Organisations now frequently rely on virtual collaboration through the use of computer technology. After a sequence of meetings, participants may only need to refer to the most important points rather than the whole meeting proceedings. This paper addresses the need for automated meeting summarisation in virtual meeting systems. An extraction approach to summarisation is adopted and a new algorithm is proposed by extending the TextRank algorithm to include constructs representing the structure of the meeting. This helps extract the most relevant sentences from the meeting transcript. The proposed method was evaluated in the context of student-tutor meetings. Results show that harnessing and utilising the structure of a virtual meeting can lead to more relevant automated summaries.

Hidden Web databases maintain a collection of specialised documents, which are dynamically generated in response to users' queries. The categorisation of such databases into a set of predefined categories has been widely employed to assist users in their information searches. In this paper we present a technique that automatically categorises a document database through its content summary and concepts described by their specificity and coverage. Experimental results show that our approach categorises databases with a larger number of relevant categories.

The larger amount of information on the Web is stored in document databases and is not indexed by general-purpose search engines (i.e., Google and Yahoo). Such information is \ndynamically generated through querying databases — which are \nreferred to as Hidden Web databases. Documents returned in \nresponse to a user query are typically presented using templategenerated Web pages. This paper proposes a novel approach that identifies Web page templates by analysing the textual contents and the adjacent tag structures of a document in order to extract query-related data. Preliminary results demonstrate that our approach effectively detects templates and retrieves data with high recall and precision.