Contextualized Text OLAP Based on Information Retrieval
Current data warehousing and On-Line Analytical Processing (OLAP) systems are not yet particularly appropriate for textual data analysis. It is therefore crucial to develop a new data model and an OLAP system to provide the necessary analyses for textual data. To achieve this objective, this paper p...
Ausführliche Beschreibung
Autor*in: |
Oukid, Lamia [verfasserIn] Benblidia, Nadjia [verfasserIn] Bentayeb, Fadila [verfasserIn] Asfari, Ounas [verfasserIn] Boussaid, Omar [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2015 |
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Umfang: |
1 Online-Ressource |
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Übergeordnetes Werk: |
Enthalten in: International journal of data warehousing and mining - Hershey, Pa : IGI Global, 2005, 11(2015), 2, Seite 1-21 |
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Übergeordnetes Werk: |
volume:11 ; year:2015 ; number:2 ; pages:1-21 |
Links: |
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DOI / URN: |
10.4018/ijdwm.2015040101 |
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Katalog-ID: |
NLEJ251798305 |
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10.4018/ijdwm.2015040101 doi (DE-627)NLEJ251798305 (VZGNL)10.4018/ijdwm.2015040101 DE-627 ger DE-627 rakwb eng Oukid, Lamia verfasserin aut Contextualized Text OLAP Based on Information Retrieval 2015 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Current data warehousing and On-Line Analytical Processing (OLAP) systems are not yet particularly appropriate for textual data analysis. It is therefore crucial to develop a new data model and an OLAP system to provide the necessary analyses for textual data. To achieve this objective, this paper proposes a new approach based on information retrieval (IR) techniques. Moreover, several contextual factors may significantly affect the information relevant to a decision-maker. Thus, the paper proposes to consider contextual factors in an OLAP system to provide relevant results. It provides a generalized approach for Text OLAP analysis which consists of two parts: The first one is a context-based text cube model, denoted CXT-Cube. It is characterized by several contextual dimensions. Hence, during the OLAP analysis process, CXT-Cube exploits the contextual information in order to better consider the semantics of textual data. Besides, the work associates to CXT-Cube a new text analysis measure based on an OLAP-adapted vector space model and a relevance propagation technique. The second part is an OLAP aggregation operator called ORank (OLAP-Rank) which allows to aggregate textual data in an OLAP environment while considering relevant contextual factors. To consider the user context, this paper proposes a query expansion method based on a decision-maker profile. Based on IR metrics, it evaluates the proposed aggregation operator in different cases using several data analysis queries. The evaluation shows that the precision of the system is significantly better than that of a Text OLAP system based on classical IR. This is due to the consideration of the contextual factors Aggregation Operator Context Information Retrieval Query Expansion Text Cube Text OLAP Benblidia, Nadjia verfasserin aut Bentayeb, Fadila verfasserin aut Asfari, Ounas verfasserin aut Boussaid, Omar verfasserin aut Enthalten in International journal of data warehousing and mining Hershey, Pa : IGI Global, 2005 11(2015), 2, Seite 1-21 Online-Ressource (DE-627)NLEJ244418896 (DE-600)2399996-2 1548-3932 nnns volume:11 year:2015 number:2 pages:1-21 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijdwm.2015040101 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijdwm.2015040101&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 11 2015 2 1-21 |
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Contextualized Text OLAP Based on Information Retrieval |
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Current data warehousing and On-Line Analytical Processing (OLAP) systems are not yet particularly appropriate for textual data analysis. It is therefore crucial to develop a new data model and an OLAP system to provide the necessary analyses for textual data. To achieve this objective, this paper proposes a new approach based on information retrieval (IR) techniques. Moreover, several contextual factors may significantly affect the information relevant to a decision-maker. Thus, the paper proposes to consider contextual factors in an OLAP system to provide relevant results. It provides a generalized approach for Text OLAP analysis which consists of two parts: The first one is a context-based text cube model, denoted CXT-Cube. It is characterized by several contextual dimensions. Hence, during the OLAP analysis process, CXT-Cube exploits the contextual information in order to better consider the semantics of textual