Name
Abstract | ||
|---|---|---|
We introduce a proposal to theoretically characterize Information Retrieval (IR) supporting metadata. The proposed model has
its foundation in a classical approach to IR, namely vector models. These models are simple and implementations are fast,
their term-weighting approach improve retrieval performance, allow partial matching, and support document ranking. The proposed
characterization includes document and query representations, support for typical IR-related activities like stemming, stoplist
application or dictionary transformations, and a framework for similarity calculation and document ranking. The classical
vector model is integrated as a particular case in the new proposal.
|
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/3-540-46043-8_7 | International Conference on Computational Science |
Keywords | Field | DocType |
vector model,term-weighting approach,classical vector model,information retrieval,support document ranking,modeling metadata-enabled information retrieval,proposed characterization,new proposal,document ranking,classical approach | Metadata,Data mining,Ranking,Information retrieval,Computer science,Implementation,Vector space model | Conference |
Volume | ISSN | ISBN |
2329 | 0302-9743 | 3-540-43591-3 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manuel J. Fernández Iglesias | 1 | 28 | 14.58 |
| Judith S. Rodríguez | 2 | 46 | 9.18 |
| Luis E. Anido-Rifón | 3 | 181 | 42.15 |
| Juan M. Santos | 4 | 80 | 15.49 |
| manuel caeiro | 5 | 75 | 18.32 |
| Martín Llamas Nistal | 6 | 108 | 35.60 |