Information processing method and device, equipment and storage medium

Abstract

The present disclosure provides an information processing method, device, equipment and storage medium, which can be applied to the field of communication technology and the field of financial technology. The method comprises: obtaining original information from a first database, wherein the original information comprises structured contact information; analyzing the original information to obtain a target contact information set, wherein the target contact information set comprises target contact information corresponding to different objects respectively; calculating the credibility of the target contact information corresponding to each object; updating the contact information corresponding to the target contact information set in a second database according to the credibility of the target contact information corresponding to each object; and obtaining a contact information list associated with query information from the second database by using the query information.

Description

Technical Field

[0001] This disclosure relates to the fields of communication technology and financial technology, and in particular to an information processing method, apparatus, device, medium and program product. Background Technology

[0002] As business expands and the need for communication within and between industries increases, the amount of contact information stored in the address book also grows. When a user's contact information changes, the corresponding contact information recorded in the address book also needs to be updated. However, relying solely on manual registration of address books often results in problems such as missing or incorrect contact information, delayed updates, and untimely synchronization, which can no longer meet daily operation and maintenance requirements. Summary of the Invention

[0003] In view of the above problems, this disclosure provides an information processing method, apparatus, device, medium and program product.

[0004] According to a first aspect of this disclosure, an information processing method is provided, comprising:

[0005] Obtain raw information from the first database, which includes structured contact information.

[0006] Analyzing the above raw information yields a set of target contact information, which includes target contact information corresponding to different objects.

[0007] Calculate the credibility of the target contact information corresponding to each of the above objects;

[0008] Based on the reliability of the target contact information information corresponding to each of the above objects, the contact information information corresponding to the above target contact information set in the second database is updated; and

[0009] Using the query information, a list of contact information related to the query information is obtained from the second database.

[0010] According to embodiments of this disclosure, obtaining original information from the first database includes:

[0011] Use the target application's read interface to obtain text information from the target application.

[0012] The above text information is structured to obtain the original information in the first database.

[0013] According to embodiments of this disclosure, the above-mentioned analysis of the original information yields a target contact information set, including:

[0014] Each structured contact information is segmented into words to obtain the segmentation results corresponding to each structured contact information.

[0015] For each of the above structured contact information entries, the word segmentation results are matched with the target keywords to obtain the matching degree corresponding to each of the above words;

[0016] For each structured contact information entry, the word segmentation results and the contact information in the second database are used to calculate the similarity between each pair of contact information entries; and

[0017] Based on the matching degree corresponding to each of the above words and the similarity between each pair of contact information, the above target contact information set is obtained from the above original information.

[0018] According to embodiments of this disclosure, the calculation of the credibility of the target contact information corresponding to each of the above objects includes:

[0019] For the target contact information corresponding to each of the above objects, the credibility of the target contact information corresponding to each of the above objects is calculated based on the data corresponding to each evaluation information and the weight corresponding to each of the above evaluation information. Here, the above similarity and the above matching degree both represent the evaluation information.

[0020] According to embodiments of this disclosure, updating the contact information information in the second database corresponding to the target contact information set based on the credibility of the target contact information information corresponding to each of the above objects includes:

[0021] Regarding the credibility of the target contact information corresponding to each of the above objects, if the credibility is below a threshold, the target contact information is verified to obtain the verification result; and

[0022] Based on the verification results, the contact information information corresponding to the target contact information set in the second database is updated.

[0023] According to embodiments of this disclosure, the above information processing method further includes:

[0024] The contact information in the second database is periodically verified to obtain a verification result corresponding to each piece of contact information; and

[0025] If the verification results indicate that the contact information is incorrect, the error information corresponding to the contact information in the second database is updated based on the correct information in the verification results.

[0026] According to embodiments of this disclosure, the above information processing method further includes:

[0027] Based on the contact information in the second database and the credibility of each contact information, a contact information table corresponding to the second database is generated.

[0028] A second aspect of this disclosure provides an information processing apparatus, comprising: a first acquisition module, an obtaining module, a calculation module, a first update module, and a second acquisition module. The first acquisition module is used to acquire raw information from a first database, wherein the raw information includes structured contact information. The obtaining module is used to analyze the raw information to obtain a set of target contact information, wherein the set of target contact information includes target contact information corresponding to different objects. The calculation module is used to calculate the credibility of the target contact information corresponding to each of the aforementioned objects. The first update module is used to update the contact information in a second database corresponding to the set of target contact information based on the credibility of the target contact information corresponding to each of the aforementioned objects. The second acquisition module is used to retrieve a list of contact information associated with the query information from the second database using query information.

