Workshop on
Applying case-based reasoning to time series prediction

Workshop objectives

Time series prediction is an important application field of artificial intelligence (A.I.) techniques. A variety of real life applications require predicting the evolution of times series. Application covers various fields such as financial markets, medical diagnosis, meteorological forecasting, forest fire forecasting, recommender systems and web navigation advisors. Different A.I. techniques have been applied to predicting the evolution of time series. Examples of such techniques are artificial neural networks, fuzzy logic, evolutionary algorithms and soft computing (the integration of the above-cited techniques). Recently, a number of researchers from the Case-based reasoning (CBR) community have addressed the problem of applying the CBR problem solving methodology for predicting sequence or time series evolutions. The different CBR systems that have tackled this problem each focus on a particular issue.

This workshop intends to bring together researches and system developers to discuss and share their ideas about how to adapt the CBR methodology for the specific task of time series prediction. The workshop is expected to produce a first state of the art about using CBR for time series treatment. Topics relevant to the workshop include but are not restricted to:

• Comparing CBR with other A.I techniques. In which fields the use of CBR methodology is likely to enhance the results of other A.I or statistical techniques? Could we define benchmarks and specific evaluation criteria for evaluating CBR based time series prediction?
• Case edition and representation. How to extract cases from raw sequences? Does a case represent a whole sequence, or a part of sequence? Which representation scheme to use in which application: interval representation or point representation?
• Similarity measures. How to efficiently take into consideration the sequential nature of cases when computing similarities?
• CBR cycle adaptation. How to exploit the sequential nature of cases in order to enhance the different CBR phases including maintenance. The fact that the target case is also extracted from a sequence should allow to reuse reasoning results obtained for past target cases extracted from the same sequence. What techniques and heuristics could be applied to achieve this?
• Hybrid systems. What other techniques could be used in order to enhance CBR prediction systems (artificial neural networks, fuzzy logic, etc.)? What type of hybrid systems is more suitable for which CBR phase?

Paper submission

Participation in the workshop will be by invitation only. People interested in participating in the workshop should submit either a full paper (10 pages) or a position paper (2 pages). submissions should be formatted according to Springer LNCS format, which is the format required for the final camera ready copy. Author's instructions along with LaTeX and Word macro files are available at http://www.springer.de/comp/lncs/authors.html. Submissions as well as the names of potential participants must be emailed to Rushed.Kanawati@lipn.univ-paris13.frby 21 April 2003. Accepted papers will be included in the workshop notes and will be available on the workshop web site. In order to have a highly interactive workshop, participation will be limited to 25 people.

Workshop organisation

The workshop organisers will be charged to produce a pre-workshop report that sums up the different accepted papers. The pre-workshop report will be available to all participants three weeks before the workshop day. At most two different relevant topics will be selected from the set of accepted contributions. These issues will be advertised before the workshop. Each participant will be asked to give her/his positions on each issue.

The workshop will be organised into three sessions: the first session is dedicated for presenting the pre-workshop report. Both left sessions are dedicated to discuss selected discussion topics. Considered issues will depend on the topics addressed by the different accepted contributions. A post workshop report will sum up the different contributions during the workshop.

Important dates

Organisation committee

Program committee