BIRCH: an efficient data clustering method for very large databases
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Improved histograms for selectivity estimation of range predicates
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Inductive learning algorithms and representations for text categorization
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Readings in information visualization: using vision to think
Readings in information visualization: using vision to think
BOAT—optimistic decision tree construction
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CACTUS—clustering categorical data using summaries
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
STHoles: a multidimensional workload-aware histogram
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Top-k selection queries over relational databases: Mapping strategies and performance evaluation
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OSQR: overlapping clustering of query results
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Personalization and visualization on handheld devices
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Ordering the attributes of query results
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Query result ranking over e-commerce web databases
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Supporting ranking and clustering as generalized order-by and group-by
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Addressing diverse user preferences in SQL-query-result navigation
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Supporting OLAP operations over imperfectly integrated taxonomies
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Minimum-effort driven dynamic faceted search in structured databases
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A Context-Sensitive Approach for Web Database Query Results Ranking
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Answering approximate queries over autonomous web databases
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Hierarchical result views for keyword queries over relational databases
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Combining keyword search and forms for ad hoc querying of databases
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Exploring biomedical databases with BioNav
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DataLens: making a good first impression
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On embedding task memory in services composition frameworks
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FACeTOR: cost-driven exploration of faceted query results
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Accessing semi-structured databases: a survey
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On the selection of tags for tag clouds
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Scalable clustering of news search results
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Query expansion based on clustered results
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Categorical data skyline using classification tree
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Differentiating search results on structured data
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Automated superSQL query formulation based on statistical characteristics of data
DEXA'05 Proceedings of the 16th international conference on Database and Expert Systems Applications
TreeCluster: clustering results of keyword search over databases
WAIM '06 Proceedings of the 7th international conference on Advances in Web-Age Information Management
Querying e-catalogs using content summaries
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part I
Categorize by: deductive aggregation of semantic web query results
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Semantic Query Expansion using Cluster Based Domain Ontologies
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Exploratory ad-hoc queries could return too many answers - a phenomenon commonly referred to as "information overload". In this paper, we propose to automatically categorize the results of SQL queries to address this problem. We dynamically generate a labeled, hierarchical category structure - users can determine whether a category is relevant or not by examining simply its label; she can then explore just the relevant categories and ignore the remaining ones, thereby reducing information overload. We first develop analytical models to estimate information overload faced by a user for a given exploration. Based on those models, we formulate the categorization problem as a cost optimization problem and develop heuristic algorithms to compute the min-cost categorization.