[0029] A third aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform the methods described above.

[0030] A fourth aspect of this disclosure also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described above.

[0031] The fifth aspect of this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0032] According to the information processing method, apparatus, equipment, medium, and program products provided in this disclosure, the raw information obtained from the first database can be analyzed to obtain a set of target contact information. The credibility of the target contact information corresponding to each object can be calculated. Based on the credibility of the target contact information corresponding to each object, the contact information in the second database corresponding to the set of target contact information can be updated. This significantly improves the efficiency and accuracy of collecting, registering, and updating contact information in daily operation and maintenance. Subsequently, the query information can be used to obtain a list of contact information related to the query information from the second database, enabling the advantages of a large second database to be leveraged and improving overall communication efficiency. Attached Figure Description

[0033] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0034] Figure 1 This diagram illustrates an application scenario of the information processing method according to an embodiment of the present disclosure.

[0035] Figure 2 A flowchart illustrating an information processing method according to an embodiment of the present disclosure is shown schematically.

[0036] Figure 3 A flowchart illustrating the process of obtaining a set of target contact information according to an embodiment of the present disclosure is shown schematically.

[0037] Figure 4 A schematic block diagram of an information processing apparatus according to an embodiment of the present disclosure is shown; and

[0038] Figure 5 A block diagram schematically illustrates an electronic device suitable for implementing an information processing method according to an embodiment of the present disclosure. Detailed Implementation

[0039] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0040] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0041] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0042] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0043] In the technical solution of this invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0044] In the process of developing this disclosure, it was discovered that when faced with large amounts of data, the lack of automation tools causes enterprises to incur extremely high human resource costs for simple and repetitive tasks. Furthermore, in related technologies, relying solely on manual registration of contact information frequently results in issues such as missing or incorrect contact information, delayed updates, and untimely synchronization, which can no longer meet the requirements of daily operations and maintenance.

[0045] To this end, embodiments of this disclosure provide an information processing method, comprising: obtaining raw information from a first database, wherein the raw information includes structured contact information; analyzing the raw information to obtain a target contact information set, wherein the target contact information set includes target contact information corresponding to different objects; calculating the credibility of the target contact information corresponding to each object; updating the contact information in a second database corresponding to the target contact information set based on the credibility of the target contact information corresponding to each object; and obtaining a list of contact information associated with the query information from the second database using query information.

[0046] Figure 1 The diagram illustrates an application scenario of the information processing method according to an embodiment of the present disclosure.

[0047] like Figure 1 As shown, application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0048] Users can interact with server 105 via network 104 using at least one of the first terminal device 101, second terminal device 102, and third terminal device 103 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, second terminal device 102, and third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0049] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0050] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0051] For example, server 105 can retrieve raw information from the first database and analyze it to obtain a set of target contact information. Then, the credibility of the target contact information corresponding to each object can be calculated. Based on the credibility of the target contact information corresponding to each object, the contact information in the second database corresponding to the set of target contact information can be updated. Finally, the query information can be used to retrieve a list of contact information related to the query information from the second database.

[0052] It should be noted that the information processing method provided in this embodiment can generally be executed by server 105. Correspondingly, the information processing device provided in this embodiment can generally be located in server 105. The information processing method provided in this embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the information processing device provided in this embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0053] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0054] The following will be based on Figure 1 The described scene, through Figures 2-3 The information processing method of the disclosed embodiments will be described in detail.

[0055] Figure 2 A flowchart illustrating an information processing method according to an embodiment of the present disclosure is shown schematically.

[0056] like Figure 2 As shown, the method 200 includes operations S210 to S250.

[0057] In operation S210, raw information is retrieved from the first database.

[0058] According to embodiments of this disclosure, the original information may include structured contact information. A first database may be used to store the structured contact information. The contact information can represent information that can be used to contact and communicate with others. The contact information may include information such as name, telephone number, address, and email address.

[0059] In operation S220, the raw information is analyzed to obtain a set of target contact information.

[0060] According to embodiments of this disclosure, the target contact information set may include target contact information corresponding to different objects. The original information may include structured contact information corresponding to different objects. The target contact information is structured information. The structured contact information corresponding to each object can represent a single piece of structured contact information. Here, the object can represent a user.

