Social information retrieval for online community question answering services

• Main Authors: Jun, Choi Lee, Yu-N, Cheah, Wai, Shiang Cheah
• Format: Conference or Workshop Item
• Language: English
• Published: 2016
• Subjects: T Technology (General)
• Online Access: http://repo.uum.edu.my/20061/1/KMICe2016%20145%20149.pdf; http://repo.uum.edu.my/20061/; http://www.kmice.cms.net.my/kmice2016/files/KMICe2016_eproceeding.pdf

Online Community Question Answering Services is a platform that allows users to seek for answers anytime and anywhere.The services cover a large collection of unstructured knowledge and become a knowledge repository for problem solving.The answers in the services are generated by other public user.This environment creates a large collection of unstructured knowledge, which can be use as knowledge source for other intelligent processes.From the review, it is a challenge to access accurate information from the Online Community Question Answering services.This study propose a social information retrieval method to access the knowledge from the services.The proposed method query and retrieve information the online services through query expansion.Then, the retrieved information is filtered through a similarity analysis between a question with a query statement and semantic relatedness between answers and the query statement.The accuracy of the proposed approach is evaluated through human evaluation.