Name
Abstract | ||
|---|---|---|
An important question in IRSs is how to facilitate the IRS-user interaction, even more when the complexity of the fuzzy query language makes difficult to formulate user queries. The use of linguistic variables to represent the input and output information in the retrieval process of IRSs significantly improves the IRS-user interaction. In the activity of an IRS, there are aspects of different nature to be assessed, e.g., the relevance of documents, the importance of query terms, etc. Therefore, these aspects should be assessed with different uncertainty degrees, i.e., using several label sets with different granularity of uncertainty. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1016/j.ijar.2003.07.009 | International Journal of Approximate Reasoning |
Keywords | Field | DocType |
Information retrieval,Linguistic modelling,Multi-granular linguistic information | Rule-based machine translation,Deep linguistic processing,Ordinal number,Computer science,Fuzzy logic,Input/output,Natural language processing,Artificial intelligence,Granularity,Fuzzy query,Linguistics,Semantics | Journal |
Volume | Issue | ISSN |
34 | 2 | 0888-613X |
Citations | PageRank | References |
71 | 3.07 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enrique Herrera-Viedma | 1 | 13105 | 642.24 |
| O. Cordón | 2 | 1380 | 66.74 |
| M. Luque | 3 | 71 | 3.07 |
| Antonio Gabriel López-herrera | 4 | 423 | 18.65 |
| A.M. Muñoz | 5 | 71 | 3.07 |