[0061] According to embodiments of this disclosure, each piece of structured contact information is processed through word segmentation, keyword matching, and similarity matching, thereby extracting structured contact information with high keyword matching and similarity from the original information, thus obtaining target contact information corresponding to different objects. The target contact information can represent contact information that conforms to specifications, meaning that the matching degree and similarity of the target contact information meet their respective preset conditions, and the preset conditions can represent the respective thresholds for matching degree and similarity.

[0062] In operation S230, the credibility of the target contact information corresponding to each object is calculated.

[0063] According to embodiments of this disclosure, the credibility of target contact information corresponding to each object can be calculated based on the similarity and matching degree of the structured contact information corresponding to each object.

[0064] In operation S240, the contact information information corresponding to the target contact information set in the second database is updated based on the credibility of the target contact information information corresponding to each object.

[0065] According to embodiments of this disclosure, based on the credibility of the target contact information corresponding to each object, if the credibility is greater than a threshold, the target contact information can be directly entered into the second database to update the contact information corresponding to that target contact information in the second database. If the credibility is less than the threshold, the target contact information needs to be verified.

[0066] According to embodiments of this disclosure, for information that needs to be frozen / deleted, a strategy of prompting user confirmation or fully automated processing can be adopted. For example, when someone leaves a company, there will be a corresponding resignation email. By analyzing this email, a message can be sent to the second database indicating that a certain contact information entry needs to be frozen or deleted due to the user's resignation.

[0067] In operation S250, using the query information, a list of contact information related to the query information is retrieved from the second database.

[0068] According to embodiments of this disclosure, users can directly retrieve a list of corresponding contact information from a second database based on query information. The query information may include user name, company name, and related communication needs.

[0069] According to embodiments of this disclosure, when using a target application, such as an office email software, users can click the embedded "one-click access" button. This will first obtain the text content written by the user, and then analyze the text content to obtain query information, thereby returning a list of contact information that meets the requirements to the user.

[0070] For example, if someone wants to contact a company but doesn't know the specific contact information, they can directly enter the relevant query information to get a list of related contact information, that is, get the contact information associated with the company they want to contact.

[0071] For example, when sending an email, the email content may contain the names of some relevant companies, but it is unclear whether the specific user's contact information is involved. You can click the embedded "One-Click Access" button to analyze the email content and return a list of possible contact information.

[0072] According to embodiments of this disclosure, by analyzing the raw information obtained from the first database, a set of target contact information can be obtained, and the credibility of the target contact information corresponding to each object can be calculated. Thus, based on the credibility of the target contact information corresponding to each object, the contact information in the second database corresponding to the set of target contact information can be updated, which significantly improves the efficiency and accuracy of collecting, registering, and updating contact information in daily operation and maintenance work. Subsequently, the query information can be used to obtain a list of contact information related to the query information from the second database, enabling the advantages of a large second database to be leveraged and improving overall communication efficiency.

[0073] According to embodiments of this disclosure, obtaining original information from a first database includes: using the reading interface of a target application to obtain text information from the target application; and performing structured processing on the text information to obtain the original information in the first database, thereby obtaining the original information from the first database.

[0074] According to embodiments of this disclosure, the target application may include an email management application, such as Outlook. The text reading interface and sending interface of the target application can be obtained by contacting the target application. Using the reading interface, text information within the target application can be retrieved. This text information may include text information from emails, Excel files, TXT files, HTML files, etc.

[0075] According to embodiments of this disclosure, the text information may include unstructured contact information corresponding to each object. Since each user in the target application has different methods and habits for recording information, the format of the information obtained from each object in the target application is inconsistent. To facilitate subsequent information analysis, the text information needs to be structured to create a unified format for the contact information of different users.

[0076] According to embodiments of this disclosure, structured information can be stored in a first database so that structured information can be directly retrieved from the first database later.

[0077] The raw information may include structured contact information for each object. The text information may include information such as name, phone number, remarks, priority, and job title for each object.

[0078] For example, structured processing can be like organizing the text messages from different users into a unified table format, placing different types of information into their corresponding positions within the table. The first row of the table can include the names of each type of information, such as name, phone number, address, and job title, allowing you to place the names, phone numbers, addresses, and job titles from different users' text messages into their corresponding positions within the table.

