When crystal balls are not available, one may rely on analysis of historical data to discover predictive patterns. Temporal patterns are of particular interest because of the large number of high-profile applications that include historical time series. The goal of this workshop is to bring together AI researchers who study time-series problems, along with practitioners and researchers from related fields, in order to establish common ground.
Authors are asked to address the following questions, where applicable:
* How have you formulated the time-series analysis problem? Do you build complete classification or regression models? discover temporal patterns? * Are you focusing on the creation of a new algorithm? On the creation of temporally oriented features? * Have you built on related work from AI or from other communities? * Is your method designed for a particular application? Do your results generalize? * Have you evaluated your work?
Those interested in attending without submitting a paper should submit a one-page summary of related work.
Dates Submission deadline: March 11, 1998 Notification date: April 1, 1998 Camera-ready copies due: April 22, 1998 Organizing Committee Andrea Danyluk (workshop chair) Computer Science Department Williams College Williamstown, MA 01267 email@example.com Phone: (413) 597-2178 FAX: (413) 597-4116 Tom Fawcett Bell Atlantic Science and Technology firstname.lastname@example.org Foster Provost Bell Atlantic Science and Technology email@example.comFor additional information, see