International Conference on Intelligent Systems Design and Applications 2009
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A Business Intelligence process to support Information Retrieval in an Ontology-based Environment
![A Business Intelligence Process to support Information Retrieval in an Ontology-Based Environment Tommaso Federici Tuscia University 01010 Viterbo, Italy [email_address] Filippo Sciarrone, Paolo Starace Open Informatica srl – BI Division Via dei Castelli Romani, 12/A 00040 Pomezia, Italy {f.sciarrone, p.starace}@openinformatica.org](https://image.slidesharecdn.com/isda09v2-12607838831868-phpapp02/85/international-conference-on-intelligent-systems-design-and-applications-2009-1-320.jpg)
![Introduction ,[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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International Conference on Intelligent Systems Design and Applications 2009
- 1. A Business Intelligence Process to support Information Retrieval in an Ontology-Based Environment Tommaso Federici Tuscia University 01010 Viterbo, Italy [email_address] Filippo Sciarrone, Paolo Starace Open Informatica srl – BI Division Via dei Castelli Romani, 12/A 00040 Pomezia, Italy {f.sciarrone, p.starace}@openinformatica.org
- 5. The semantic indexing process unstructured docs ontologies terms set
- 6. The overall system dm1 presentation layer structured data index CUSTOM ETL PROCESS data warehouse and datamarts Addictional integrable data dm3 dm2 semantic dictionary
- 9. Dynamic dimension definition dimension table bridge table fact table Unbalanced ontology tree dynamic computation concept_id description parent 1 one 2 two 1 parent subsidiary distance 1 1 0 1 2 1 concept_id other_dim_id measure 1 … … … … …
- 12. Integration of the indexed data SELECT * FROM index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id; SELECT * FROM ((index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id) JOIN std_dimension_dt ON op_fact_table.column = std_dimension_dt.column); SELECT * FROM ((index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id) JOIN std_dimension_dt ON op_fact_table.column = std_dimension_dt.column) JOIN ontology_dt ON index.concept = ontology_dt.concept; SELECT ontology_dt.ontology_id, std_dimension_dt.std_dimension_id, sum(op_fact_table.measure) FROM ((index JOIN op_fact_table ON index.op_fact_id = op_fact_table.id) JOIN std_dimension_dt ON op_fact_table.column = std_dimension_dt.column) JOIN ontology_dt ON index.concept = ontology_dt.concept GROUP BY std_dimension_dt.std_dimension_id, ontology_dt.ontology_id;
- 17. Thanks to all for your attention Questions?
Notes de l'éditeur
- Today the power of a company depends on how fast it take decisions about its business. Currently BI processes, to support companies business, rely only on traditional keywords searching. We think that is a good thing to extend this way to do with a semantic approach
- Presentation breaks down as follow: Firstly i will introduce the semantic indexing process over this one we have developed our system. Secondly i will illustrate the dynamic dimension definition process, ranging from the working hypotheses, to the treatment of Bridge Tables and the automatic generation of OLAP dimensions. After i will explain the processes lying behind the integration of the indexed data, pointing out the most significant SQL code parts. Last of all I will present a simple case study to summarize all the presented concepts.
- Presentation breaks down as follow: Firstly i will introduce the semantic indexing process over this one we have developed our system. Secondly i will illustrate the dynamic dimension definition process, ranging from the working hypotheses, to the treatment of Bridge Tables and the automatic generation of OLAP dimensions. After i will explain the processes lying behind the integration of the indexed data, pointing out the most significant SQL code parts. Last of all I will present a simple case study to summarize all the presented concepts.
- Presentation breaks down as follow: Firstly i will introduce the semantic indexing process over this one we have developed our system. Secondly i will illustrate the dynamic dimension definition process, ranging from the working hypotheses, to the treatment of Bridge Tables and the automatic generation of OLAP dimensions. After i will explain the processes lying behind the integration of the indexed data, pointing out the most significant SQL code parts. Last of all I will present a simple case study to summarize all the presented concepts.
- Presentation breaks down as follow: Firstly i will introduce the semantic indexing process over this one we have developed our system. Secondly i will illustrate the dynamic dimension definition process, ranging from the working hypotheses, to the treatment of Bridge Tables and the automatic generation of OLAP dimensions. After i will explain the processes lying behind the integration of the indexed data, pointing out the most significant SQL code parts. Last of all I will present a simple case study to summarize all the presented concepts.
- This aspect is now left to the user’s capacity of developing consistent schemas, but it is our intention to introduce a management system based on weighted trees