[0079] According to embodiments of this disclosure, the acquired text information is processed in a structured manner to obtain structured contact information, and the obtained structured contact information is stored in a first database, thereby ensuring that the format of the information corresponding to each object is uniform, which facilitates the subsequent direct retrieval of structured contact information from the first database for analysis.

[0080] Figure 3 A flowchart illustrating the process of obtaining a set of target contact information according to an embodiment of the present disclosure is shown.

[0081] like Figure 3 As shown, the method 300 includes operations S310 to S340.

[0082] In operation S310, each structured contact information is segmented into words to obtain the segmentation result corresponding to each structured contact information.

[0083] According to embodiments of this disclosure, a word segmentation tool can be used to segment each piece of structured contact information to obtain a segmentation result corresponding to each piece of structured contact information. The word segmentation tool may include the jieba word segmentation tool.

[0084] For example, if a structured contact information includes a specific address, such as a province, city, and county, then word segmentation of that address can yield word segmentation results for the province, city, and county.

[0085] In operation S320, for each segmentation result corresponding to each structured contact information, each word in the segmentation result is matched with the target keyword to obtain the matching degree corresponding to each word.

[0086] According to embodiments of this disclosure, target keywords can represent keywords set manually. For each segmentation result corresponding to a structured contact information entry, each word in that structured contact information entry can be matched with the set target keywords to obtain the matching degree for each word.

[0087] According to embodiments of this disclosure, for each piece of structured contact information, if the matching degree with each word is greater than a threshold, it can be indicated that the structured contact information is useful; if the matching degree with each word is less than the threshold, it can be indicated that the structured contact information is useless. That is, structured contact information selected based on matching degree is relatively valuable.

[0088] In operation S330, for each segmentation result corresponding to each structured contact information and the contact information in the second database, the similarity between each pair of contact information is calculated.

[0089] According to embodiments of this disclosure, the contact information in the second database can also represent structured contact information, which is information extracted previously that conforms to the specifications.

[0090] According to embodiments of this disclosure, the similarity between structured contact information obtained from a first database can be calculated, as can the similarity between the obtained structured contact information and contact information in a second database.

[0091] According to embodiments of this disclosure, for each piece of structured contact information, if the similarity reaches a threshold, the contact information can be extracted to determine whether it is duplicate data or information about the same object.

[0092] For example, if the similarity between a contact information obtained from the first database and an existing contact information in the second database reaches 90%, it can be determined whether the contact information obtained from the first database and the contact information in the second database are related to the same object, and whether the contact information of that object has been updated.

[0093] According to embodiments of this disclosure, based on each word in each contact information, feature extraction is performed on the word to obtain a word vector corresponding to each word, and similarity matching is performed based on the word vectors to obtain a similarity score.

[0094] In operation S340, the target contact information set is obtained from the original information based on the matching degree corresponding to each word and the similarity between each pair of contact information.

[0095] According to embodiments of this disclosure, contact information with matching degree and similarity greater than a threshold can be extracted from the original information based on the matching degree corresponding to each word and the similarity between each pair of contact information information to obtain a target set of contact information information, that is, to extract contact information information that conforms to the specifications.

[0096] According to embodiments of this disclosure, by performing word segmentation, keyword matching, and similarity matching on each structured contact information, contact information with high matching and high similarity is selected from the original information, thereby obtaining target contact information that conforms to the specifications.

[0097] According to embodiments of this disclosure, calculating the credibility of target contact information corresponding to each object includes: for the target contact information corresponding to each object, calculating the credibility of the target contact information corresponding to each object based on the data corresponding to each evaluation information and the weight corresponding to each evaluation information.

[0098] According to embodiments of this disclosure, both similarity and matching degree can characterize evaluation information. Evaluation information may include information source (referring to whether it is read from an email or obtained from a file), update frequency (referring to the number of times the user's contact information is updated within a fixed period of time), similarity, matching degree, number of corrections, user ratings, etc.

[0099] According to embodiments of this disclosure, a weight value can be set for each piece of evaluation information, and the credibility of each piece of contact information can be calculated based on the weight value, structured contact information, and data corresponding to each piece of evaluation information.

[0100] According to embodiments of this disclosure, the credibility level can be used as a reference for all users, and if the credibility level is lower than the threshold, a warning will be triggered (e.g., the record will be displayed in red), which will require initiating an information verification process or reminding the administrator to intervene manually.

[0101] For example, if a contact's information hasn't been updated in a year, then that contact information is of low credibility.

