Science and Technology Information Consulting Service Platform Based on Big Data Analysis and Collection System

Abstract

The present invention provides a scientific and technological information consulting service platform based on a big data analysis and collection system, including: an identity authentication module for authenticating the identity of logged-in users; a retrieval module for, after confirming the identity of the logged-in user, retrieving in a database according to the information to be retrieved input, and sorting and recommending the retrieval results based on the information matching degree; a consulting module for, when the logged-in user has doubts about the retrieval results, sending a question to the service module; and a service module for answering the question of the logged-in user. The present invention provides users with a variety of consulting methods, enabling users to conduct scientific and technological information consulting at any time and place, reducing the waiting time for consulting services, and realizing self-service scientific and technological information consulting.

Description

Technical Field

[0001] The present invention relates to the technical field of consulting services, and particularly relates to a science and technology information consulting service platform based on a big data analysis and collection system. Background Art

[0002] Traditional technology information consulting mostly adopts telephone connection consulting and on-site consulting. These two consulting methods often take a lot of time. At the same time, consulting service personnel may need to repeat answers to the same questions. Even under the influence of subjective consciousness, it cannot be guaranteed that each reply is comprehensive and consistent, bringing many inconveniences to science and technology information consulting. Therefore, the present invention proposes a science and technology information consulting service platform based on a big data analysis and collection system to realize self-service consulting for scientific and technological personnel. Summary of the Invention

[0003] The present invention provides a science and technology information consulting service platform based on a big data analysis and collection system to solve the above problems and realize self-service consulting for scientific and technological personnel.

[0004] The present invention provides a science and technology information consulting service platform based on a big data analysis and collection system, including:

[0005] An identity verification module for verifying the identity of the logged-in user;

[0006] A retrieval module for, after confirming the identity of the logged-in user, retrieving in the database according to the information to be retrieved input, and sorting and recommending the retrieval results based on the information matching degree;

[0007] A consultation module for, when the logged-in user has questions about the retrieval results, sending a question to the service module;

[0008] A service module for answering the questions of the logged-in user.

[0009] Preferably, the identity verification module includes:

[0010] A first verification unit for verifying whether the account and login password of the logged-in user are correctly corresponding. If they are correctly corresponding, allowing the logged-in user to log in to the science and technology information consulting service platform;

[0011] Otherwise, not allowing the logged-in user to log in to the science and technology information consulting service platform;

[0012] A second verification unit for obtaining the account recharge information of the logged-in user and determining the usage permission of the logged-in user on the science and technology information consulting service platform according to the recharge information.

[0013] Preferably, the retrieval module includes:

[0014] A determination unit, configured to determine the type of the input method of the information to be retrieved by the logged-in user;

[0015] A processing unit, configured to determine the processing method of the information to be retrieved according to the type of the input method, and obtain a processing result of the information to be retrieved;

[0016] A retrieval unit, configured to perform a retrieval in a database according to the processing result, and sort and recommend the retrieval results based on the information matching degree.

[0017] Preferably, the consultation module includes:

[0018] A consultation guidance unit, configured to display question query rules to the logged-in user, and guide the logged-in user to correctly input a consultation question;

[0019] A semantic recognition unit, configured to recognize keywords according to the consultation question input by the logged-in user;

[0020] A quick consultation unit, configured to determine whether the consultation question is a question in a question database according to the keywords, and if so, query an answer to the question in the questions in the question database and quickly reply;

[0021] If not, send the consultation question to the service module.

[0022] Preferably, the consultation module further includes:

[0023] A service scoring unit, configured to make a satisfaction evaluation on the result of the question reply by the logged-in user after the question consultation ends, wherein the satisfaction evaluation includes a scoring evaluation and a text evaluation.

[0024] Preferably, the service module includes:

[0025] An answering unit, configured to make a reply to the consultation question of the logged-in user by a background artificial customer service personnel;

[0026] A question data collection unit, configured to collect consultation questions of the same retrieval result, and obtain the frequency of being asked for the same consultation question;

[0027] A database update unit, configured to, when the frequency of being asked is greater than a preset value, determine whether the consultation question is a question in the question database, and if not, collect an answer to the consultation question, and enter the consultation question and its answer into the question database.

