Name
Abstract | ||
|---|---|---|
In this paper we propose an attribute retrieval approach which extracts and ranks attributes from Web tables. We combine simple heuristics to filter out improbable attributes and we rank attributes based on frequencies and a table match score. Ranking is reinforced with external evidence from Web search, DBPedia and Wikipedia. Our approach can be applied to whatever instance (e.g. Canada) to retrieve its attributes (capital, GDP). It is shown it has a much higher recall than DBPedia and Wikipedia and that it works better than lexico-syntactic rules for the same purpose. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1998076.1998153 | JCDL |
Keywords | Field | DocType |
improbable attribute,attribute retrieval approach,web table,simple heuristics,web search,ranks attribute,lexico-syntactic rule,external evidence,higher recall,table match score,information retrieval | Information retrieval,Ranking,Computer science,Heuristics,Web tables,Recall | Conference |
Citations | PageRank | References |
4 | 0.39 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arlind Kopliku | 1 | 64 | 9.45 |
| Karen Pinel-Sauvagnat | 2 | 175 | 24.64 |
| Mohand Boughanem | 3 | 923 | 109.00 |