Title :
An event ontology construction approach to web crime mining
Author :
Li Cunhua ; Hu Yun ; Zhong Zhaoman
Author_Institution :
Sch. of Comput. Eng., Huaihai Inst. of Technol., Lianyungang, China
Abstract :
Along with the rapid popularity of the Internet, crime information on the web is becoming increasingly rampant, and the majority of them are in the form of text. Because a lot of crime information in documents is described through events, event-based semantic technology can be used to study the patterns and trends of web-oriented crimes. In our research project on cyber crime mining, we construct event ontology to extract the attributes and relations in web pages and reconstruct the scenario for crime mining. This article discusses the methods of analyzing and reconstructing the features of Chinese web pages. Event ontology and Support Vector Machine (SVM) classification are used to validate the proposed methods. As an example, a prototype system is implemented for Chinese text classification. The experimental results show that event ontology has many advantages in web crime mining application.
Keywords :
Web sites; computer crime; data mining; ontologies (artificial intelligence); pattern classification; support vector machines; text analysis; Chinese Web page; Chinese text classification; Internet; SVM classification; Web crime mining; Web-oriented crime; attribute extraction; crime information; cyber crime mining; event ontology construction; event-based semantic technology; support vector machine; Accuracy; Internet; Ontologies; Support vector machines; Text categorization; Web pages; Web mining; cyber crime; event; event ontology;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569290