International audienceThis report explains the objectives, datasets and evaluation criteria of both the clustering and classification tasks set in the INEX 2009 XML Mining track. The report also describes the approaches and results obtained by the different participants

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This paper describes the approach taken to the XML Mining track at INEX 2008 by a group at the Queensland University of Technology. We introduce the K-tree clustering algorithm in an Information Retrieval context by adapting it for document clustering. Many large scale problems exist in document clustering. K-tree scales well with large inputs due to its low complexity. It offers promising results both in terms of efficiency and quality. Document classification was completed using Support Vector Machines.Comment: 12 pages, INEX 200

Abstract. This report explains the objectives, datasets and evaluation criteria of both the clustering and classification tasks set in the INEX 2010 XML Mining track. The report also describes the approaches and results obtained by participants.

Article disponible en ligne : http://www.cs.otago.ac.nz/homepages/andrew/papers/2010-4.pdfInternational audienceINEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2009 evaluation campaign, which consisted of a wide range of tracks: Ad hoc, Book, Efficiency, Entity Ranking, Interactive, QA, Link the Wiki, and XML Mining. INEX in running entirely on volunteer effort by the IR research community: anyone with an idea and some time to spend, can have a major impact