Name
Abstract | ||
|---|---|---|
Information Retrieval is a complex task, which deals with both the subjectivity related to the user's needs and the uncertainty and vagueness that characterize the retrieval process. For this reason, deciding to which extent a document is relevant to a user's needs is not easy, and it strongly depends on several dimensions such as topicality, novelty, user's context, and so on. One of the most straightforward ways to interpret this activity is as a Multi-Criteria Decision Making (MCDM) problem, in which the choice of appropriate aggregation operators can play an important role in various tasks related to, or characterizing the IR process. This article aims to provide a presentation of the main approaches that in the literature have made use of aggregation operators in Information Retrieval. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.fss.2016.12.018 | Fuzzy Sets and Systems |
Keywords | Field | DocType |
Aggregation operators,Information Retrieval,Indexing,Query languages,Multidimensional relevance assessment,Metasearch,OWA operators,Copulas,Choquet integrals | Cognitive models of information retrieval,Vagueness,Query language,Multiple-criteria decision analysis,Human–computer information retrieval,Information retrieval,Search engine indexing,Artificial intelligence,Relevance (information retrieval),Novelty,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
324 | C | 0165-0114 |
Citations | PageRank | References |
8 | 0.50 | 33 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefania Marrara | 1 | 171 | 21.05 |
| Gabriella Pasi | 2 | 1673 | 169.31 |
| Marco Viviani | 3 | 143 | 18.95 |