Name
Abstract | ||
|---|---|---|
This paper presents a new method for computing a thesaurus from a text corpus. Each word is represented as a vector in a multi-dimensional space that captures cooccurrence information. Words are defined to be similar if they have similar cooccurrence patterns. Two different methods for using these thesaurus vectors in information retrieval are shown to significantly improve performance over the Tipster reference corpus as compared to a term vector space baseline. |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1016/S0306-4573(96)00068-4 | Information Processing and Management: an International Journal |
Keywords | Field | DocType |
cooccurrence-based thesaurus,information retrieval | Information retrieval,Computer science,Text corpus,Artificial intelligence,Natural language processing | Conference |
Volume | Issue | ISSN |
33 | 3 | Information Processing and Management |
Citations | PageRank | References |
11 | 1.61 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hinrich Schütze | 1 | 2113 | 362.21 |
| Jan O. Pedersen | 2 | 6301 | 1177.07 |