{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/26413"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/26413","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"CASM: searching context-aware sequential patterns iteratively","abstract":"Many applications are interested in mining context-aware sequential patterns such as opinions, common navigation patterns, and product recommendations. However, traditional sequential pattern mining algorithms are not effective to mine such patterns. We thus study the problem of searching context-aware patterns on the fly. As a solution, we presented a variable-order random walk as the ranking model and developed two efficient algorithms GraphCAP and R3CAP. To show the effectiveness and efficiency of our solution, we conducted extensive experiments on real dataset. Lastly, we applied our solution to support opinion search, a novel application that significantly differs from traditional opinion mining and retrieval.","abstract_html":"Many applications are interested in mining context-aware sequential patterns such as opinions, common navigation patterns, and product recommendations. However, traditional sequential pattern mining algorithms are not effective to mine such patterns. We thus study the problem of searching context-aware patterns on the fly. As a solution, we presented a variable-order random walk as the ranking model and developed two efficient algorithms GraphCAP and R3CAP. To show the effectiveness and efficiency of our solution, we conducted extensive experiments on real dataset. Lastly, we applied our solution to support opinion search, a novel application that significantly differs from traditional opinion mining and retrieval.","abstract_has_math":false,"creators":["Zhong, Hengzhi"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Chang, Kevin C-C."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-08-26T15:34:57Z","date_published":"2011-08-26T15:34:57Z","updated_at":"2026-07-22T22:25:27Z","subjects":["Sequential pattern mining","opinion search"],"languages":["en"],"rights":["Copyright 2011 Hengzhi Zhong"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/26413","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Chang, Kevin C-C."]},{"key":"dc:creator","label":"Author","values":["Zhong, Hengzhi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-08-26T15:34:57Z","2013-08-27T10:00:28Z","2011-08"]},{"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":["Sequential pattern mining","opinion search"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2011 Hengzhi Zhong"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/26413"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Many applications are interested in mining context-aware sequential patterns such as opinions, common navigation patterns, and product recommendations. 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