{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/44150"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/44150","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Utilizing forum meta-information to improve relevance in forum discovery","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Yeh, Han-Wen"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Zhai, ChengXiang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-05-24T21:52:42Z","date_published":"2013-05-24T21:52:42Z","updated_at":"2026-07-22T22:25:33Z","subjects":["forum search","information retrieval"],"languages":["en"],"rights":["Copyright 2013 Han-Wen Yeh"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/44150","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhai, ChengXiang"]},{"key":"dc:creator","label":"Author","values":["Yeh, Han-Wen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2013-05-24T21:52:42Z","2013-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["forum search","information retrieval"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2013 Han-Wen Yeh"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/44150"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-23T21:08:30Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Yeh_Han-Wen.pdf: 681209 bytes, checksum: 5f3312c1c20c26a3f1274cda2e38f8c7 (MD5)","Made available in DSpace on 2013-05-24T21:52:42Z (GMT). No. of bitstreams: 2 Han-Wen_Yeh.pdf: 681209 bytes, checksum: 5f3312c1c20c26a3f1274cda2e38f8c7 (MD5) license.txt: 4057 bytes, checksum: bce9ee0001fd8e023cfd0a155d9d5c49 (MD5)"]},{"key":"dc:title","label":"Title","values":["Utilizing forum meta-information to improve relevance in forum discovery"]}]}],"canonical_facts":{"dc:contributor":["Zhai, ChengXiang"],"dc:creator":["Yeh, Han-Wen"],"dc:date":["2013-05-24T21:52:42Z","2013-05"],"dc:description":["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.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-23T21:08:30Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Yeh_Han-Wen.pdf: 681209 bytes, checksum: 5f3312c1c20c26a3f1274cda2e38f8c7 (MD5)","Made available in DSpace on 2013-05-24T21:52:42Z (GMT). No. of bitstreams: 2 Han-Wen_Yeh.pdf: 681209 bytes, checksum: 5f3312c1c20c26a3f1274cda2e38f8c7 (MD5) license.txt: 4057 bytes, checksum: bce9ee0001fd8e023cfd0a155d9d5c49 (MD5)"],"dc:identifier":["http://hdl.handle.net/2142/44150"],"dc:language":["en"],"dc:rights":["Copyright 2013 Han-Wen Yeh"],"dc:subject":["forum search","information retrieval"],"dc:title":["Utilizing forum meta-information to improve relevance in forum discovery"],"dc:type":["text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:33Z"}