Name
Abstract | ||
|---|---|---|
This paper presents an implemented and evaluated methodology for disambiguating terms in search queries and for augmenting queries with expansion terms. By exploiting Wikipedia articles and their reference relations, our method is able to disambiguate terms in particularly short queries with few context words and to effectively expand queries for retrieval of short documents such as tweets. Our strategy can determine when a sequence of words should be treated as a single entity rather than as a sequence of individual entities. This work is part of a larger project to retrieve information graphics in response to user queries. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.datak.2013.07.004 | Data & Knowledge Engineering |
Keywords | Field | DocType |
Disambiguation,Query expansion,Search queries | Graphics,Data mining,Query expansion,Information retrieval,Computer science,Queries per second,Database | Journal |
Volume | Issue | ISSN |
90 | 1 | 0169-023X |
Citations | PageRank | References |
7 | 0.44 | 31 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christopher Boston | 1 | 10 | 0.82 |
| Hui Fang | 2 | 918 | 63.03 |
| Sandra Carberry | 3 | 1005 | 122.43 |
| Hao Wu | 4 | 37 | 4.58 |
| Xitong Liu | 5 | 89 | 7.81 |