Intelligent Database Workshop (IDBW'08)
May 20, 2008, York University, Toronto, Canada
Chair: Parke Godfrey, York University
Tentative Schedule
Location: Lecture Hall N106, Seymour Schulich Building (SSB), York University
Description
An intelligent database augments query answering to return the most relevant information possible. It may add information to the answers themselves to help disambiguate, or to address misconceptions of the user. It may order answers by relevance, based on perceived preferences of the user. It may offer a richer query language that allows users to express more easily their queries, new types of queries, and explicitly their preferences.
Work in intelligent databases started in the 1970's, and continues today. The work has involved researchers from both the database and artificial intelligence communities. It has found forums in conferences such as ISMIS that cater to an interdisciplinary audience. From the database perspective, the idea is to improve database systems to make them more flexible and intuitive. From the AI perspective, the idea is to leverage database technology to enable and scale knowledge-base systems.
In the meanwhile, the database and AI landscapes keep evolving rapidly. With the rise of the Web, search has taken center stage again. Data mining has become a key research area and a major industry. Data warehousing and business intelligence, likewise, have become core activities for many organizations. The study of agents looks to how complex knowledge-based tasks can be accomplished by "simpler" active components that self organize and coordinate. The field of service science, management, and engineering (SSME) has arisen as the interdisciplinary endeavor to study, design, and implement services systems. And database technology itself is rapidly evolving to support richer, diverse data models (as XML) and query languages (as XQuery).
Although diverse, these areas share common themes. Database technology is foundational throughout, but only as one piece of the puzzle. They involve complex architectures with advanced algorithms, often AI based, distributed across many components. To simplify this complexity, one looks to integrate better the functionality needed in these applications into the foundational technologies. This leads back to the intelligent database paradigm.
The workshop will be composed of talks by invited speakers over topics discussed above, but with a perspective of intelligent databases, and how the meet of database technology and AI should evolve to address these challenges. Speakers are to be from Ontario industry and academia. The workshop will also have a panel and ample discussion to involve the participants.
