PAT-tree-based keyword extraction for Chinese information retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
Novelty and redundancy detection in adaptive filtering
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Beyond independent relevance: methods and evaluation metrics for subtopic retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Learning to cluster web search results
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A data mining approach to modeling relationships among categories in image collection
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Improving novelty detection for general topics using sentence level information patterns
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
An information-pattern-based approach to novelty detection
Information Processing and Management: an International Journal
Learning to rank relational objects and its application to web search
Proceedings of the 17th international conference on World Wide Web
Conceptual Subtopic Identification in the Medical Domain
IBERAMIA '08 Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence
Evaluating subtopic retrieval methods: Clustering versus diversification of search results
Information Processing and Management: an International Journal
Topic based photo set retrieval using user annotated tags
Multimedia Tools and Applications
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This paper presents a novel formulation and approach to the minimal document set retrieval problem. Minimal Document Set Retrieval (MDSR) is a promising information retrieval task in which each query topic is assumed to have different subtopics; the task is to retrieve and rank relevant document sets with maximum coverage but minimum redundancy of subtopics in each set. For this task, we propose three document set retrieval and ranking algorithms: Novelty Based method, Cluster Based method and Subtopic Extraction Based method. In order to evaluate the system performance, we design a new evaluation framework for document set ranking which evaluates both relevance between set and query topic, and redundancy within each set. Finally, we compare the performance of the three algorithms using the TREC interactive track dataset. Experimental results show the effectiveness of our algorithms.