Ontology for Knowledge Discovery in Semantic Web Mining - Mahak - Bog

The development of the World Wide Web has huge and increasing amount of data and information. This huge data provided by the web has become an important information resource for all internet users. Furthermore, the low cost of web data makes it more attractive to researchers. Users can retrieve web data by browsing and keyword searching. Still, it may have lots of limitations to these techniques. Normally, several web links are getting users while they browsing for one data so it is hard for researchers to retrieve data efficiently. Mostly, pages in web contain both hyperlinks and text documents to other documents. Furthermore, mailing lists, newsgroups, and forums are considered as another form of data sources. Thus, web mining can also support web mining design and implementation but this becomes provocation for people with extracting web information. Web mining is able to support the web information sources based on user needs, including knowing availability, importance and relevance of web systems; it should be able to select extracted data, because both related and not related information are present in Web sites; it should be easy to collect data and then analyze and help to build models and produce validity.

Internet users have improved significantly over the last decade and endure to growth. Through the user numbers, data available in web, persistent to increase exponentially. E- commerce is one of the application areas related to information mining. Fast growth of internet users has improved e-business applications. Many attempts are made on "breaking the syntax barrier" in web and many of them depend on text corpora of the semantic information used completely by statistical techniques.

Ontology framework plays a key role in semantic web along with the artificial intelligence purposes and these contain Resource Description Framework (RDF) and XML. Ontology has developed into a necessary model tool for applying various intelligent systems which represent domain knowledge, which is easily understandable by both humans and machines. Ontologies play important role to make interoperability efficient and smooth, among heterogeneous systems. Ontology basically provides the link between particular domain concepts. The aim of ontology is to attain good knowledge about that system that can be circulated between people and application framework and intend to gain knowledge of domain and their role involves the semantics design exactly in a generic method, offering the agreement premise inside the area. In general, Ontology covers four key components namely: instances, concepts, axioms and relations. Concept was key element and is a basic domain with collection of group or objects or abstract set and normally means a common knowledge shared among group of members.