LarKC-WS 2007

From semanticweb.org

The main open question that will be discussed at the workshop is: Why isn't reasoning scaling for the Web and how can this fixed? Some of the limiting assumptions underlying current reasoning languages for the Web are:

• sets of axioms and facts are restricted in size
• the axioms and facts are static and known in advance
• the inference process must be sound and complete

Each of these assumptions (and most likely others) needs to be revisited and adopted to the reality as it is provided by the Web.

Contributions form many very different scientific fields will be needed to establish the paradigmatic shift that is necessary to obtain this goal. The workshop aims to attract participants from scientific fields not typically seen at Semantic Web events:

• Economics can tell us about cost-benefit trade-off models, sunk-cost theory and the role of negotiation in obtaining near-optimal results under bounded resources
• Cognitive Science can tell us about strategies of human memory and human reasoning which is so succesful in reaching good enough conclusion in limited time-spans, using methods such as priming, attention scoping, recency-based self-optimising memory, etc.
• Computational Learning Theory has contributions to make with their notions of Probably Approximately Correct (PAC) computing, and strategies for abstraction and compression of information.
• Combinatorial Search has made recent breakthroughs in handling massive search-spaces with heuristics based on Monte Carlo simulations.

Communities closer to home also that also have important contributions to make are Information Retrieval and Very Large Databases.