Section: 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 contribute to user-driven open innovation as a way to foster innovation, 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 involve the users in the design process and to empower them, so that they can become co-designers. This is a new way to anticipate the usage and its analysis and also to consider 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 Scientific Foundations), 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 researches are organised to support the disruptive process of continuous innovation.
In this continuous process: design is never ended and relies on very short test-adapt-test cycles users are co-designers: they can contribute to design before/after market launch as ideas providers, as participants in test beds or field experimentations or even as solution providers when they are given the convenient tools.
To support this process, a large collection of tools and methods are needed and numerous efforts have already been engaged at european level to provide infrastructures for experimentations (for instance the Future Internet Research & Experimentation (FIRE ) initiative launched in summer 2008), tools for creativity or sharing (Laboranova , CoSpaces , etc.).
In this context, our team focuses its effort on the technical and methodological environment needed to extract meaning from the huge amount of data issued from large and distributed information system.
Our researches are organised in three research topics:
Topic 1 - Mining complex data and IS data : mainly temporal data, semantic Web mining (ontologies and Web mining) and semantics checking of an evolving IS. Most effort is put into two problems related to mining temporal data: a) analysing the evolution of user behaviours and b) summarizing and mining data streams.
Topic 2 - Mining Web 2.0 and collective usage data : mining social networks, community detection, finding expert, collaborative filtering based recommender systems for information retrieval, social networks based recommender systems, personalization, etc.
Topic 3 - the Focus methodological and technical experimentation platform : methods and tools based on a multidisciplinary approach (SHS and TIC) for the design and the evaluation of innovative services and for user-driven open innovation..