Name
Abstract | ||
|---|---|---|
Information Retrieval in technical domains like physics is characterised by long and precise queries, whose meaning is strongly influenced by term context and domain. We treat this as a disambiguation problem, and present initial findings of a retrieval model that posits a higher probability of relevance for documents matching disambiguated query terms. Preliminary evaluation on a real-life physics test collection shows promising performance improvement. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2009916.2010069 | SIGIR |
Keywords | Field | DocType |
promising performance improvement,higher probability,preliminary evaluation,disambiguation problem,physics retrieval,disambiguated query term,information retrieval,sense discrimination,real-life physics test collection,precise query,retrieval model,present initial finding | Data mining,Cognitive models of information retrieval,Human–computer information retrieval,Information retrieval,Query expansion,Computer science,Relevance (information retrieval),Vector space model,Term Discrimination,Performance improvement | Conference |
Citations | PageRank | References |
2 | 0.40 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christina Lioma | 1 | 391 | 39.58 |
| Alok Kothari | 2 | 23 | 1.95 |
| Hinrich Schuetze | 3 | 33 | 2.73 |