Abstract:
Finding information on World Wide Web or web is the most popular and interactive
searching medium to retrieve information these days. Web is easy to access and there
are lots ofinformation available on the web. With growth of amount ofthe content or
information, web has become increasingly difficult to find the data on the web
quickly. The easiest way of searching on the web is search engines. Search engines
returns thousands of results for small search keyword. It is difficult to filter out the
required information from these search results.
Web content mining is one of the most popular and effective way of filtering data.
Users will be able to retrieve their required information through this kind of filtering
mechanism. Web content mining is specific to particular area. The filtered data can be
saved locally in order to user later. This information can be stored in a database
system to use as required. Integrating relational database with ontology is an active
research area these days. Ontology will be a core part of the next generation web.
Current web (web 2.0) mostly relies on keyword based search. The performance of
the system depends on the matching the keyword with available data.
This study has focused on web content mining technologies and integrating ontology
with relational database system to manipulate filtered data. The domain ofthe study is
movies and related information. Movie related information is filtered using a web
crawler and this information is saved in a database system after further cleaning. Web
crawler is configured to get the movie related information from the web. Ontology is
designed based on the movie related information. After designing the database and the
ontology, these two layers should be mapped. This part is done using a data wrapper.
This wrapper links ontology instances with database system.
After mapping is done there should be a proper way to retrieve the data from
ontology. SPARQL is used to query the ontology and SPARQL will get the data from
the database through ontology mapping. Finally user interface is designed to interact
with the user. User can search through two interfaces called general search advanced
search. Using general search user will be able to search a keyword and through
advanced search user can search using multiple parameters. Users will be able to
search based on their actual searching criteria’s rather that searching a keyword.
