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Title:Utilizing forum meta-information to improve relevance in forum discovery
Author(s):Yeh, Han-Wen
Advisor(s):Zhai, ChengXiang
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):forum search
information retrieval
Abstract:The World Wide Web is abundant with discussion forums about all sorts of topics, and it is becoming increasingly difficult for people to find quality forums about a certain topic in which to join. While many modern search engines crawl through discussion forums and return threads in various forums based on each thread’s relevance to query terms, there are not a lot of search engines that can tell a user the best forum to join to discuss about a topic of interest. We have observed that users looking for forums to join may be more interested in joining one with a high posting activity from a diverse community. However, current search engines do not fully utilize information from forums to provide the best search results to these users. We propose a specialized retrieval system that looks for discussion forums and returns a list of forums based on a user’s search query. When ranking search results, this system not only takes relevance into account, but also the posting activity and number of members from each forum. We evaluate our system over a manually-selected set of 150 forums that cover ten general topics, and show that our system retrieves forums that are relevant to the search query and are more appealing to users than forums retrieved from conventional search engines.
Issue Date:2013-05-24
URI:http://hdl.handle.net/2142/44150
Rights Information:Copyright 2013 Han-Wen Yeh
Date Available in IDEALS:2013-05-24
Date Deposited:2013-05


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