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They first apply a maximal frequent pattern mining algorithm to extract the patterns from retrieval results of the query. The authors then propose to model a subtopic with either a single pattern or a group of similar patterns. A profile-based clustering method is adapted to group similar patterns based on their context information. The search results are then diversified using the extracted subtopics. Experimental results show that the proposed pattern-based methods are effective to diversify the search results.<\/p>","DOI":"10.4018\/jswis.2012100103","type":"journal-article","created":{"date-parts":[[2013,3,21]],"date-time":"2013-03-21T22:37:13Z","timestamp":1363905433000},"page":"37-56","source":"Crossref","is-referenced-by-count":4,"title":["Diversifying Search Results through Pattern-Based Subtopic Modeling"],"prefix":"10.4018","volume":"8","author":[{"given":"Wei","family":"Zheng","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, USA"}]},{"given":"Hui","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, USA"}]},{"given":"Hong","family":"Cheng","sequence":"additional","affiliation":[{"name":"Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong"}]},{"given":"Xuanhui","family":"Wang","sequence":"additional","affiliation":[{"name":"Facebook, Menlo Park, CA, USA"}]}],"member":"2432","reference":[{"key":"jswis.2012100103-0","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Gollapudi, S., Halverson, A., & Ieong, S. 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