Name
Abstract | ||
|---|---|---|
With the adoption of timestamps and geotags on Web data, search engines are increasingly being asked questions of \"where\" and \"when\" in addition to the classic \"what.\" In the case of Twitter, many tweets are tagged with location information as well as timestamps, creating a demand for query processors that can search both of these dimensions along with text. We propose 3W, a search framework for geo-temporal stamped documents. It exploits the structure of time-stamped data to dramatically shrink the temporal search space and uses a shallow tree based on the spatial distribution of tweets to allow speedy search over the spatial and text dimensions. Our evaluation on 30 million tweets shows that the prototype system outperforms the baseline approach that uses a monolithic index. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2675354.2675358 | GIR |
Keywords | Field | DocType |
algorithms,efficient query processing,experimentation,systems and software,geographic and temporal search engines,information search and retrieval,performance,twitter search engines | Web search query,Data mining,Search engine,Information retrieval,Computer science,Keyword search,Temporal search,Exploit,Geotagging,Timestamp | Conference |
Citations | PageRank | References |
6 | 0.44 | 30 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergey Nepomnyachiy | 1 | 6 | 0.44 |
| Bluma Gelley | 2 | 6 | 0.44 |
| Wei Jiang | 3 | 220 | 22.56 |
| Tehila Minkus | 4 | 25 | 2.06 |