[0028] Preferably, the service module further includes:

[0029] An answer collection and processing unit is used to take consultation questions with a frequency of being asked greater than a preset value and not in the question database as questions to be stored in the database, and obtain all the manual reply answers to the questions to be stored in the database and their corresponding satisfaction evaluation results;

[0030] In the satisfaction evaluation results, extract the text evaluation results, determine the nature of the text evaluation according to the first semantics of the text evaluation, and screen out multiple excellent manual reply answers;

[0031] Sort the multiple excellent manual reply answers according to the scoring evaluation results to obtain a sorting result;

[0032] According to the sorting result, screen out the excellent manual reply answers before a preset ranking as answers to be stored in the database;

[0033] According to sentence pattern analysis, determine the complexity of the answers to be stored in the database. If the answers to be stored in the database are simple sentences, obtain the answer to be stored in the database with the highest scoring;

[0034] At the same time, obtain the answer framework of the question answers in the question database, adjust the structure of the answer to be stored in the database with the highest scoring according to the answer framework to obtain the final answer to be stored in the database, and enter the final answer to be stored in the database and the corresponding question into the question database;

[0035] If the answers to be stored in the database are complex sentences, decompose all the answers to be stored in the database according to the second semantics of the answers to be stored in the database to obtain multiple first simple sentences;

[0036] Construct a semantic matrix, put the first simple sentences with the same semantics into the same semantic matrix, and obtain the sentence construction characteristics of the semantic matrix;

[0037] Based on the third semantics corresponding to different semantic matrices, generate second simple sentences according to the sentence construction characteristics;

[0038] According to the second semantics, combine all the second simple sentences to generate a new answer to be stored in the database;

[0039] Based on the answer framework of the question answers in the question database, adjust the structure of the new answer to be stored in the database to obtain the final answer to be stored in the database, and enter the final answer to be stored in the database and the corresponding question into the question database.

[0040] Preferably, a science and technology information consultation service platform based on a big data analysis and collection system further includes:

[0041] A data upload module is used for logged-in users to upload and share data and unsolved consultation questions to the science and technology information consultation service platform;

[0042] The data uploading module is further configured to monitor the download rate of the shared materials of the logged-in user, and when the download rate reaches the preset download rate, the shared materials are incorporated into the database of the science and technology information consulting service platform;

[0043] Meanwhile, corresponding rewards are issued to the logged-in user according to the usage value of the shared materials.

[0044] Preferably, a science and technology information consulting service platform based on a big data analysis and collection system further includes:

[0045] A science and technology information traceability module for a logged-in user to query traceability information of the retrieved science and technology information, where the traceability information includes the appearance time, development process, and current development level of the science and technology information.

[0046] Preferably, a science and technology information consulting service platform based on a big data analysis and collection system further includes: a platform management module, including:

[0047] A content determination unit for obtaining the platform login data of the science and technology information consulting service platform, where the login data includes logged-in user information and logged-in user retrieval records;

[0048] Based on the login information, classify the retrieval information of all logged-in users, obtain the first retrieval rate for each classification, and obtain the first target science and technology category of the science and technology information corresponding to the first highest retrieval rate;

[0049] Obtain the second retrieval rate of each same retrieval information in the first target science and technology category, and determine the first homepage display recommended content according to the sorting of the second retrieval rate;

[0050] Based on the login information, draw a regional distribution map of the logged-in users, and determine the second target science and technology category corresponding to the second highest retrieval rate in each region on the regional distribution map;

[0051] Judge whether the second target science and technology category is consistent with the first target science and technology category. If they are consistent, it is determined that the homepage recommended content of the science and technology information consulting service platform in the current region is the first homepage display recommended content;

[0052] Otherwise, obtain the difference between the first highest retrieval rate and the second highest retrieval rate. If the difference is within the preset range, obtain the third retrieval rate of each same retrieval information in the second target science and technology category, determine the second homepage display recommended content according to the sorting of the third retrieval rate, and cross-display the first homepage display recommended content and the second homepage display recommended content;

[0053] If the difference is not within the preset range, it is determined that the recommended content on the homepage of the science and technology information consulting service platform in the current area is the recommended content displayed on the second homepage;

[0054] A rhythm adjustment unit, configured to draw a traffic monitoring image of the science and technology information consulting service platform according to the login information, and draw a daily traffic change curve of the science and technology information consulting service platform according to the traffic monitoring image;

[0055] Obtain the variation law of the traffic change curve, and establish a mapping relationship between the scrolling speed of the homepage recommended content and the time axis based on the variation law;

[0056] According to the mapping relationship, control the scrolling speed of the homepage recommended content, and continuously monitor the platform login data of the science and technology information consulting service platform. Other features and advantages of the present invention will be described in the following specification, and part of them will become obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained by the structures specifically pointed out in the written specification, claims, and drawings.

