Name
Abstract | ||
|---|---|---|
An unsolved problem in logic-based information retrieval is how to obtain automatically logical representations for documents and queries. This problem limits the impact of logical models for information retrieval because their full expressive power cannot be harnessed. In this paper we propose a method for producing logical document representations which goes further than other simplistic "bag-of-words" approaches. The suggested procedure adopts popular information retrieval heuristics, such as document length corrections and global term distribution. This work includes a report of several experiments applying partial document representations in the context of a propositional model of information retrieval. The benefits of this expressive framework, powered by the new logical indexing approach, become apparent in the evaluation. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.is.2005.11.001 | SPIRE |
Keywords | Field | DocType |
process capability,indexation | Divergence-from-randomness model,Data mining,Cognitive models of information retrieval,Human–computer information retrieval,Information retrieval,Document clustering,Computer science,Relevance (information retrieval),Vector space model,Document retrieval,Database,Visual Word | Journal |
Volume | Issue | ISSN |
31 | 7 | Information Systems |
Citations | PageRank | References |
0 | 0.34 | 18 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David E. Losada | 1 | 326 | 40.63 |
| Alvaro Barreiro | 2 | 226 | 22.42 |
| DE Losada | 3 | 0 | 0.34 |