Algorithms for clustering data
Algorithms for clustering data
Scatter/gather browsing communicates the topic structure of a very large text collection
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Reexamining the cluster hypothesis: scatter/gather on retrieval results
SIGIR '96 Proceedings of the 19th 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
Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
Information Retrieval
The effectiveness of query-specific hierarchic clustering in information retrieval
Information Processing and Management: an International Journal
Constrained K-means Clustering with Background Knowledge
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
ACM SIGIR Forum
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Proceedings of the 13th international conference on World Wide Web
Learning to cluster web search results
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A probabilistic framework for semi-supervised clustering
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Findex: search result categories help users when document ranking fails
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A Concept-Driven Algorithm for Clustering Search Results
IEEE Intelligent Systems
Document clustering with prior knowledge
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
The complex dynamics of collaborative tagging
Proceedings of the 16th international conference on World Wide Web
Learn from web search logs to organize search results
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Personalized interactive faceted search
Proceedings of the 17th international conference on World Wide Web
Exploring folksonomy for personalized search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
Cluster Analysis
A survey of Web clustering engines
ACM Computing Surveys (CSUR)
Query result clustering for object-level search
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Interactive clustering of text collections according to a user-specified criterion
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Rants: a framework for rank editing and sharing in web search
Proceedings of the 19th international conference on World wide web
iCollaborate: harvesting value from enterprise web usage
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Increasing stability of result organization for session search
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
InfoLand: information lay-of-land for session search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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How to organize and present search results plays a critical role in the utility of search engines. Due to the unprecedented scale of the Web and diversity of search results, the common strategy of ranked lists has become increasingly inadequate, and clustering has been considered as a promising alternative. Clustering divides a long list of disparate search results into a few topic-coherent clusters, allowing the user to quickly locate relevant results by topic navigation. While many clustering algorithms have been proposed that innovate on the automatic clustering procedure, we introduce ClusteringWiki, the first prototype and framework for personalized clustering that allows direct user editing of the clustering results. Through a Wiki interface, the user can edit and annotate the membership, structure and labels of clusters for a personalized presentation. In addition, the edits and annotations can be shared among users as a mass-collaborative way of improving search result organization and search engine utility.