An overview of data warehousing and OLAP technology
ACM SIGMOD Record
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
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
The integration of business intelligence and knowledge management
IBM Systems Journal
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Multidimensional content eXploration
Proceedings of the VLDB Endowment
Text Cube: Computing IR Measures for Multidimensional Text Database Analysis
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Topic modeling for OLAP on multidimensional text databases: topic cube and its applications
Statistical Analysis and Data Mining - Best of SDM'09
Promotion analysis in multi-dimensional space
Proceedings of the VLDB Endowment
Effective data warehouse for information delivery: a literature survey and classification
International Journal of Networking and Virtual Organisations
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With the amount of textual information massively growing in various kinds of business systems and Internet, there are increasingly demands for analyzing both structured data and unstructured text data. Online Analysis Processing (OLAP) is effective for analyzing and mining structured data. However, while handling with unstructured data, it is powerless. After working on several information integration and data analysis applications, we have realized the defect of OLAP on text data analysis and use technical ways to handle this issue. In this paper, we propose a semi-supervised algorithm to extract dimensions and their members from textual information for the purpose of analyzing a huge set of textual data. We use straightforward measures to express analysis results. Experiment result shows that the extracting algorithm is valid and our approach has a high scalability and flexibility.