data. Besides, the work associates to CXT-Cube a new text analysis measure based on an OLAP-adapted vector space model and a relevance propagation technique. The second part is an OLAP aggregation operator called ORank (OLAP-Rank) which allows to aggregate textual data in an OLAP environment while considering relevant contextual factors. To consider the user context, this paper proposes a query expansion method based on a decision-maker profile. Based on IR metrics, it evaluates the proposed aggregation operator in different cases using several data analysis queries. The evaluation shows that the precision of the system is significantly better than that of a Text OLAP system based on classical IR. This is due to the consideration of the contextual factors |
abstractGer |
Current data warehousing and On-Line Analytical Processing (OLAP) systems are not yet particularly appropriate for textual data analysis. It is therefore crucial to develop a new data model and an OLAP system to provide the necessary analyses for textual data. To achieve this objective, this paper proposes a new approach based on information retrieval (IR) techniques. Moreover, several contextual factors may significantly affect the information relevant to a decision-maker. Thus, the paper proposes to consider contextual factors in an OLAP system to provide relevant results. It provides a generalized approach for Text OLAP analysis which consists of two parts: The first one is a context-based text cube model, denoted CXT-Cube. It is characterized by several contextual dimensions. Hence, during the OLAP analysis process, CXT-Cube exploits the contextual information in order to better consider the semantics of textual data. Besides, the work associates to CXT-Cube a new text analysis measure based on an OLAP-adapted vector space model and a relevance propagation technique. The second part is an OLAP aggregation operator called ORank (OLAP-Rank) which allows to aggregate textual data in an OLAP environment while considering relevant contextual factors. To consider the user context, this paper proposes a query expansion method based on a decision-maker profile. Based on IR metrics, it evaluates the proposed aggregation operator in different cases using several data analysis queries. The evaluation shows that the precision of the system is significantly better than that of a Text OLAP system based on classical IR. This is due to the consideration of the contextual factors |
abstract_unstemmed |
Current data warehousing and On-Line Analytical Processing (OLAP) systems are not yet particularly appropriate for textual data analysis. It is therefore crucial to develop a new data model and an OLAP system to provide the necessary analyses for textual data. To achieve this objective, this paper proposes a new approach based on information retrieval (IR) techniques. Moreover, several contextual factors may significantly affect the information relevant to a decision-maker. Thus, the paper proposes to consider contextual factors in an OLAP system to provide relevant results. It provides a generalized approach for Text OLAP analysis which consists of two parts: The first one is a context-based text cube model, denoted CXT-Cube. It is characterized by several contextual dimensions. Hence, during the OLAP analysis process, CXT-Cube exploits the contextual information in order to better consider the semantics of textual data. Besides, the work associates to CXT-Cube a new text analysis measure based on an OLAP-adapted vector space model and a relevance propagation technique. The second part is an OLAP aggregation operator called ORank (OLAP-Rank) which allows to aggregate textual data in an OLAP environment while considering relevant contextual factors. To consider the user context, this paper proposes a query expansion method based on a decision-maker profile. Based on IR metrics, it evaluates the proposed aggregation operator in different cases using several data analysis queries. The evaluation shows that the precision of the system is significantly better than that of a Text OLAP system based on classical IR. This is due to the consideration of the contextual factors |
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title_short |
Contextualized Text OLAP Based on Information Retrieval |
url |
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijdwm.2015040101 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijdwm.2015040101&buylink=true |
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author2 |
Benblidia, Nadjia Bentayeb, Fadila Asfari, Ounas Boussaid, Omar |
author2Str |
Benblidia, Nadjia Bentayeb, Fadila Asfari, Ounas Boussaid, Omar |
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NLEJ244418896 |
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doi_str |
10.4018/ijdwm.2015040101 |
up_date |
2024-07-06T11:38:13.360Z |
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score |
7.400358 |