Trend Ontology for Knowledge-Based Trend Mining in Textual Information

Author

Streibel, Olga ; Mochol, Malgorzata

Author_Institution

Inst. for Comput. Sci., Free Univ. Berlin, Berlin, Germany

fYear

2010

fDate

12-14 April 2010

Firstpage

1285

Lastpage

1288

Abstract

Providing ontologies for the automatic trend detection enhance the quality of trend predictions. However, in the case of dynamic and fuzzy expert knowledge like the knowledge used in trend detection, it is difficult to formalize knowledge unambiguously and in a static way. In this paper we report on our experiences in modeling and formalizing trend ontology for automatic knowledge-based trend detection by the example of market research, i.e. we describe the knowledge-based trend mining approach and requirements for trend ontology, discuss obstacles in modeling trend knowledge and outline three lightweight trend ontologies modeled.

Keywords

data mining; ontologies (artificial intelligence); text analysis; dynamic expert knowledge; fuzzy expert knowledge; knowledge-based trend mining; textual information; trend ontology; Computer science; Data mining; Information analysis; Information retrieval; Internet; Market research; Ontologies; Semantic Web; Text analysis; Text mining; information retrieval; knowledge modeling; ontology engineering; trend mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology: New Generations (ITNG), 2010 Seventh International Conference on

Conference_Location

Las Vegas, NV

Print_ISBN

978-1-4244-6270-4

Type

conf

DOI

10.1109/ITNG.2010.232

Filename

5501567