Name
Abstract | ||
|---|---|---|
The increasing problem of information overload can be reduced by the improvement of information access tasks like Information Retrieval. Relevance Feedback plays a key role in this task, and is typically based only on the information extracted from documents judged by the user for a given query. We propose to make use of a thesaurus to complement this information to improve RF. This must be done by means of a Word Sense Disambiguation process that correctly identifies the suitable information from the thesaurus WORDNET. The results of our experiments show that the utilisation of a thesaurus requires Word Sense Disambiguation, and that with this process, Relevance Feedback is substantially improved. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1007/3-540-45323-7_16 | TSD |
Keywords | Field | DocType |
information retrieval | Information overload,SemEval,Relevance feedback,Information retrieval,Query expansion,Computer science,Information access,Relevance (information retrieval),Natural language processing,Artificial intelligence,WordNet,Concept search | Conference |
ISBN | Citations | PageRank |
3-540-41042-2 | 1 | 0.35 |
References | Authors | |
9 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luis Alfonso Ureña López | 1 | 257 | 53.93 |
| José María Gómez Hidalgo | 2 | 225 | 24.70 |
| Manuel De Buenaga Rodríguez | 3 | 67 | 16.59 |