Selection method of network answers based on probabilistic latent semantic analysis

Abstract

A selection method of network answers based on probabilistic latent semantic analysis comprises the following steps: a problem set C, constructing a probabilistic latent semantic analysis model by using a user set u and a word set w as variables, and using the probabilistic latent semantic analysis model to dig the latent theme information of each user u; obtaining problems q newly raised in a question-answering community and the words w forming the questions, determining the joint probability of the current problems and candidate answers, and calculating the joint probability of the current questions and the users answering the current problems; linearly weighting the joint probability of the current problems and the candidate answers and the joint probability of the current questions and the users answering the current problems to obtain candidate answer scores, arranging the candidate answer scores in the manner of descending order, and sending the answers to the user raising the problem according to an arranged order. The invention has the advantages of capability of adequately using the abundant user information in the question-answering community, high accuracy and wide applicability.

Description

technical field [0001] The invention relates to an answer selection method for question-and-answer communities on the network, in particular to a network answer selection method based on probabilistic latent semantic analysis. technical background [0002] In recent years, question-answering communities, which aim to enhance user communication, have received increasing attention from researchers. In the past few years, there have been such websites as Sina Aiwen, Baidu Zhizhi, Yahoo! Answers and other question-and-answer communities. Users are free to ask questions, browse questions, and answer questions. However, with the increasing number of users participating in the question-and-answer community, the number of candidate answers increases, resulting in an increasing burden on the questioning users to choose the best answer. Therefore, automatic ranking of candidate answers becomes an urgent need in the question answering community. [0003] Answer selection is a techn...

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Problems solved by technology

[0004] In order to overcome the shortcomings of the prior art that cannot make full use of the rich user information in the question-and-answer community, the accuracy rate is low, and the applicability is small, the present invention provides a method that can make full use of the rich user information in the question-and-answer community, with high accuracy and low applicability. A Wide Web Answer Selection Method Based on Probabilistic Latent Semantic Analysis

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