IDUF: An active learning based scenario for relevance feedback query expansion
| Autor: | Seyed Mohammad Reza Moosavi, Seyed Mohammad Bidoki |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Web search query
Information retrieval Computer science InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL computer.software_genre Query language Query optimization Ranking (information retrieval) Query expansion Web query classification Sargable Data mining computer RDF query language computer.programming_language |
| Zdroj: | CAMP |
| DOI: | 10.1109/infrkm.2012.6204982 |
| Popis: | In usual Information Retrieval (IR) systems, the user query is represented in the form of a keyword set. Information resources are retrieved according to their similarities to this query. Consequently if query is not declared with appropriate terms, retrieved results would not be satisfactory. Therefore query refinement procedures are incorporated to improve the efficiency of the IR systems. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|