Southampton and The Open University. Preface(7)

Advanced Knowledge Technologies is recognised as a leading research programme conducted at some of the foremost informatics departments in Britain. It is also a training ground for a new generation of researchers. To highlight the work of these students, a

2. Motivation

The process of mining for semantic data involves several processes namely, crawling the web for semantic web documents, extracting and analysing information from this data, clustering the semantic data for later retrieval purposes, and its scope for the future which involves enhancing the capability of information extraction systems by adding reporting functionality which involves tracking changes in information over time. We try to give an insight into these aspects in the following section.

Semantic Web Documents, which are stored in the form of RDF, OWL, FOAF, RSS, etc at various The task of mining the Web for Semantic Data essentially consists of crawling the web and finding locations. This leads us to the idea of designing a robust RDF crawler. essentially identical to crawling the HTML content web - it's simply a case of choosing one or more Crawling the semantic web is starting points, downloading a resource and following the pointers in it to further resources. (Biddulph, 2003). The difference between gathering HTML and RDF data is that RDF has a well defined mechanism for merging multiple RDF models. We many combine any number of RDF models to produce a single unified model. Hence instead of performing the task of building a database of keywords and links to locations where HTML representations related to those keywords can be found, the RDF crawler can create a combined model for all the semantic data found. The major advantage of this union of models is that the model now becomes a rich resource of information. That is one document contains the combined information of the all the separate documents which contain fragments of data. Some of the design considerations while implementing such a crawler could be Resource Pooling to avoid overload on the server, Gathering URLs from certain targets in RDF representation E.G the and mapping of the ontology to the data. After download of Semantic Data is complete, we now have <rdf:seealso> triples that contain additional information about a document to move to the second part of the process that is extraction and analysis of information from the data, one of the most efficient ways to extract information from RDF graphs is by using RDQL (RDF data query language). RDQL is now supported by many popular RDF API frameworks such as Jena1

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