[0102] According to the embodiments of this disclosure, the target contact information obtained in accordance with the specifications is recommended, but the information may not be entirely accurate. Therefore, it is necessary to calculate the credibility to ensure the accuracy of the obtained target contact information.

[0103] According to embodiments of this disclosure, the credibility of each target contact information is calculated based on evaluation information for user reference, thereby enabling verification of target contact information with credibility below a threshold to ensure the accuracy of the target contact information.

[0104] According to embodiments of this disclosure, updating the contact information in the second database corresponding to the target contact information set based on the credibility of the target contact information information corresponding to each object includes: verifying the target contact information information when the credibility is lower than a threshold, and obtaining a verification result; and updating the contact information in the second database corresponding to the target contact information set based on the verification result.

[0105] According to embodiments of this disclosure, for the credibility of the target contact information corresponding to each object, if the credibility is lower than a threshold, the target contact information needs to be verified in order to obtain a verification result.

[0106] According to embodiments of this disclosure, if the verification results indicate that the target contact information is correct, the target contact information can be directly entered into the second database to update the contact information in the second database corresponding to the target contact information.

[0107] According to embodiments of this disclosure, if the verification result indicates that the target contact information is incorrect, the incorrect information in the target contact information can be updated based on the correct information in the verification result, and the updated target contact information can be entered into the second database.

[0108] According to embodiments of this disclosure, if the credibility of the target contact information is below a threshold, the accuracy of the information entered into the second database can be ensured by verifying the target contact information.

[0109] According to embodiments of this disclosure, the above information processing method further includes: periodically verifying the contact information in the second database to obtain a verification result corresponding to each piece of contact information; and updating the error information corresponding to the contact information in the second database based on the correct information in the verification result when the verification result indicates that there is an error in the contact information.

[0110] According to embodiments of this disclosure, contact information from a second database can be periodically sent to users semi-automatically or fully automatically via the target application's sending interface to verify the information and obtain verification results.

[0111] The time period for sending verification information can be flexibly set according to actual needs, such as monthly, quarterly, or semi-annually, or information verification can be performed when the number of contact information accumulated in the first database reaches a certain value.

[0112] According to the embodiments of this disclosure, the contact information in the second database will not change if it is not modified. However, in reality, users' contact information may change, so it is necessary to verify the contact information in the second database periodically to ensure the accuracy of the information stored in the second database.

[0113] According to embodiments of this disclosure, if the verification result indicates that the contact information contains errors, the error information corresponding to the contact information in the second database can be updated based on the correct information in the verification result. If the verification result indicates that the contact information does not contain errors, no update is required.

[0114] According to embodiments of this disclosure, based on a set period or the timeliness requirements provided by the first database, information verification requests are proactively initiated for contact information in the second database, organized by company or organization, in order to further improve the accuracy and reliability of the contact information in the second database.

[0115] According to embodiments of this disclosure, the above information processing method further includes: generating a contact information table corresponding to the second database based on the contact information in the second database and the credibility corresponding to each contact information.

[0116] According to embodiments of this disclosure, the overall credibility of the second database can be obtained by averaging the credibility of each piece of contact information in the second database. Alternatively, the credibility of each type of contact information in the second database can be obtained by averaging the credibility of that type of contact information. The categories of contact information may include phone numbers and addresses, etc.

[0117] According to embodiments of this disclosure, a contact information table corresponding to the second database can be generated based on the total number of contact information entries in the second database, the overall credibility of the second database, and the credibility of each type of contact information.

[0118] According to embodiments of this disclosure, the overall credibility of the contact information table is compared with a threshold. If the overall credibility is lower than the threshold, the contact information in the second database can be verified to ensure the accuracy of the information in the second database.

[0119] According to embodiments of this disclosure, the contact information table can intuitively display information such as the current size and reliability of the second database, thereby helping maintenance personnel determine whether manual intervention is required and providing a basis for subsequent optimization.

[0120] Based on the above information processing method, this disclosure also provides an information processing apparatus. The following will be combined with... Figure 4 The device is described in detail.

[0121] Figure 4 A schematic block diagram of an information processing apparatus according to an embodiment of the present disclosure is shown.

[0122] like Figure 4 As shown, the information processing device 400 in this embodiment includes a first acquisition module 410, an acquisition module 420, a calculation module 430, a first update module 440, and a second acquisition module 450.

