Name
Abstract | ||
|---|---|---|
Web search engines typically index and retrieve at the page level. In this study, we investigate a dynamic pruning strategy that allows the query processor to first determine the most promising websites and then proceed with the similarity computations for those pages only within these sites. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1390334.1390543 | SIGIR |
Keywords | Field | DocType |
similarity computation,site-based dynamic pruning,page level,dynamic pruning strategy,web search engine,query processing,promising web,query processor,performance,inverted index,search engine | Query optimization,Data mining,Web search query,Query language,Information retrieval,Query expansion,Computer science,Sargable,Search engine indexing,Web query classification,Ranking (information retrieval) | Conference |
Citations | PageRank | References |
1 | 0.91 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ismail Sengor Altingovde | 1 | 320 | 29.96 |
| Engin Demir | 2 | 343 | 14.59 |
| Fazli Can | 3 | 581 | 94.63 |
| Özgür Ulusoy | 4 | 1250 | 113.15 |