Research on Knowledge Discovery on Documents in Spatiotemporal Document Streams
| Project/Area Number |
23700124
|
|---|
| Research Category |
Grant-in-Aid for Young Scientists (B)
|
| Allocation Type | Multi-year Fund |
|---|
| Research Field |
Media informatics/Database
|
|---|
| Research Institution | Hiroshima City University |
|---|
Principal Investigator |
TAMURA Keiichi 広島市立大学, 情報科学研究科, 准教授 (80347616)
|
|---|
| Project Period (FY) |
2011 – 2012
|
| Project Status |
Completed (Fiscal Year 2012)
|
| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2012: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2011: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
|
|---|
| Keywords | テキストマイニング / 文書ストリーム / 情報検索 / ソーシャルメディア / 並列分散処理 |
|---|
| Research Abstract |
This study has developed a novel method for extracting spatiotemporal social events and hot topics in a spatiotemporal document stream. In this study, a mathematical model for spatiotemporal document stream is defined. Spatiotemporal social events and hot topics can be extracted by using the location-based burst detection algorithm. To extract bursts for topics, the clustering-based burst detection algorithm is proposed. Moreover, the parallelization method for burst detection algorithm, which is developed in this study, archives the speed-up of extracting bursts on the large-scale spatiotemporal document streams.
|
Report
(3 results)
Research Products
(27 results)
