A fuzzy grassroots ontology for improving social semantic web search

Portmann, Edy (2011). A fuzzy grassroots ontology for improving social semantic web search. In: Proceedings of 6th International Summer School on Aggregation Operators (pp. 189-194). Lulu

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The web is continuously evolving into a collection of many data, which results in the interest to collect and merge these data in a meaningful way. Based on that web data, this paper describes the building of an ontology resting on fuzzy clustering techniques. Through continual harvesting folksonomies by web agents, an entire automatic fuzzy grassroots ontology is built. This self-updating ontology can then be used for several practical applications in fields such as web structuring, web searching and web knowledge visualization.A potential application for online reputation analysis, added value and possible future studies are discussed in the conclusion.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems > Information Management
03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems

UniBE Contributor:

Portmann, Edy

Subjects:

600 Technology > 650 Management & public relations

ISBN:

978-1-4477-7019-0

Publisher:

Lulu

Projects:

[388] Knowledge Aggregation, Representation and Reasoning

Language:

English

Submitter:

Sara D'Onofrio

Date Deposited:

10 Apr 2014 11:30

Last Modified:

02 Nov 2015 09:43

Uncontrolled Keywords:

Folksonomy, Fuzzy Data Clustering, Knowledge Visualization, Ontology, Search Engine, Semantic Web, Social Semantic Web, Social Web.

BORIS DOI:

10.7892/boris.45582

URI:

https://boris.unibe.ch/id/eprint/45582

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