Name
Abstract | ||
|---|---|---|
Open Mind Common Sense is a knowledge acquisition system designed to acquire commonsense knowledge from the general public over the web. We describe and evaluate our first fielded system, which enabled the construction of a 450,000 assertion commonsense knowledge base. We then discuss how our second-generation system addresses weaknesses discovered in the first. The new system acquires facts, descriptions, and stories by allowing participants to construct and fill in natural language templates. It employs word-sense disambiguation and methods of clarifying entered knowledge, analogical inference to provide feedback, and allows participants to validate knowledge and in turn each other. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/3-540-36124-3_77 | CoopIS/DOA/ODBASE |
Keywords | Field | DocType |
general public,analogical inference,knowledge acquisition,assertion commonsense knowledge base,commonsense knowledge,second-generation system addresses weakness,open mind common sense,natural language template,new system,word-sense disambiguation,knowledge acquisition system,natural language,knowledge base | Commonsense knowledge,Data mining,Common sense,Computer science,Assertion,Knowledge-based systems,Knowledge management,Human–computer interaction,Natural language,Knowledge base,Knowledge acquisition,Open Knowledge Base Connectivity | Conference |
Volume | ISSN | ISBN |
2519 | 0302-9743 | 3-540-00106-9 |
Citations | PageRank | References |
170 | 13.58 | 15 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Push Singh | 1 | 358 | 31.13 |
| Thomas Lin | 2 | 367 | 24.03 |
| Erik T. Mueller | 3 | 373 | 48.75 |
| Grace Lim | 4 | 170 | 13.58 |
| Travell Perkins | 5 | 170 | 13.58 |
| Wan Li Zhu | 6 | 170 | 13.58 |