Name
Abstract | ||
|---|---|---|
Query rewriting algorithms can be used as a form of query expansion, by combining the user's original query with automatically generated rewrites. Rewriting algorithms bring linguistic datasets to bear without the need for iterative relevance feedback, but most studies of rewriting have used proprietary datasets such as large-scale search logs. By contrast this paper uses readily available data, particularly ClueWeb09 link text with over 1.2 billion anchor phrases, to generate rewrites. To avoid overfitting, our initial analysis is performed using Million Query Track queries, leading us to identify three algorithms which perform well. We then test the algorithms on Web and newswire data. Results show good properties in terms of robustness and early precision. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2433396.2433440 | WSDM |
Keywords | Field | DocType |
available data,billion anchor phrase,anchor data,original query,newswire data,clueweb09 link text,million query track query,linguistic datasets,query expansion,early precision,robust query,proprietary datasets,anchor text | Query optimization,Data mining,Web search query,Query language,Relevance feedback,Query expansion,Information retrieval,Computer science,Web query classification,Anchor text,Rewriting | Conference |
Citations | PageRank | References |
5 | 0.41 | 27 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nick Craswell | 1 | 3942 | 279.60 |
| Bodo Billerbeck | 2 | 272 | 14.24 |
| Dennis Fetterly | 3 | 1367 | 107.30 |
| Marc A. Najork | 4 | 2538 | 278.16 |