[0057] The technical solutions of the present invention will be further described in detail below through the accompanying drawings and embodiments. Description of the Drawings

[0058] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0059] Figure 1 is a schematic diagram of a science and technology information consulting service platform based on a big data analysis and collection system of the present invention;

[0060] Figure 2 is a schematic diagram of an identity authentication module of a science and technology information consulting service platform based on a big data analysis and collection system of the present invention;

[0061] Figure 3 is a schematic diagram of a retrieval module of a science and technology information consulting service platform based on a big data analysis and collection system of the present invention;

[0062] Figure 4 is a schematic diagram of a consultation module of a science and technology information consulting service platform based on a big data analysis and collection system of the present invention;

[0063] Figure 5 is a schematic diagram of a service module of a science and technology information consulting service platform based on a big data analysis and collection system of the present invention;

[0064] Figure 6This is a schematic diagram of the platform management module of a science and technology information consulting service platform based on a big data analysis and collection system according to the present invention. Detailed implementation manners

[0065] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0066] Embodiment 1:

[0067] The present invention provides a science and technology information consulting service platform based on a big data analysis and collection system, as Figure 1 shown, including:

[0068] An identity verification module for verifying the identity of the logged-in user;

[0069] A retrieval module for, after confirming the identity of the logged-in user, retrieving in the database according to the input information to be retrieved, and sorting and recommending the retrieval results based on the information matching degree;

[0070] A consultation module for, when the logged-in user has questions about the retrieval results, sending a question to the service module;

[0071] A service module for answering the questions of the logged-in user.

[0072] In this embodiment, the information to be retrieved refers to the content entered by the logged-in user in the search box according to his own consultation content.

[0073] Advantages of the above embodiment: The present invention verifies the identity of the logged-in user, effectively improving the security of the user's consultation service; the setting of the retrieval module realizes self-service science and technology information consultation, and users can conduct science and technology information consultation at any time and place while waiting. At the same time, a consultation module is set up to provide manual answers for users, realizing multiple consultation methods and improving the service quality.

[0074] Embodiment 2:

[0075] On the basis of the above Embodiment 1, the identity verification module, as Figure 2 shown, includes:

[0076] A first verification unit for verifying whether the account and login password of the logged-in user are correctly corresponding. If they are correctly corresponding, the logged-in user is allowed to log in to the science and technology information consulting service platform;

[0077] Otherwise, the logged-in user is not allowed to log in to the science and technology information consulting service platform;

[0078] A second verification unit, configured to obtain the account recharge information of the logged-in user, and determine the usage permission of the logged-in user on the technology information consulting service platform according to the recharge information.

[0079] In this embodiment, the usage permission includes an online browsing permission and a download permission.

[0080] Beneficial effects of the above embodiment: In the present invention, the first verification unit verifies the identity of the logged-in user, effectively improving the security of the user's consulting service. The second verification unit verifies the usage permission of the logged-in user on the technology information consulting service platform, safeguarding the interests of the platform.

[0081] Embodiment 3:

[0082] Based on the above Embodiment 1, the retrieval module, as Figure 3 shown, includes:

[0083] A determination unit, configured to determine the type of the input method of the information to be retrieved by the logged-in user;

[0084] A processing unit, configured to determine the processing method of the information to be retrieved according to the type of the input method, and obtain the processing result of the information to be retrieved;

[0085] A retrieval unit, configured to perform a retrieval in the database according to the processing result, and sort and recommend the retrieval results based on the information matching degree.

[0086] In this embodiment, the types of the input method include voice input, text input, and photo recognition.

[0087] In this embodiment, the processing method specifically means that when the retrieval information input method is text input, directly retrieve in the database according to the input text; when the retrieval information input method is voice input, the voice recognition system of the technology information consulting platform generates corresponding text according to the voice input by the logged-in user and retrieves in the database; when the retrieval information input method is photo recognition, identify the image information according to the photo recognition system, generate corresponding text according to the image information, and retrieve in the database.

[0088] In this embodiment, the information matching degree refers to the matching degree between the content obtained by retrieving in the database and the content obtained by the logged-in user.

[0089] Beneficial effects of the above embodiment: The present invention determines the type of the input method of the information to be retrieved by the logged-in user and adopts different processing methods according to different input methods, providing convenience for the user's technology information consulting; at the same time, sorting and recommending the retrieved information, improving the service quality.