[0123] The first acquisition module 410 is used to acquire raw information from the first database, wherein the raw information includes structured contact information. In one embodiment, the first acquisition module 410 can be used to perform the operation S210 described above, which will not be repeated here.

[0124] The obtaining module 420 analyzes the original information to obtain a set of target contact information, wherein the set of target contact information includes target contact information corresponding to different objects. In one embodiment, the obtaining module 420 can be used to perform the operation S220 described above, which will not be repeated here.

[0125] The calculation module 430 is used to calculate the credibility of the target contact information corresponding to each object. In one embodiment, the calculation module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0126] The first update module 440 is used to update the contact information information corresponding to the target contact information set in the second database according to the credibility of the target contact information information corresponding to each object. In one embodiment, the first update module 440 can be used to perform the operation S240 described above, which will not be repeated here.

[0127] The second acquisition module 450 is used to retrieve a list of contact information associated with the query information from the second database. In one embodiment, the second acquisition module 450 may be used to perform the operation S250 described above, which will not be repeated here.

[0128] According to embodiments of this disclosure, the first acquisition module 410 includes an acquisition unit and a first obtaining unit.

[0129] The acquisition unit is used to acquire text information from the target application using the target application's read interface.

[0130] The first obtaining unit is used to perform structured processing on the text information to obtain the original information in the first database.

[0131] According to embodiments of this disclosure, the obtaining module 420 includes a word segmentation unit, a matching unit, a calculation unit, and a second obtaining unit.

[0132] The word segmentation unit is used to segment each structured contact information into words, and obtain the word segmentation result corresponding to each structured contact information.

[0133] The matching unit is used to match each word in the segmentation results corresponding to each structured contact information with the target keyword, and obtain the matching degree corresponding to each word.

[0134] The calculation unit is used to calculate the similarity between each pair of contact information based on the word segmentation results corresponding to each structured contact information and the contact information in the second database.

[0135] The second acquisition unit is used to obtain a set of target contact information from the original information based on the matching degree corresponding to each word and the similarity between each pair of contact information.

[0136] According to embodiments of this disclosure, the computing unit includes a computing subunit.

[0137] The calculation subunit is used to calculate the credibility of the target contact information corresponding to each object based on the data and weight corresponding to each evaluation information. Here, similarity and matching degree both represent the evaluation information.

[0138] According to embodiments of this disclosure, the first update module 440 includes a verification unit and an update unit.

[0139] The verification unit is used to verify the credibility of the target contact information corresponding to each object. If the credibility is lower than the threshold, the target contact information is verified to obtain the verification result.

[0140] The update unit is used to update the contact information information in the second database that corresponds to the target contact information information set based on the verification results.

[0141] According to embodiments of this disclosure, the information processing apparatus 400 further includes a verification module and a second update module.

[0142] The verification module is used to periodically verify the contact information in the second database and obtain the verification result corresponding to each piece of contact information.

[0143] The second update module is used to update the error information corresponding to the contact information in the second database based on the correct information in the verification results when the verification results indicate that there is an error in the contact information.

[0144] According to embodiments of this disclosure, the information processing apparatus further includes a generation module.

[0145] The generation module is used to generate a contact information table corresponding to the second database based on the contact information information in the second database and the credibility of each contact information.

[0146] According to embodiments of this disclosure, any plurality of modules among the first acquisition module 410, acquisition module 420, calculation module 430, first update module 440, and second acquisition module 450 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the first acquisition module 410, acquisition module 420, calculation module 430, first update module 440, and second acquisition module 450 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in hardware or firmware, or in any one of software, hardware, and firmware implementations, or in a suitable combination of any of these. Alternatively, at least one of the first acquisition module 410, the acquisition module 420, the calculation module 430, the first update module 440, and the second acquisition module 450 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0147] Figure 5 A block diagram schematically illustrates an electronic device suitable for implementing an information processing method according to an embodiment of the present disclosure.

[0148] like Figure 5 As shown, an electronic device 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage portion 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0149] RAM 503 stores various programs and data required for the operation of electronic device 500. Processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Processor 501 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 502 and / or RAM 503. It should be noted that the programs may also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0150] According to embodiments of this disclosure, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to a bus 504. The electronic device 500 may also include one or more of the following components connected to the input / output (I / O) interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output (I / O) interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.

[0151] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0152] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 502 and / or RAM 503 and / or one or more memories other than ROM 502 and RAM 503 described above.

[0153] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the item recommendation method provided in the embodiments of this disclosure.

