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June 29, 2009, at 05:01 PM by 81.80.50.25 -
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    * Define the new challenges for structured data mining with ML techniques.
    * Build Interlinked document collections, define evaluation methodologies and develop software which will be used for the evaluation of classification of documents in a graph.
    * Compare existing methods on different datasets.
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  • Define the new challenges for structured data mining with ML techniques.
  • Build Interlinked document collections, define evaluation methodologies and develop software which will be used for the evaluation of classification of documents in a graph.
  • Compare existing methods on different datasets.
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Dealing with XML document collections is a particularly challenging task for ML and IR. XML documents are deŻned by their logical structure and their content (hence the name semi-structured data). Moreover, in a large majority of cases (Web collections for example), XML documents collections are also structured by links between documents (hyperlinks for example). These links can be of different types and correspond to different information: for example, one collection can provide hierarchical links, hyperlinks, citations, etc. Earlier models developed in the Żeld of XML categorization/clustering simultaneously use the con- tent information and the internal structure of XML documents for a list of models) but they rarely use the external structure of the collection i.e the links between documents. We have focus here on the problem of classication of XML documents organized

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Dealing with XML document collections is a particularly challenging task for ML and IR. XML documents are deŻned by their logical structure and their content (hence the name semi-structured data). Moreover, in a large majority of cases (Web collections for example), XML documents collections are also structured by links between documents (hyperlinks for example). These links can be of different types and correspond to different nformation: for example, one collection can provide hierarchical links, hyperlinks, citations, etc.

Earlier models developed in the field of XML categorization/clustering simultaneously use the content information and the internal structure of XML documents for a list of models) but they rarely use the external structure of the collection i.e the links between documents.

We focus here on the problem of classication of XML documents organized

June 29, 2009, at 05:00 PM by 81.80.50.25 -
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Tasks

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Description

The goal of the challenge is to identify the different Machine Learning (ML) methods proposed so far for structured data, to assess the potential of these methods for dealing with generic ML tasks in the structured domain, to identify the new challenges of this emerging field and to foster research in this domain. Structured data appears in many different domains. We will focus here on Graph document collections and we are organizing this challenge in cooperation with the INEX initiative. This challenge aims at gathering ML, Information Retrieval (IR) and Data Mining researchers in order to:

    * Define the new challenges for structured data mining with ML techniques.
    * Build Interlinked document collections, define evaluation methodologies and develop software which will be used for the evaluation of classification of documents in a graph.
    * Compare existing methods on different datasets.

Results of the track will be presented at the INEX workshop.

Task : Graph (Semi-)Supervised Classification

Dealing with XML document collections is a particularly challenging task for ML and IR. XML documents are deŻned by their logical structure and their content (hence the name semi-structured data). Moreover, in a large majority of cases (Web collections for example), XML documents collections are also structured by links between documents (hyperlinks for example). These links can be of different types and correspond to different information: for example, one collection can provide hierarchical links, hyperlinks, citations, etc. Earlier models developed in the Żeld of XML categorization/clustering simultaneously use the con- tent information and the internal structure of XML documents for a list of models) but they rarely use the external structure of the collection i.e the links between documents. We have focus here on the problem of classication of XML documents organized in graph. More precisely, the participants of the task have to classify the document of a partially labelled graph.

June 29, 2009, at 04:51 PM by 81.80.50.25 -
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XML Mining Track - Supervised Classification of Documents organized in a graph - INEX 2009

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  • June 25 : 2009 Collection available (see Collection)
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  • June 29 : 2009 Collection finally available
June 22, 2009, at 02:48 PM by 132.227.204.229 -
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  • June 22 : 2009 Collection available (see Collection)
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  • June 25 : 2009 Collection available (see Collection)
June 16, 2009, at 10:38 AM by 132.227.204.229 -
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  • June 15 : 2009 Collection available (see Collection)
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  • June 22 : 2009 Collection available (see Collection)
May 28, 2009, at 04:41 PM by 88.185.138.92 -
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XML Mining Track - INEX 2008

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XML Mining Track - Supervised Classification of Documents organized in a graph - INEX 2009

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  • April 8 : New website
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  • Due to technical problems, the collection will be available on july the 4th
  • July 7 : 2008 Collection avaiable (see Collection)
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  • June 15 : 2009 Collection available (see Collection)
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The challenge focuses mainly on two tasks about XML document :

  • Categorization
  • Clustering

Overview

The objective of the challenge is to develop machine learning methods for structured data mining and to evaluate these methods for XML document mining tasks. The challenge is focused on classification and clustering for XML documents. Datasets coming from different XML collections and covering a variety of classification and clustering situations will be provided to the participants.

One goal of this track is to build a reference categorization/clustering corpora of XML documents. The organizers are opened to any suggestion concerning the construction of such corpora.

How to particpate ?

In order to participate, you have to register to the XML Mining track on the INEX 2008 website . You will then be registered on a XML Mining mailing list and you will regularly receive news about the track.

July 07, 2008, at 06:20 PM by 82.247.114.231 -
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  • Due to technical problems, the collection will be available on july the 4th
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  • Due to technical problems, the collection will be available on july the 4th
  • July 7 : 2008 Collection avaiable (see Collection)
July 01, 2008, at 07:36 PM by 193.253.243.14 -
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  • Due to technical problems, the collection will be available on july the 4th
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  • Due to technical problems, the collection will be available on july the 4th
July 01, 2008, at 07:36 PM by 193.253.243.14 -
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  • Due to technical problems, the collection will be available on july the 4th
May 28, 2008, at 06:18 PM by 132.227.204.229 -
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  • May 28: Additionnal information (timeline and tasks description)
April 08, 2008, at 11:13 AM by 132.227.204.229 -
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Coucou

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XML Mining Track - INEX 2008

News

  • April 8 : New website

Tasks

The challenge focuses mainly on two tasks about XML document :

  • Categorization
  • Clustering

Overview

The objective of the challenge is to develop machine learning methods for structured data mining and to evaluate these methods for XML document mining tasks. The challenge is focused on classification and clustering for XML documents. Datasets coming from different XML collections and covering a variety of classification and clustering situations will be provided to the participants.

One goal of this track is to build a reference categorization/clustering corpora of XML documents. The organizers are opened to any suggestion concerning the construction of such corpora.

How to particpate ?

In order to participate, you have to register to the XML Mining track on the INEX 2008 website . You will then be registered on a XML Mining mailing list and you will regularly receive news about the track.

If any problem, please contact Ludovic DENOYER : ludovic dot denoyer at lip6 dot fr.

April 08, 2008, at 11:04 AM by 132.227.204.229 -
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