[0090] Embodiment 4:

[0091] Based on the above-mentioned Embodiment 1, the consultation module, as Figure 4 shown, includes:

[0092] A consultation guidance unit, configured to display question query rules to the logged-in user and guide the logged-in user to correctly input a consultation question;

[0093] A semantic recognition unit, configured to recognize keywords according to the consultation question input by the logged-in user;

[0094] A quick consultation unit, configured to determine whether the consultation question is a question in the question database according to the keywords. If so, query the question answer in the questions in the question database and give a quick reply;

[0095] If not, send the consultation question to the service module.

[0096] In this embodiment, the question query rule refers to the format and steps for inputting questions during the sub-consultation of the scientific and technological information consultation service platform of the present invention.

[0097] In this embodiment, the question database refers to a database that stores the questions most frequently asked by the logged-in user and their answers obtained by the platform based on big data analysis of the logged-in user.

[0098] Beneficial effects of the above-mentioned embodiment: The present invention displays question query rules to the logged-in user, guides the logged-in user to correctly input a consultation question, enables the user to more clearly describe the consultation question, improves the consultation efficiency, and at the same time, facilitates the correct understanding of the consultation question by the manual reply; the quick consultation unit realizes the quick reply to the consultation question, reduces the consultation time for common questions, and reduces the workload of the consultation service personnel.

[0099] Embodiment 5:

[0100] Based on the above-mentioned Embodiment 4, the consultation module, as Figure 4 shown, further includes:

[0101] A service scoring unit, configured to make a satisfaction evaluation on the question reply result by the logged-in user after the question consultation ends, where the satisfaction evaluation includes a scoring evaluation and a text evaluation.

[0102] Beneficial effects of the above-mentioned embodiment: The present invention enables the logged-in user to make a satisfaction evaluation on the question reply result after the question consultation ends, which is beneficial for the platform to timely understand the experience of the logged-in user with the platform and timely improve the platform service problems; at the same time, it also provides a basis for the update of the platform question database.

[0103] Embodiment 6:

[0104] Based on the above-mentioned Embodiment 1, the service module, as Figure 5As shown in the figure, it includes:

[0105] An answering unit, which is used for the background artificial customer service staff to answer the consulting questions of logged-in users;

[0106] A question data collection unit, which is used to collect the consulting questions of the same search result and obtain the frequency of being asked for the same consulting question;

[0107] A database update unit, which is used to judge whether the consulting question is in the question database when the frequency of being asked is greater than a preset value. If not, collect the answer of the consulting question and enter the consulting question and its answer into the question database.

[0108] In this embodiment, the frequency of being asked refers to the proportion of the same question (including questions with the same answer) in all questions of the same search result within the same time period.

[0109] The beneficial effects of the above embodiment: When the logged-in user's independent consultation cannot solve the problem, the present invention uses the background artificial customer service staff to answer the consulting questions of the logged-in user, providing multiple consultation options for the user; at the same time, when the asking rate of the same question is greater than the preset value, the question is entered into the question database, enriching the question database, injecting new content into the question database, and improving the completion rate of the logged-in user's independent query.

[0110] Embodiment 7:

[0111] On the basis of the above Embodiment 6, the service module, as Figure 5 shown in the figure, further includes:

[0112] An answer collection and processing unit, which is used to take the consulting questions with the frequency of being asked greater than the preset value and not in the question database as the questions to be stored in the database, and obtain all the manual reply answers of the questions to be stored in the database and their corresponding satisfaction evaluation results;

[0113] In the satisfaction evaluation results, extract the text evaluation results, determine the nature of the text evaluation according to the first semantics of the text evaluation, and screen out multiple excellent manual reply answers;

[0114] According to the scoring evaluation results, sort the multiple excellent manual reply answers to obtain a sorting result;

[0115] According to the sorting result, screen out the excellent manual reply answers before the preset ranking as the answers to be stored in the database;

[0116] According to the sentence pattern analysis, determine the complexity of the answers to be stored in the database. If the answers to be stored in the database are simple sentences, obtain the answer to be stored in the database with the highest scoring evaluation;

[0117] Meanwhile, obtain the answer framework of the answers in the question database, adjust the structure of the answer to be stored in the database with the highest scoring based on the answer framework to obtain the final answer to be stored in the database, and enter the final answer to be stored in the database and the corresponding question into the question database;

[0118] If the answer to be stored in the database is a complex sentence, decompose all the answers to be stored in the database according to the second semantic meaning of the answer to be stored in the database to obtain multiple first simple sentences;

[0119] Construct a semantic matrix, place the first simple sentences with the same semantic meaning in the same semantic matrix, and obtain the sentence construction characteristics of the semantic matrix;

[0120] Based on the third semantic meaning corresponding to different semantic matrices, generate second simple sentences according to the sentence construction characteristics;

[0121] According to the second semantic meaning, combine all the second simple sentences to generate a new answer to be stored in the database;

[0122] Based on the answer framework of the answers in the question database, adjust the structure of the new answer to be stored in the database to obtain the final answer to be stored in the database, and enter the final answer to be stored in the database and the corresponding question into the question database.

