CXT-cube: contextual text cube model and aggregation operator for text OLAP
| Autor: | Omar Boussaid, Fadila Bentayeb, Lamia Oukid, Ounas Asfari, Nadjia Benblidia |
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| Přispěvatelé: | Bentayeb, Fadila |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Information retrieval
Computer science Online analytical processing InformationSystems_DATABASEMANAGEMENT Context (language use) Cube (algebra) computer.software_genre Data warehouse Operator (computer programming) Factor (programming language) Contextual information [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB] Data mining computer ComputingMilieux_MISCELLANEOUS computer.programming_language |
| Zdroj: | DOLAP |
| Popis: | Traditional data warehousing technologies and On-Line Analytical Processing (OLAP) are unable to analyze textual data. Moreover, as OLAP queries of a decision-maker are generally related to a context, contextual information must be taken into account during the exploitation of data warehouses. Thus, we propose a contextual text cube model denoted CXT-Cube which considers several contextual factors during the OLAP analysis in order to better consider the contextual information associated with textual data. CXT-Cube is characterized by several contextual dimensions, each one related to a contextual factor. In addition, we extend our aggregation OLAP operator for textual data ORank (OLAP-Rank) to consider all the contextual factors defined in our CXT-Cube model. To validate our model, we perform an experimental study and the preliminary results show the importance of our approach for integrating textual data into a data warehouse and improving the decision-making. |
| Databáze: | OpenAIRE |
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