Name
Abstract | ||
|---|---|---|
The search terms that a user passes to a search engine are often ambiguous, referring to homonyms. The results in these cases are a mixture of links to documents that contain different meanings of the search terms. To improve the search for homonyms, we previously designed an Ontology-Supported Web Search System (OSWS) for "famous people." To serve this system, we built an ontology of famous people based on mining the suggested completions of a search engine and on data from DBpedia. In this paper, we present an approach to improve the OSWS ontology by mining data from Facebook "people public pages." Facebook attributes are cleaned up and mapped to the OSWS ontology. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2494068.2494073 | SSW@VLDB |
Field | DocType | Citations |
Ontology,Data mining,World Wide Web,Social network,Search engine,Information retrieval,Computer science,Homonym,Database | Conference | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Soon Ae Chun | 1 | 893 | 100.67 |
| Tian Tian | 2 | 120 | 17.90 |
| James Geller | 3 | 0 | 0.34 |