[0123] In this embodiment, the question to be stored in the database refers to a question whose asking frequency is greater than a preset value and is not in the consultation questions of the question database

[0124] In this embodiment, the first semantic meaning refers to the semantic meaning of the sentence corresponding to the text evaluation of the question to be stored in the database.

[0125] In this embodiment, the nature of the text evaluation includes bad reviews, medium reviews, and good reviews.

[0126] In this embodiment, an excellent artificial reply answer refers to an answer whose nature of the text evaluation of the question to be stored in the database is a good review.

[0127] In this embodiment, the answer to be stored in the database refers to several answers ranked at the front according to the score ranking of the excellent artificial reply answers.

[0128] In this embodiment, the complexity refers to the complex length of the answer to be stored in the database, including simple sentences and complex sentences. A single sentence is a simple sentence, and two or more are complex sentences.

[0129] In this embodiment, the answer framework refers to the structure of the answers in the question database. Structure adjustment means that when the structure of the artificial reply answer is different from the structure of the answers in the question database, adjust the structure of the artificial reply answer. For example, the questions in the question database adopt a reply structure of first cause and then effect, while the artificial reply answer adopts a reply structure of first effect and then cause.

[0130] In this embodiment, the final stored answer refers to the manual reply answer entered into the question database.

[0131] In this embodiment, the second semantics refers to the semantics when the answer to be stored is a complex sentence.

[0132] In this embodiment, the first simple sentence refers to multiple simple sentences obtained by splitting according to the semantics when the answer to be stored is a complex sentence.

[0133] In this embodiment, the semantic matrix refers to a matrix used to store the first simple sentences with the same semantics (the third semantics).

[0134] In this embodiment, the sentence construction feature refers to the keywords of the short sentences in the same semantic matrix and the logical relationship expressed by the simple sentence.

[0135] In this embodiment, the second simple sentence is automatically generated according to the keywords of the short sentences in the same semantic matrix, the logical relationship expressed by the simple sentence, and the semantic system.

[0136] Beneficial effects of the above embodiment: The invention has a questioning frequency greater than a preset value and is not in the question database of the consulting question entry platform of the question database. At the same time, the answers to the consulting questions are spliced and combined to obtain the best reply sentence, and the structure of the reply sentence is adjusted according to the answer structure of the questions and answers in the question database to ensure that the questions and answers entered into the question database meet the requirements of the question database, ensuring the simplicity of the platform's convenient reply answers and improving the user service experience.

[0137] Embodiment 8:

[0138] Based on the above Embodiment 1, a science and technology information consulting service platform based on a big data analysis and collection system further includes:

[0139] A data upload module for a logged-in user to upload and share materials and unsolved consulting questions to the science and technology information consulting service platform;

[0140] The data upload module is also used to monitor the download rate of the shared materials of the logged-in user. When the download rate reaches the preset download rate, the shared materials are included in the database of the science and technology information consulting service platform;

[0141] At the same time, corresponding rewards are issued to the logged-in user according to the usage value of the shared materials.

[0142] In this embodiment, the shared materials include the reply of the logged-in user to a certain consulting question and also include the works and documents of the logged-in user.

[0143] Beneficial effects of the above embodiments: Through the data upload module of the present invention, logged-in users can upload and share materials and unsolved consultation questions to the science and technology information consultation service platform, enriching the platform content; at the same time, corresponding rewards are given to logged-in users according to the usage value of the shared materials, motivating users' creative enthusiasm on the platform and increasing the platform activity.

[0144] Embodiment 9:

[0145] Based on the above Embodiment 1, a science and technology information consultation service platform based on a big data analysis and collection system further includes:

[0146] A science and technology information traceability module for logged-in users to query traceability information of the retrieved science and technology information, where the traceability information includes the appearance time, development process, and current development level of the science and technology information.

[0147] Beneficial effects of the above embodiments: Logged-in users of the present invention can query traceability information of the retrieved science and technology information; it is beneficial for users to timely understand the situation of the consultation content.

