Question recommending method and question recommending system both in questions-and-answers community

A question-and-answer community and recommendation method technology, applied in the Internet field, can solve problems such as single recommended questions, low question answer rate, poor user experience effect, etc., to achieve the effect of improving experience effect and answer rate

Active Publication Date: 2013-10-23
SHENZHEN SHI JI GUANG SU INFORMATION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiments of the present invention is to provide a method and system for recommending questions in the question-and-answer community, aiming at solving the problem that when recommending questions to users

Method used

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  • Question recommending method and question recommending system both in questions-and-answers community
  • Question recommending method and question recommending system both in questions-and-answers community
  • Question recommending method and question recommending system both in questions-and-answers community

Examples

Experimental program
Comparison scheme
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Example Embodiment

[0025] Example one:

[0026] figure 1 The implementation process of the question recommendation method in the question and answer community provided by the first embodiment of the present invention is shown, and the details are as follows:

[0027] In step S101, a question keyword list of the question to be recommended is obtained.

[0028] In the specific implementation process, when a new question is raised, it is hoped that users who can answer the question can answer the new question. However, because they do not know which fields and / or users can answer the new question, or because they can The user who answers the new question cannot know that the question he can answer is asked, so the question recommendation method provided by the embodiment of the present invention can first obtain the keyword list of the question raised, specifically extracting the question raised, Keywords that can reflect the content of the question, etc., according to the keyword list, the new question...

Example Embodiment

[0078] Embodiment two:

[0079] figure 2 Shows the implementation process of the method for obtaining a user’s weighted question keyword list provided by the second embodiment of the present invention. Before using the question recommendation method in the question-and-answer community to recommend a new question to a user, it is necessary to obtain the user’s A list of keywords with weighted questions, detailed as follows:

[0080] In step S201, all the questions that the user has answered and refused to answer are obtained, and all the questions are sorted according to the time of occurrence.

[0081] In step S202, the problem keywords whose occurrence times are greater than 1 among the sorted problems are extracted, and a problem keyword list of the user is formed.

[0082] In step S203, the initial weight of each keyword in the question keyword list is set to 0.

[0083] In the specific implementation process, first collect the question list Q that a certain user U has answered a...

Example Embodiment

[0107] Example three:

[0108] image 3 The structure of the question recommendation system in the question and answer community provided by the third embodiment of the present invention is shown. For ease of description, only the parts related to the embodiment of the present invention are shown.

[0109] The question recommendation system in the Q&A community includes a main keyword list obtaining unit 31, a weight sum obtaining unit 32, a maximum value obtaining unit 33, a relevance obtaining unit 34, and a question pushing unit 35, among which:

[0110] The keyword list obtaining main unit 31 is configured to obtain a question keyword list of the question to be recommended.

[0111] In the embodiment of the present invention, when a new question is asked, users who want to answer the question are expected to answer the new question, but because they do not know which fields and / or users can answer the new question, or because The user who can answer the new question cannot know ...

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Abstract

The invention is applicable to the technical field of internet technology, provides a question recommending method and a question recommending system both in a questions-and-answers community. The method includes the following steps: matching a question keyword list of a to-be-recommended question with a preset weighted question keyword list of each user to acquire a weight sum of successfully-matched question keywords corresponding to each user, matching the question keyword list with preset weighted field keyword lists of each user to acquire a maximum value of a weight sum of successfully-matched field question keywords corresponding to each user, combining the weight sum of the successfully-matched question keywords corresponding to each user and the maximum value of the weight sum of the field question keywords to acquire relevancy of the to-be-recommended question and a user, and pushing the to-be-recommended question to one or more users with highest relevancy to improve answering rate of the users to the questions in the questions-and-answers community and improve user experience effect.

Description

technical field [0001] The invention belongs to the technical field of the Internet, and in particular relates to a question recommendation method and system in a question-and-answer community. Background technique [0002] At present, in the Internet Q&A community, it is often necessary to automatically recommend questions to users. Existing recommendation methods are mainly divided into two categories, namely collaborative recommendation methods and attribute-based recommendation methods. In the collaborative recommendation method, the system searches for users similar to the user to be recommended, and recommends suitable items to the user according to the items selected by these users; Users of these items, recommending the item for suitable users. For example, the electronic mall can find out the products that he may be interested in based on the user's historical purchase behavior and recommend them for him. In the attribute-based method, recommendations will be made...

Claims

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Application Information

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IPC IPC(8): G06F17/30H04L29/08
Inventor 勇凤伟何晓宁邹烷贺海军阳昕周建勋王钰琨郭奇
Owner SHENZHEN SHI JI GUANG SU INFORMATION TECH
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