Embedding knowledge in Web documents
WWW '99 Proceedings of the eighth international conference on World Wide Web
Information retrieval on the semantic web
Proceedings of the eleventh international conference on Information and knowledge management
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Integrating Structured Data and Text: A Multi-Dimensional Approach
ITCC '00 Proceedings of the The International Conference on Information Technology: Coding and Computing (ITCC'00)
Ontology-based Integration of OLAP and Information Retrieval
DEXA '03 Proceedings of the 14th International Workshop on Database and Expert Systems Applications
Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
Text Cube: Computing IR Measures for Multidimensional Text Database Analysis
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
OLAP-based query recommendation
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A methodology and tool for conceptual designing a data warehouse from ontology-based sources
DOLAP '10 Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
ONTOCUBE: efficient ontology extraction using OLAP cubes
Proceedings of the 20th ACM international conference on Information and knowledge management
Ontologies are us: a unified model of social networks and semantics
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Proceedings of the 21st ACM international conference on Information and knowledge management
Meta-stars: multidimensional modeling for social business intelligence
Proceedings of the sixteenth international workshop on Data warehousing and OLAP
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Text columns commonly extend core information stored as atomic values in a relational database, creating a need to explore and summarize text data. OLAP cubes can precisely accomplish such tasks. However, cubes have been overlooked as a mechanism for capturing not only text summarizations, but also for representing and exploring the hierarchical structure of an ontology. In this paper, we focus on exploiting cubes to compute multidimensional aggregations on classified documents stored in a DBMS (keyword frequency, document count, document class frequency and so on). We propose CUBO (CUBed Ontologies), a novel algorithm, which efficiently manipulates the hierarchy behind an ontology. Our algorithm is optimized to compute desired summarizations without having to search all possible dimension combinations, exploiting the sparseness of the document classification frequency matrix. Experiments on large text data sets show CUBO can explore faster more dimension combinations than a standard cube algorithm, especially when the cube has a large number of dimensions. CUBO was developed entirely inside a DBMS, using SQL queries and extensibility features.