[0148] Embodiment 10:

[0149] Based on the above Embodiment 1, a science and technology information consultation service platform based on a big data analysis and collection system, as Figure 6 shown, the platform management module includes:

[0150] A content determination unit for obtaining the platform login data of the science and technology information consultation service platform, where the login data includes logged-in user information and logged-in user retrieval records;

[0151] Based on the login information, classify the retrieval information of all logged-in users, obtain the first retrieval rate of each classification, and obtain the first target science and technology category of the science and technology information corresponding to the first highest retrieval rate;

[0152] Obtain the second retrieval rate of each same retrieval information in the first target science and technology category, and determine the first homepage display recommended content according to the ranking of the second retrieval rate;

[0153] Based on the login information, draw the regional distribution map of the logged-in users, and determine the second target science and technology category corresponding to the second highest retrieval rate of each region on the regional distribution map;

[0154] Judge whether the second target science and technology category is consistent with the first target science and technology category. If they are consistent, determine that the homepage recommended content of the science and technology information consultation service platform in the current region is the first homepage display recommended content;

[0155] Otherwise, obtain the difference between the first highest retrieval rate and the second highest retrieval rate. If the difference is within a preset range, obtain the third retrieval rate of each same retrieval information of the second target technology category, determine the recommended content for display on the second homepage according to the sorting of the third retrieval rate, and cross-display the recommended content for display on the first homepage and the recommended content for display on the second homepage;

[0156] If the difference is not within the preset range, determine that the recommended content for the homepage of the technology information consulting service platform in the current area is the recommended content for display on the second homepage;

[0157] The rhythm adjustment unit is configured to draw a traffic monitoring image of the technology information consulting service platform according to the login information, and draw a daily traffic change curve of the technology information consulting service platform according to the traffic monitoring image;

[0158] Obtain the variation law of the traffic change curve, and establish a mapping relationship between the scrolling speed of the recommended content for the homepage and the time axis based on the variation law;

[0159] Control the scrolling speed of the recommended content for the homepage according to the mapping relationship, and continuously monitor the platform login data of the technology information consulting service platform. In this embodiment, the logged-in user information includes the user's logged-in IP address, the user's login time, and the login account, etc.

[0160] In this embodiment, the first retrieval rate refers to the frequency of a same type of technology information (for example, communication engineering) being retrieved in all retrieval contents.

[0161] In this embodiment, the first highest retrieval rate is the maximum value among the first retrieval rates.

[0162] In this embodiment, the first target technology category refers to the technology information category with the highest first retrieval rate (for example, communication engineering).

[0163] In this embodiment, the second retrieval rate refers to the frequency of each of all retrieval contents (such as wired communication, wireless communication, postal communication, etc.) of the technology information category with the highest first retrieval rate being retrieved in the highest technology information category.

[0164] In this embodiment, the recommended content for display on the first homepage refers to several retrieved contents with the highest second retrieval rate.

[0165] In this embodiment, the regional distribution map refers to the distribution image of the login addresses of the logged-in users of the technology information consulting service platform.

[0166] In this embodiment, the second highest retrieval rate refers to the maximum value of the frequency of a same type of technology information (for example, mechanical engineering) corresponding to each region on the regional distribution map being retrieved in all retrieval contents of the region.

[0167] In this embodiment, the second target technology category refers to the technology information category with the highest retrieval rate corresponding to each region on the regional distribution map (for example, mechanical engineering).

[0168] In this embodiment, the third retrieval rate refers to the frequency at which all the technology information categories with the highest retrieval rates corresponding to each region on the regional distribution map are retrieved by the retrieved content (such as mechanical design, mechanical manufacturing, mechanical maintenance, etc.) respectively within the highest technology information category.

[0169] In this embodiment, the recommended content displayed on the second home page refers to the several retrieved contents with the highest third retrieval rate.

[0170] In this embodiment, the daily traffic change curve refers to the curve graph of the daily traffic change of the technology information consulting service platform.

[0171] Beneficial effects of the above embodiment: The present invention monitors the platform login retrieval rate through the platform management module, and adjusts the recommended content displayed on the platform's home page according to the monitoring results. At the same time, it timely adjusts the recommended content displayed on the regional home page according to the regional retrieval preferences, which is conducive to the platform developing its own characteristic technology information consulting and improving the platform's competitiveness.

