Team AxIS

Members
Overall Objectives
Application Domains
Software
New Results
Contracts and Grants with Industry
Other Grants and Activities
Dissemination
Bibliography

Section: Overall Objectives

Keywords : information system, user-centered design, evaluation, knowledge discovery, KDD, data mining, usage mining, document mining, knowledge management, ontology management, information retrieval, recommender system, Web mining, semantic Data mining, Semantic Web, personnalisation data stream mining, transportation system, World Wide Web, Security, intrusion detection, anomaly detection.

Overall Objectives

AxIS is carrying out research in the area of Information and Knowledge Systems (ISs) with a special interest in evolving large ISs such as Web based-information Systems. Our ultimate goal is to improve the overall quality of ISs, to support designers during the design process and to ensure ease of use to end users. We are convinced that to reach this goal, according to the constant evolution of actual and future ISs, it is necessary to anticipate the usage and its analysis and also the maintenance very early in the design process.

To achieve such a research, we have set up in July 2003 a multidisciplinary team that involves people from different computer sciences domains (Artificial Intelligence, Data Mining & Analysis, Software Engineering, Document Management from 2004) and at the end of 2005 from Ergonomics (Human Sciences), all of them focusing on information systems. Our goal is of course to improve efficiency of machine learning and data mining methods but also to improve the quality of results. The originality of AxIS project-team is to adopt a cognitive and inter-disciplinary approach for the whole KDD process and for each step (preprocessing, data mining, interpretation).

To address this challenge, relying on our scientific foundations (see our 2007 activity report,section 3 or http://ralyx.inria.fr/2007/Raweb/axis/uid0.html ), we had a first 4 years steps dedicated to the design of methodological and technical building blocks for IS mining (usage, content and structure). Our next steps started this year identified three applicative objectives:

Our researches are organised in three topics according to the genericity level of results:

  1. Mining complex data and IS data (mainly mining data streams and evolutive data)

  2. Mining social networks, support tools for Information retrieval (recommender systems), personalization

  3. SHS-STIC approach in evaluating the usage of Web-based information systems and applications.


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