Name
Abstract | ||
|---|---|---|
During Phase I of the TIPSTER program, HNC developed a unique approach to machine learning of similarity of meaning. This approach, embodied in a system called "MatchPlus", exploits this learned similarity of meaning for concept-based text retrieval, routing and visualization of textual information. MatchPlus uses an information representation scheme called "context vectors" to encode similarity of usage. Key attributes of the context vector approach are as follows:• Words, documents, and queries are represented by context vectors. A context vector encodes a representation of the meaning of a word, query, or document as a high-dimension, fixed length, real vector. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.3115/1119149.1119160 | TIPSTER |
Keywords | Field | DocType |
final report,real vector,context vector,key attribute,unique approach,fixed length,tipster program,textual information,tipster phase,context vector approach,concept-based text retrieval,information representation scheme | Semantic similarity,ENCODE,Information retrieval,Visualization,Textual information,Computer science,Exploit,Embodied cognition,Artificial intelligence,Natural language processing,Text retrieval,Information representation | Conference |
Citations | PageRank | References |
1 | 2.54 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bill Caid | 1 | 1 | 2.54 |
| Stephen Gallant | 2 | 32 | 6.02 |
| Joel Carleton | 3 | 18 | 11.60 |
| David Sudbeck | 4 | 18 | 10.93 |