[0172] Embodiment 11:

[0173] Based on the above Embodiment 3, the retrieval module of a technology information consulting service platform based on a big data analysis and collection system further includes a result sorting sub-module for:

[0174] An activity calculation unit for obtaining information data of different retrieval results, where the information data includes the single-view duration, the number of retrieval times, and the storage duration of the retrieval result, and calculating the platform activity of the j-th retrieval result using the following formula:

[0175]

[0176] where H j represents the platform activity of the j-th retrieval result; t j,i represents the duration of the i-th view of the j-th retrieval result; M j represents the total number of views of the j-th retrieval result; T j represents the storage duration of the j-th retrieval result in the platform database; ε represents the platform data feedback error factor, with a value in (0, 0.01); γ represents the platform download rate of the j-th retrieval result;

[0177] A matching degree calculation unit, configured to calculate the information matching degree between the j-th search result and the information to be retrieved input by the logged-in user based on the platform activity of the j-th search result and the following formula:

[0178]

[0179] where P j represents the information matching degree between the j-th search result and the information to be retrieved input by the logged-in user; ω1 represents the weight of the platform activity of the j-th search result, taking 0.3; ω2 represents the weight of the similarity between the j-th search result and the information to be retrieved input by the logged-in user, taking 0.7; V1 represents the keyword vector of the j-th search result; |V1| represents the modulus of the keyword vector of the j-th search result; V2 represents the keyword vector of the information to be retrieved input by the logged-in user; |V2| represents the modulus of the keyword vector of the information to be retrieved input by the logged-in user; represents the similarity between the j-th search result and the information to be retrieved input by the logged-in user; β represents the extraction error of keywords, taking (0, 0.03); Δ(ω1×H j ) represents the fine-tuning factor for the similarity between the j-th search result and the information to be retrieved input by the logged-in user. The greater the platform activity, the greater the corresponding fine-tuning factor, and P j has a maximum value of 1.

[0180] A sorting unit, configured to sort the search results based on the information matching degree.

[0181] Advantageous effects of the above technical solution: The present invention calculates the matching degree between the search results of the science and technology information consulting service platform and the information to be retrieved input by the logged-in user, and sorts the search results according to the information matching degree, so as to provide the logged-in user with the search results with the best similarity and activity, and improve the user service experience.

[0182] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. A scientific and technological information consulting service platform based on a big data analysis and collection system, characterized in that, Including: An authentication module for authenticating the identity of the logged-in user; A retrieval module for retrieving in the database according to the input information to be retrieved after confirming the identity of the logged-in user, and sorting and recommending the retrieval results based on the information matching degree; A consultation module for sending a question to the service module when the logged-in user has doubts about the retrieval results; A service module for answering the questions of the logged-in user; The science and technology information consultation service platform further includes: a platform management module, including: A content determination unit for obtaining the platform login data of the science and technology information consultation service platform, where the login data includes logged-in user information and logged-in user retrieval records; Based on the login data, classifying the retrieval information of all logged-in users, obtaining the first retrieval rate of each classification, and obtaining the first target technology type of the science and technology information corresponding to the first highest retrieval rate; Obtaining the second retrieval rate of each same retrieval information in the first target technology type, and determining the first homepage display recommendation content according to the sorting of the second retrieval rate; Based on the login data, drawing the regional distribution map of the logged-in users, and determining the second target technology type corresponding to the second highest retrieval rate of each region on the regional distribution map; Judging whether the second target technology type is consistent with the first target technology type. If they are consistent, it is determined that the homepage recommendation content of the science and technology information consultation service platform in the current region is the first homepage display recommendation content; Otherwise, obtaining the difference between the first highest retrieval rate and the second highest retrieval rate. If the difference is within the preset range, obtaining the third retrieval rate of each same retrieval information of the second target technology type, and determining the second homepage display recommendation content according to the sorting of the third retrieval rate, and cross-displaying the first homepage display recommendation content and the second homepage display recommendation content; If the difference is not within the preset range, it is determined that the homepage recommendation content of the science and technology information consultation service platform in the current region is the second homepage display recommendation content; A rhythm adjustment unit for drawing the traffic monitoring image of the science and technology information consultation service platform according to the login data, and drawing the daily traffic change curve of the science and technology information consultation service platform according to the traffic monitoring image; Obtaining the change rule of the traffic change curve, and establishing a mapping relationship between the scrolling speed of the homepage recommendation content and the time axis based on the change rule; According to the mapping relationship, controlling the scrolling speed of the homepage recommendation content, and continuously monitoring the platform login data of the science and technology information consultation service platform.

2. The technology information consulting service platform based on the big data analysis and collection system according to claim 1, wherein, The authentication module includes: A first verification unit for verifying whether the account and login password of the logged-in user are correct. If they are correct, allowing the logged-in user to log in to the science and technology information consultation service platform; Otherwise, not allowing the logged-in user to log in to the science and technology information consultation service platform; A second verification unit for obtaining the account recharge information of the logged-in user, and determining the usage permission of the logged-in user on the science and technology information consultation service platform according to the recharge information.

