Name
Abstract | ||
|---|---|---|
Many popular online services provide "local" or "yellow-pages" search, but none of them allow users to customize the search over user-specified data. This paper describes a novel system for providing custom local search over user-provided spatial datasets logically combined with detailed street-level vector data. We present the algorithms and architecture underlying our prototype system, which handles complex queries and elegantly solves the problem of parsing terms from multiple datasets in the presence of ambiguity and misspellings. We show that the system provides custom local search with precision and recall figures that often exceed that of a commercial local search service. Further, we show that our system scales gracefully with the number of individual custom data sets being served simultaneously. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1653771.1653835 | Workshop on Advances in Geographic Information Systems |
Keywords | Field | DocType |
detailed street-level vector data,robust parsing,prototype system,novel system,geocoding,custom local search,multiple datasets,user-specified data,system scale,custom location search,individual custom data,complex query,commercial local search service,local search,service provider | Data mining,Architecture,Data set,Geocoding,Computer science,Precision and recall,Artificial intelligence,Parsing,Local search (optimization),Ambiguity,Machine learning | Conference |
Citations | PageRank | References |
1 | 0.35 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Naren Datha | 1 | 16 | 2.55 |
| Tanuja Joshi | 2 | 59 | 9.76 |
| Joseph Joy | 3 | 88 | 5.40 |
| Vibhuti S. Sengar | 4 | 38 | 4.06 |