Spatio-temporal text mining based on real-time information retrieval
| Project/Area Number |
25330363
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Web informatics, Service informatics
|
|---|
| Research Institution | Konan University (2014-2015)
Kobe University (2013) |
|---|
Principal Investigator |
Seki Kazuhiro 甲南大学, 知能情報学部, 准教授 (30444566)
|
|---|
| Project Period (FY) |
2013-04-01 – 2016-03-31
|
| Project Status |
Completed (Fiscal Year 2015)
|
| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2013: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
|
|---|
| Keywords | リアルタイム検索 / 株価動向予測 / 経済指標 / 株価 / ニューラルネットワーク / 深層学習 / マイクロブログ / 情報検索 / 情報抽出 / Twitter / 疑似適合フィードバック / クエリ拡張 / リアルタイム / コンセプト |
|---|
| Outline of Final Research Achievements |
This research project first studied realtime information retrieval systems, which consider temporal properties of users' information needs, as a building block of intelligent information systems, and then investigated spatio-temporal text mining. The main outcome of the project is two-fold: one is to devise a realtime microblog retrieval model modeling trends of topics, and the other is the development of a framework to predict short-term stock price movements using recursive neural networks analyzing breaking news headlines.
|
Report
(4 results)
Research Products
(35 results)
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
[Presentation] 深層学習による経済指標動向推定2014
Author(s)
吉原輝，藤川和樹，関和広，上原邦昭
Organizer
第28回人工知能学会全国大会
Place of Presentation
ひめぎんホール（愛媛県松山市）
Year and Date
2014-05-12 – 2014-05-15
Related Report
-
-
-
-
-