3. The technology information consulting service platform based on the big data analysis and collection system according to claim 1, wherein, The retrieval module includes: A determination unit for determining the type of the input method of the information to be retrieved by the logged-in user; A processing unit for determining the processing method of the information to be retrieved according to the type of the input method, and obtaining the processing result of the information to be retrieved; A retrieval unit for retrieving in the database according to the processing result, and sorting and recommending the retrieval results based on the information matching degree.

4. A technology information consulting service platform based on the big data analysis and collection system according to claim 1, characterized in that, The consultation module includes: A consultation guidance unit for displaying the question query rules to the logged-in user and guiding the logged-in user to correctly input the consultation question; A semantic recognition unit for identifying keywords according to the consultation question input by the logged-in user; A quick consultation unit for determining whether the consultation question is a question in the question database according to the keywords. If so, query the question answer in the questions in the question database and give a quick reply; If not, send the consultation question to the service module.

5. The technology information consulting service platform based on the big data analysis and collection system according to claim 4, wherein The consultation module further includes: A service scoring unit for the logged-in user to make a satisfaction evaluation on the question reply result after the question consultation. Among them, the satisfaction evaluation includes a scoring evaluation and a text evaluation.

6. The technology information consulting service platform based on the big data analysis and collection system according to claim 1, wherein The service module includes: An answering unit for the background artificial customer service personnel to reply to the consultation questions of the logged-in user; A question data collection unit for collecting the consultation questions of the same retrieval result and obtaining the questioned frequency of the same consultation question; A database update unit for determining whether the consultation question is in the question database when the questioned frequency is greater than a preset value. If not, collect the answer to the consultation question and enter the consultation question and its answer into the question database.

7. The technology information consulting service platform based on the big data analysis and collection system according to claim 6, wherein, The service module further includes: An answer collection and processing unit for taking the consultation questions with a questioned frequency greater than the preset value and not in the question database as the questions to be stored in the database, obtaining all the manual reply answers of the questions to be stored in the database and their corresponding satisfaction evaluation results; In the satisfaction evaluation results, extract the text evaluation results, determine the nature of the text evaluation according to the first semantics of the text evaluation, and screen out multiple excellent manual reply answers; Sort the multiple excellent manual reply answers according to the scoring evaluation results to obtain a sorting result; According to the sorting result, screen out the excellent manual reply answers before the preset ranking as the answers to be stored in the database; According to the sentence pattern analysis, determine the complexity of the answer to be stored in the database. If the answer to be stored in the database is a simple sentence, obtain the answer to be stored in the database with the highest scoring score; At the same time, obtain the answer structure of the question answers in the question database, and adjust the structure of the answer to be stored in the database with the highest scoring score according to the answer structure to obtain the final answer to be stored in the database, and enter the final answer to be stored in the database and the corresponding question into the question database; If the answer to be stored in the database is a complex sentence, decompose all the answers to be stored in the database according to the second semantics of the answer to be stored in the database to obtain multiple first simple sentences; Construct a semantic matrix, put the first simple sentences with the same semantics into the same semantic matrix, and obtain the sentence construction characteristics of the semantic matrix; Generate second simple sentences based on the third semantics corresponding to different semantic matrices according to the sentence construction characteristics; According to the second semantic meaning, all the second simple statements are combined to generate a new answer to be stored in the database; Based on the answer structure of the question answers in the question database, the structure of the new answer to be stored in the database is adjusted to obtain the final answer to be stored in the database, and the final answer to be stored in the database and the corresponding question are entered into the question database.

8. A technology information consulting service platform based on a big data analysis and collection system according to claim 1, characterized in that, It further includes: A data upload module, which is used for the logged-in user to upload and share materials and unsolved consultation questions to the science and technology information consultation service platform; The data upload module is further used to monitor the download rate of the shared materials of the logged-in user. When the download rate reaches the preset download rate, the shared materials are incorporated into the database of the science and technology information consultation service platform; Meanwhile, corresponding rewards are issued to the logged-in user according to the usage value of the shared materials.

9. The technology information consulting service platform based on the big data analysis and collection system according to claim 1, characterized in that, It further includes: A science and technology information traceability module, which is used for the logged-in user to query the traceability information of the retrieved science and technology information, where the traceability information includes the appearance time, development process and current development level of the science and technology information.

Images