The questions that the real estate agent may need to ask can be mined without having multiple rounds of conversations with the real estate agent, thereby improving the efficiency of accurately mining the questions that the real estate agent needs to ask. Secondly, it can also improve the accuracy of mining the questions that the real estate agent needs to ask.

[0166] Furthermore, the greater the historical adoption volume of the second real estate question text, the greater the possibility that it is the question that the real estate agent needs to ask. In this way, displaying multiple second real estate question texts on the question interface in order of historical adoption volume from large to small can make it easier for the real estate agent to find the question that the real estate agent needs to ask among the multiple second real estate question texts more quickly and easily, thereby improving the efficiency of accurately mining the questions that the real estate agent needs to ask.

[0167] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0168] Optionally, an embodiment of the present invention further provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0169] The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the above method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0170] Figure 6 800 is a block diagram of an electronic device 800 shown in the present application. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0171] Reference Figure 6, the electronic device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0172] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0173] The memory 804 is configured to store various types of data to support operations on the device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, images, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0174] The power supply component 806 provides power to the various components of the electronic device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

[0175] The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0176] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0177] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

[0178] The sensor assembly 814 includes one or more sensors for providing various aspects of status assessment for the electronic device 800. For example, the sensor assembly 814 can detect the open / closed state of the device 800, the relative positioning of components, such as the display and keypad of the electronic device 800, and the sensor assembly 814 can also detect the position change of the electronic device 800 or a component of the electronic device 800, the presence or absence of contact between the user and the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and the temperature change of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0179] The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a communication standard, such as WiFi, a carrier network (such as 2G, 3G, 4G or 5G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast operation information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0180] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0181] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the instructions can be executed by a processor 820 of an electronic device 800 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0182] Figure 7 1 is a block diagram of an electronic device 1900 shown in the present application. For example, the electronic device 1900 may be provided as a server.

[0183] Reference Figure 7 , the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions executable by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method.

[0184] The electronic device 1900 may also include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input / output (I / O) interface 1958. The electronic device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™ or the like.

[0185] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0186] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0187] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

[0188] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the embodiments of the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0189] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0190] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0191] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0192] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0193] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0194] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A data processing method, characterized in that: Applied to the server, the method includes: receiving a real estate inquiry text sent by a terminal, the real estate inquiry text being text input by a real estate agent on an inquiry interface, the inquiry interface being an interface in an application displayed on a screen of the terminal; Analyze the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; According to the word units in the real estate question text and the relative distribution positions of the word units in the real estate question text, a plurality of first real estate question texts are selected in a real estate question text library, wherein the real estate question text library includes a plurality of real estate question texts collected in advance; Obtaining personalized property characteristics of the real estate agent; Selecting, from among the plurality of first real estate question texts, a plurality of second real estate question texts that match the real estate personalized characteristics of the real estate agent; Get the historical adoption volume of each second property question text; Send multiple second real estate question texts and the historical adoption volume of each second real estate question text to the terminal; so that the terminal displays multiple second real estate question texts on the questioning interface in descending order of the historical adoption volume.

2. The method according to claim 1, characterized in that The method further comprises: receiving a target second real estate question text sent by a terminal, wherein the target second real estate question text is a real estate question text adopted by the real estate agent from a plurality of second real estate question texts displayed on a questioning interface of the terminal; Generate a derivative question text associated with the target second real estate question text according to the target second real estate question text, the real estate personalized characteristics of the real estate agent, and the question generation model; The derived question text at least includes: at least one of a question text having keywords and positive semantics, a question text having keywords and negative semantics, and a question text having keywords and involving a business type of a real estate business involved in the target second real estate question text, wherein the keyword is a word element in the target second real estate question text used to describe the question theme of the target second real estate question text; The derived question text is sent to the terminal so that the terminal displays the derived question text on the questioning interface.

3. The method according to claim 1, characterized in that The method of screening a plurality of first real estate question texts in a real estate question text library according to the word units in the real estate question text and the relative distribution positions of the word units in the real estate question text comprises: For any real estate question text in the real estate question text library, obtain the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; Determine whether each word in the real estate question text is a word in the real estate question text; In the case where all the word units in the real estate question text are the word units in the real estate question text, determining whether the relative distribution positions of the word units in the real estate question text and the relative distribution positions of the word units in the real estate question text are the same as the relative distribution positions of the word units in the real estate question text; Under the same circumstances, the real estate problem text is determined as the first real estate problem text.

