we present ONTOLOGY BASED WEB CRAWLER,

With the advent of the World Wide Web, people nowadays not only have access to more worldwide
news information than ever before, but they can also obtain it in a more timely manner. Online
newspapers present breaking news on their websites in real time, and users can receive automatic
notifications of them via RSS feeds.
RSS is a free way to promote a site without the need to advertise or create complicated content sharing
partnerships, and an easy mechanism for the users to be informed of the latest news or web contents.
However, the increasing volume, growth rate, ubiquity of access, and the unstructured nature of the
contents challenge the limits of human processing capabilities. It is in such scenario where
recommender systems can do their most, by scanning the space of choices, and predicting the potential
usefulness of news for each particular user, without explicitly specifying needs or querying for items
whose existence is unknown beforehand.
However, general common problems have not been fully solved yet, and further investigation is needed.
For example, typical approaches are domain dependant. Their models are generated from information
gathered within a specific domain, and cannot be easily extended and/or incorporated to other systems.
Moreover, the need for further flexibility in the form of query-driven or group-oriented
recommendations, and the consideration of contextual features during the recommendation processes
are also unfulfilled requirements in most systems.
In this work, we present ONTOLOGY BASED WEB CRAWLER, a system that makes use of Semantic
Web technologies to recommend news. The system supports different recommendation models for
single and multiple users which address several recommender systems limitations. The exploitation of
meta-information in the form of ontologies that describe items and user profiles in a general, portable
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way, along with the capability of inferring knowledge from the semantic relations defined in the
ontologies, are the key aspects of the system.
Section 2 presents the architecture, functionalities and recommendation models of ONTOLOGY
BASED WEB CRAWLER, referencing previous works that have more detailed explanations and
evaluations, and section 3 emphasises the benefits of our proposal.