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Textual aggregation approaches in OLAP context: A survey
- Source :
- International Journal of Information Management, International Journal of Information Management, Elsevier, 2017, 37 (6), pp.684-69. ⟨10.1016/j.ijinfomgt.2017.06.005⟩
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- International audience; In the last decade, OnLine Analytical Processing (OLAP) has taken an increasingly important role as a research field. Solutions, techniques and tools have been provided for both databases and data warehouses to focus mainly on numerical data. however these solutions are not suitable for textual data. Therefore recently, there has been a huge need for new tools and approaches that treat and manipulate textual data and aggregate it as well. Textual aggregation techniques emerge as a key tool to perform textual data analysis in OLAP for decision support systems. This paper aims at providing a structured and comprehensive overview of the literature in the field of OLAP Textual Aggregation. We provide a new classification framework in which the existing textual aggregation approaches are grouped into two main classes, namely approaches based on cube structure and approaches based on text mining. We discuss and synthesize also the potential of textual similarity metrics, and we provide a recent classification of them.
- Subjects :
- Structure (mathematical logic)
Decision support system
OLAP
[SHS.STAT]Humanities and Social Sciences/Methods and statistics
Computer Networks and Communications
Computer science
Online analytical processing
Aggregate (data warehouse)
Textual data
Context (language use)
02 engineering and technology
Library and Information Sciences
Data science
Data warehouse
Field (computer science)
Aggregation
020204 information systems
Similarity (psychology)
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Data mining
Information Systems
Subjects
Details
- ISSN :
- 02684012 and 01436236
- Volume :
- 37
- Database :
- OpenAIRE
- Journal :
- International Journal of Information Management
- Accession number :
- edsair.doi.dedup.....bcc11ced445f5428ce0b44cf3391cd83