4. The method according to claim 1, characterized in that: The real estate personalized characteristics of the real estate agent include: the business type of the real estate business engaged in by the real estate agent among multiple types of real estate business; The selecting, from the plurality of first real estate question texts, a plurality of second real estate question texts that match the real estate personalized characteristics of the real estate agent comprises: For any first real estate problem text among the multiple first real estate problem texts, obtaining a business type of the real estate business involved in the first real estate problem text; Determining whether the business type of the real estate business involved in the first real estate question text is the business type of the real estate business engaged in by the real estate agent; In a case where the business type of the real estate business involved in the first real estate question text is the business type of the real estate business engaged in by the real estate agent, the first real estate question text is determined as the second real estate question text.

5. The method according to claim 1, characterized in that The real estate personalized features of the real estate agent include: among the multiple real estate functions of the application, the real estate functions used by the real estate agent; The selecting, from the plurality of first real estate question texts, a plurality of second real estate question texts that match the real estate personalized characteristics of the real estate agent comprises: For any first real estate question text among the plurality of first real estate question texts, obtaining a real estate function of an application program involved in the first real estate question text; Determining whether the real estate function of the application program involved in the first real estate question text is a real estate function used by the real estate agent; When the real estate function of the application program involved in the first real estate question text is the real estate function used by the real estate agent, the first real estate question text is determined as the second real estate question text.

6. A data processing method, characterized in that: Applied to a terminal, the method comprises: Acquire the real estate question text entered by the real estate agent on the question interface; the question interface is an interface in the application displayed on the screen of the terminal; Sending a real estate question text to a server so that the server analyzes the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; screening a plurality of first real estate question texts in a real estate question text library according to the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, wherein the real estate question text library includes a plurality of real estate question texts collected in advance; obtaining the real estate personalized characteristics of the real estate agent; selecting a plurality of second real estate question texts matching the real estate personalized characteristics of the real estate agent from the plurality of first real estate question texts; obtaining the historical adoption amount of each second real estate question text; sending a plurality of second real estate question texts and the historical adoption amount of each second real estate question text to a terminal; Receive multiple second real estate question texts sent by the server and the historical adoption amount of each second real estate question text; Multiple second real estate question texts are displayed on the question interface in order of historical adoption volume from large to small.

7. The method according to claim 6, characterized in that The method further comprises: Obtaining a target second real estate question text adopted by the real estate agent from among multiple second real estate question texts displayed on the questioning interface; Sending the target second real estate question text to the server, so that the server generates a derivative question text associated with the target second real estate question text according to the target second real estate question text, the real estate personalized characteristics of the real estate agent, and the question generation model; the derivative question text at least includes: at least one of a question text having keywords and positive semantics, a question text having keywords and negative semantics, and a question text having keywords and involving the business type of the real estate business involved in the target second real estate question text, the keyword being a word element in the target second real estate question text used to describe the question theme of the target second real estate question text; sending the derivative question text to the terminal; Receiving the derivative question text sent by the server; The derived question text is displayed on the questioning interface.

8. A data processing device, characterized in that: Applied to the server, the device comprises: A first receiving module is used to receive a real estate question text sent by a terminal, where the real estate question text is text that has been input by a real estate agent on a question interface, and the question interface is an interface in an application program displayed on a screen of the terminal; A parsing module, used to parse the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; A screening module is used to screen a plurality of first real estate question texts in a real estate question text library according to word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, wherein the real estate question text library includes a plurality of real estate question texts collected in advance; A first acquisition module is used to acquire the personalized characteristics of the real estate of the real estate agent; A selection module, for selecting, from among the plurality of first real estate question texts, a plurality of second real estate question texts that match the real estate personalized characteristics of the real estate agent; A second acquisition module is used to obtain the historical adoption amount of each second real estate question text; The first sending module is used to send multiple second real estate question texts and the historical adoption volume of each second real estate question text to the terminal; so that the terminal displays multiple second real estate question texts on the questioning interface in the order of historical adoption volume from large to small.

9. A data processing device, characterized in that: Applied to a terminal, the device comprises: The third acquisition module is used to acquire the real estate question text input by the real estate agent on the question interface; the question interface is an interface in the application displayed on the screen of the terminal; The third sending module is used to send the real estate question text to the server, so that the server analyzes the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text; according to the word units in the real estate question text and the relative distribution positions of each word unit in the real estate question text, a plurality of first real estate question texts are screened in the real estate question text library, wherein the real estate question text library includes a plurality of real estate question texts collected in advance; obtain the real estate personalized characteristics of the real estate agent; select a plurality of second real estate question texts matching the real estate personalized characteristics of the real estate agent from the plurality of first real estate question texts; obtain the historical adoption amount of each second real estate question text; send the plurality of second real estate question texts and the historical adoption amount of each second real estate question text to the terminal; A third receiving module is used to receive multiple second real estate problem texts and the historical adoption amount of each second real estate problem text sent by the server; The first display module is used to display multiple second real estate question texts on the questioning interface in order of historical adoption volume from large to small.

10. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the method according to any one of claims 1 to 7 when executed by the processor.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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