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
Projections for efficient document clustering
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Exploiting clustering and phrases for context-based 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 anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Grouper: a dynamic clustering interface to Web search results
WWW '99 Proceedings of the eighth international conference on World Wide Web
ACM Computing Surveys (CSUR)
Latent semantic indexing: a probabilistic analysis
Journal of Computer and System Sciences - Special issue on the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems
WWW '03 Proceedings of the 12th international conference on World Wide Web
IMPLICITLY RESTARTED ARNOLDI/LANCZOS METHODS FOR LARGE SCALE EIGENVALUE CALCULATIONS
IMPLICITLY RESTARTED ARNOLDI/LANCZOS METHODS FOR LARGE SCALE EIGENVALUE CALCULATIONS
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 personalized search engine based on web-snippet hierarchical clustering
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
The infocious web search engine: improving web searching through linguistic analysis
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
A Concept-Driven Algorithm for Clustering Search Results
IEEE Intelligent Systems
Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters
IEEE Transactions on Computers
Designing evolving user profile in e-CRM with dynamic clustering of Web documents
Data & Knowledge Engineering
Query result clustering for object-level search
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
A survey of evolutionary algorithms for clustering
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Noodles: a clustering engine for the web
ICWE'07 Proceedings of the 7th international conference on Web engineering
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Journal of Intelligent Information Systems
Dynamic refinement of search engines results utilizing the user intervention
Journal of Systems and Software
Result disambiguation in web people search
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Optimised K-means for web search
International Journal of Advanced Intelligence Paradigms
Towards discovering ontological models from big RDF data
ER'12 Proceedings of the 2012 international conference on Advances in Conceptual Modeling
Towards discovering conceptual models behind web sites
ER'12 Proceedings of the 31st international conference on Conceptual Modeling
Journal of Biomedical Informatics
Hybrid entity clustering using crowds and data
The VLDB Journal — The International Journal on Very Large Data Bases
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We develop a new algorithm for clustering search results. Differently from many other clustering systems that have been recently proposed as a post-processing step for Web search engines, our system is not based on phrase analysis inside snippets, but instead uses latent semantic indexing on the whole document content. A main contribution of the paper is a novel strategy - called dynamic SVD clustering - to discover the optimal number of singular values to be used for clustering purposes. Moreover, the algorithm is such that the SVD computation step has in practice good performance, which makes it feasible to perform clustering when term vectors are available. We show that the algorithm has very good classification performance, and that it can be effectively used to cluster results of a search engine to make them easier to browse by users. The algorithm has being integrated into the Noodles search engine, a tool for searching and clustering Web and desktop documents.