Name
Abstract | ||
|---|---|---|
Encoding knowledge is time consuming and expensive. A possible solution to reduce the cost of developing a new knowledge base (KB) is to reuse existing knowledge. Previous work addressing this problem has focused on standards for representing, exchanging, and accessing knowledge (Genesereth and Fikes 1992), (Chaudhri et al. 1998), and on creating large repositories of knowledge (Lenat and Guha 1990). Results on the level of reuse achievable have been reported (Cohen et al. 1999). In this paper, we focus on the process of reuse and report a case study on constructing a KB by reusing existing knowledge. The reuse process involved the following steps: translation, comprehension, slicing, reformulation, and merging. We discuss technical problems encountered at each of these steps and explain how we solved them. face/expect in <InternationalActionType>?''. An example instantiation is, ` ` What risks can Iran expect in attacking targets in Saudi Arabia?''. The KB development included several test cycles with the test phase based on questions derived from the question grammar, but not previously seen by the system developers. A major test cycle was conducted at the end of the year with several small-scale tests in between. The results reported here are based on the work conducted over a period of two years. Teams led by Teknowledge and SAIC developed the systems for answering the questions. SRI was a part of the SAIC team, and this paper concerns primarily the work conducted at SRI. The KB was developed using the KIF syntax |
Year | Venue | Keywords |
|---|---|---|
2000 | AAAI/IAAI | knowledge base |
Field | DocType | ISBN |
Software engineering,Reuse,Computer science,Slicing,Artificial intelligence,Knowledge base,Merge (version control),Machine learning,Comprehension,Encoding (memory) | Conference | 0-262-51112-6 |
Citations | PageRank | References |
7 | 1.65 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vinay K. Chaudhri | 1 | 587 | 246.49 |
| Mark E. Stickel | 2 | 133 | 15.73 |
| Jérôme Thoméré | 3 | 78 | 8.43 |
| Richard J. Waldinger | 4 | 573 | 693.15 |