Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Lexical ambiguity and information retrieval
ACM Transactions on Information Systems (TOIS)
Using WordNet to disambiguate word senses for text retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation and information retrieval
SIGIR '94 Proceedings of the 17th 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
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
Word sense disambiguation in information retrieval revisited
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
A divide-and-merge methodology for clustering
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A Concept-Driven Algorithm for Clustering Search Results
IEEE Intelligent Systems
A graph model for unsupervised lexical acquisition
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Improving web search results using affinity graph
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Improving Web Clustering by Cluster Selection
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
A Method of Web Search Result Clustering Based on Rough Sets
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Word sense disambiguation in queries
Proceedings of the 14th ACM international conference on Information and knowledge management
A large scale study of wireless search behavior: Google mobile search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Less is more: probabilistic models for retrieving fewer relevant documents
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Graph Visualization Techniques for Web Clustering Engines
IEEE Transactions on Visualization and Computer Graphics
The opposite of smoothing: a language model approach to ranking query-specific document clusters
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A cluster-based resampling method for pseudo-relevance feedback
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Ambiguous queries: test collections need more sense
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A rank-aggregation approach to searching for optimal query-specific clusters
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A comparative evaluation of different link types on enhancing document clustering
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
An Unsupervised Approach to Cluster Web Search Results Based on Word Sense Communities
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
A survey of Web clustering engines
ACM Computing Surveys (CSUR)
Web Search Clustering and Labeling with Hidden Topics
ACM Transactions on Asian Language Information Processing (TALIP)
Refined experts: improving classification in large taxonomies
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Dynamicity vs. effectiveness: studying online clustering for scatter/gather
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Enhancing cluster labeling using wikipedia
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Full-Subtopic Retrieval with Keyphrase-Based Search Results Clustering
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Evaluating and optimizing the parameters of an unsupervised graph-based WSD algorithm
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
Inducing word senses to improve web search result clustering
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
A quick tour of word sense disambiguation, induction and related approaches
SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science
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We present a novel method for clustering Web search results based on Word Sense Induction. First, we acquire the meanings of a query by means of a graph-based clustering algorithm that calculates the maximum spanning tree of the co-occurrence graph of the query. Then we cluster the search results based on their semantic similarity to the induced word senses. We show that our approach improves classical search result clustering methods in terms of both clustering quality and degree of diversification.