Name
Abstract | ||
|---|---|---|
Query logs record the actual usage of search systems and their analysis has proven critical to improving search engine functionality. Yet, despite the deluge of information, query log analysis often suffers from the sparsity of the query space. Based on the observation that most queries pivot around a single entity that represents the main focus of the user's need, we propose a new model for query log data called the entity-aware click graph. In this representation, we decompose queries into entities and modifiers, and measure their association with clicked pages. We demonstrate the benefits of this approach on the crucial task of understanding which websites fulfill similar user needs, showing that using this representation we can achieve a higher precision than other query log-based approaches. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2396761.2398500 | CIKM |
Keywords | Field | DocType |
similar user need,query log data,entity-aware click graph,website similarity,actual usage,query log-based approach,query space,search engine functionality,query log analysis,query log,search system,queries pivot | Query optimization,Data mining,Web search query,Query language,Information retrieval,Query expansion,Computer science,Sargable,Web query classification,Ranking (information retrieval),Spatial query | Conference |
Citations | PageRank | References |
4 | 0.44 | 20 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pablo N. Mendes | 1 | 1070 | 51.09 |
| Peter Mika | 2 | 2049 | 176.71 |
| Hugo Zaragoza | 3 | 2035 | 111.36 |
| Roi Blanco | 4 | 872 | 57.42 |