Question routing method based on word vectors

A technology of word vectors and questions, applied in the field of question routing based on word vectors, can solve problems such as reducing accuracy

Active Publication Date: 2015-05-20
DALIAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Such methods improve the recall rate of retrieval to a certain extent, but often

Method used

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  • Question routing method based on word vectors
  • Question routing method based on word vectors
  • Question routing method based on word vectors

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Embodiment Construction

[0046] The present invention will be described below with reference to the accompanying drawings.

[0047] like figure 1 As shown, a problem routing method based on word vector includes the following steps:

[0048] Step 1. Construction of user profiles: construct profiles for users based on the user's answer history. Users who have answered questions in the community Q&A are all candidates for a new question. The construction of each user profile includes the following sub-steps:

[0049] Step (a), download all data from the website provided by Stackoverflow website from July 2008 to March 2014, the data is in XML format, read the XML file format to extract all questions, including the questions Tag field, title field and content body field;

[0050] Step (b), collecting those questions selected as the best answer among the questions answered by the user to form the user's profile;

[0051] Step (c), ignoring the users who are selected as the best answer in a relatively sm...

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Abstract

The invention relates to a question routing method, in particular to a question routing method based on word vectors. The question routing method based on the word vectors includes the following steps that firstly, user files are established; secondly, data are preprocessed; thirdly, the word vectors are trained; fourthly, document vectors are expressed; fifthly, user authority is worked out; sixthly, user activity is worked out; seventhly, candidate answerers are ranked. The data are trained through word2vec, efficiency is high, the word vectors have the superposition property, and the defect that no co-occurrence word with the similarity of 0 exists among documents is overcome; meanwhile, document subject words are extracted, the document vectors are expressed by the word vectors, the authority, the activity and the similarity among the document vectors are worked out comprehensively, semantic information among the documents is considered, and noise is also reduced. Contrast experiments are carried out between the question routing method and classic TF_IDF and between the question routing method and a classic Language Model, and S@N of the question routing method is higher than those of the other two methods.

Description

technical field [0001] The present invention relates to a problem routing method, more particularly, to a problem routing method based on word vectors. Background technique [0002] Q&A communities in recent years, such as Yahoo! Answers, Baidu Knows, and Stackoverflow have become more and more popular. The public shares knowledge in the community. Every day, a large number of users ask questions. The content of the answers in the community provides users with optional answers. General community Q&A websites will divide the questions according to the question category. When users ask a question, they will select a suitable category, that is, the question label, and wait for other users to answer. The questioner must wait for other users to browse the community and read the question before they can provide the answer, and it is possible that many users can answer the question before they can get the best answer. This process generally takes hours or days. The answer may no ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/24578G06F16/9535G06Q50/01
Inventor 王健董华磊林鸿飞
Owner DALIAN UNIV OF TECH
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