[0154] When the computer program is executed by the processor 501, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0155] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 509, and / or installed from a removable medium 511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0156] In such an embodiment, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by processor 501, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0157] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0158] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0159] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0160] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. An information processing method, comprising: The original information is obtained from a first database, wherein the original information includes structured contact information, and the original information is obtained from the target application; The original information is analyzed to obtain a set of target contact information, wherein the set of target contact information includes target contact information corresponding to different objects, and the target contact information is contact information with high keyword matching degree and high similarity in the original information; For each target contact information corresponding to an object, the credibility of the target contact information corresponding to each object is calculated based on the data corresponding to each evaluation information and the weight corresponding to each evaluation information; wherein, the evaluation information includes information source, update frequency, similarity, matching degree, number of corrections and user reviews; The calculation of the similarity between each pair of contact information includes: extracting features from each word in each contact information to obtain a word vector corresponding to each word, and performing similarity matching based on the word vectors to obtain the similarity. The matching degree is used to filter valuable contact information, and the similarity degree is used to determine duplicate data or identify multiple contact information corresponding to the same object. Based on the credibility of the target contact information information corresponding to each object, determine whether to update the contact information information in the second database corresponding to the target contact information set; and update the contact information information in the second database corresponding to the target contact information set if the credibility is greater than a threshold; and Using the query information, a list of contact information associated with the query information is obtained from the second database and returned to the target application. The query information is obtained by analyzing the text content in the target application, and the list of contact information records the credibility of the contact information.

2. The method according to claim 1, wherein, The step of obtaining the original information from the first database includes: Text information is obtained from the target application using the target application's read interface; The text information is structured to obtain the original information in the first database, so as to retrieve the original information from the first database.

3. The method according to claim 1, wherein, The analysis of the original information to obtain a set of target contact information includes: Each structured contact information is segmented into words to obtain the segmentation result corresponding to each structured contact information. For each segmentation result corresponding to each structured contact information, each word in the segmentation result is matched with the target keyword to obtain the matching degree corresponding to each word; For each structured contact information entry, the word segmentation result and the contact information in the second database are used to calculate the similarity between each pair of contact information entries; and The target contact information set is obtained from the original information based on the matching degree corresponding to each word and the similarity between each pair of contact information.

4. The method according to claim 1, wherein, The step of updating the contact information information in the second database corresponding to the target contact information set based on the credibility of the target contact information information corresponding to each object includes: Regarding the credibility of the target contact information corresponding to each object, if the credibility is lower than a threshold, the target contact information is verified to obtain a verification result; and Based on the verification results, the contact information information corresponding to the target contact information set in the second database is updated.

5. The method according to claim 1, further comprising: The contact information in the second database is periodically verified to obtain the verification result corresponding to each piece of contact information; as well as If the verification result indicates that the contact information is incorrect, the error information corresponding to the contact information in the second database is updated according to the correct information in the verification result.

6. The method according to claim 1, further comprising: Based on the contact information in the second database and the credibility of each contact information, a contact information table corresponding to the second database is generated.

7. A device for obtaining a contact information list, comprising: The first acquisition module is used to acquire raw information from the first database, wherein the raw information includes structured contact information and is acquired from the target application; The acquisition module is used to analyze the original information to obtain a set of target contact information, wherein the set of target contact information includes target contact information corresponding to different objects, and the target contact information is contact information with high keyword matching degree and high similarity in the original information; The calculation module is used to calculate the credibility of the target contact information corresponding to each object, based on the data and weight corresponding to each evaluation information; wherein the evaluation information includes information source, update frequency, similarity, matching degree, number of corrections, and user ratings. The calculation of the similarity between each pair of contact information includes: extracting features from each word in each contact information to obtain a word vector corresponding to each word, and performing similarity matching based on the word vectors to obtain the similarity. The matching degree is used to filter valuable contact information, and the similarity degree is used to determine duplicate data or identify multiple contact information corresponding to the same object. The first update module is used to determine, based on the credibility of the target contact information information corresponding to each object, whether to update the contact information information in the second database corresponding to the target contact information set, and to update the contact information information in the second database corresponding to the target contact information set if the credibility is greater than a threshold; and The second acquisition module is used to retrieve a list of contact information associated with the query information from the second database and return the list of contact information to the target application. The query information is obtained by analyzing the text content in the target application, and the list of contact information records the credibility of the contact information.

8. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 6.

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