A survey of visual analytics for knowledge discovery and content analysis

2012 ◽  
Author(s):  
Mohammad S. Habibi ◽  
Amir Shirkhodaie
Keyword(s):  
Content Analysis ◽  
Knowledge Discovery ◽  
Visual Analytics

Web Usage Mining for Ontology Management

2010 ◽  
pp. 418-447
Author(s):  
Brigitte Trousse ◽  
Marie-Aude Aufaure ◽  
Bénédicte Le Grand ◽  
Yves Lechevallier ◽  
Florent Masseglia
Keyword(s):  
Content Analysis ◽  
Knowledge Discovery ◽  
Web Site ◽  
Web Usage Mining ◽  
Sequential Patterns ◽  
Web Based ◽  
Web Logs ◽  
Usage Analysis ◽  
Original Approach ◽  
Ontology Management

This chapter proposes an original approach for ontology management in the context of Web-based information systems. Our approach relies on the usage analysis of the chosen Web site, in addition to the existing approaches based onWeb pages content analysis. Our methodology is based on knowledge discovery techniques mainly from HTTP Web logs and aims to confronting the discovered knowledge in terms of usage with the existing ontology in order to propose new relations between concepts. We illustrate our approach on a Web site provided by local French tourism authorities (related to Metz city) with the use of clustering and sequential patterns discovery methods. One major contribution of this chapter is, thus, the application of usage analysis to support ontology evolution and/or Web site reorganization.

Web Usage Mining for Ontology Management

2011 ◽  
pp. 37-64 ◽  
Author(s):  
Brigitte Trousse ◽  
Marie-Aude Aufaure ◽  
Bénédicte Le Grand ◽  
Yves Lechevallier ◽  
Florent Masseglia
Keyword(s):  
Content Analysis ◽  
Knowledge Discovery ◽  
Web Site ◽  
Sequential Patterns ◽  
Web Pages ◽  
Web Based ◽  
Web Logs ◽  
Usage Analysis ◽  
Original Approach ◽  
Ontology Management

This chapter proposes an original approach for ontology management in the context of Web-based information systems. Our approach relies on the usage analysis of the chosen Web site, in complement of the existing approaches based on content analysis of Web pages. Our methodology is based on the knowledge discovery techniques mainly from HTTP Web logs and aims at confronting the discovered knowledge in terms of usage with the existing ontology in order to propose new relations between concepts. We illustrate our approach on a Web site provided by French local tourism authorities (related to Metz city) with the use of clustering and sequential patterns discovery methods. One major contribution of this chapter is thus the application of usage analysis to support ontology evolution and/or web site reorganization.

Interactive visual knowledge discovery from data-based temporal decision support system

2015 ◽  
Vol 15 (1) ◽  
pp. 31-50 ◽  
Author(s):  
Hela Ltifi ◽  
Emna Ben Mohamed ◽  
Mounir ben Ayed
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Discovery ◽  
Support System ◽  
Visual Analytics ◽  
Medical Knowledge ◽  
Visual Knowledge ◽  
Design Proposal ◽  
Representation Techniques

The article aims to present a generic interactive visual analytics solution that provides temporal decision support using knowledge discovery from data modules together with interactive visual representations. It bases its design decisions on classification of visual representation techniques according to the criteria of temporal data type, periodicity, and dimensionality. The design proposal is applied to an existing medical knowledge discovery from data–based decision support system aiming at assisting physicians in the fight against nosocomial infections in the intensive care units. Our solution is fully implemented and evaluated.

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