| Presentation | 2017-09-19 Model Ensemble for Failure Event Detection using Multiple User Activity Data on the Web Motoyuki Oki, Koh Takeuchi, Yukio Uematsu, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Mobile network service providers aim to maintain stable operation and improve service performance using multiple user's activity data. The data is sometimes corrupted by a number of unusual behavior such as service failure occurrence. In this paper, we address the detection and forecasting problems of finding and extracting failure event. We collect tweets related to the service, search queries on a search box, and web access logs from official web pages. We present the feature extraction for text classification problems and informative representation of the time series. We propose ensemble event detection and forecasting methods using supervised classification models and unsupervised anomaly detection models. Experiments to detect and predict multiple failure events in a content service provider demonstrate the effectiveness of the proposed method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Failure Prediction / Event Detection / Social Network / Machine Learning / Ensemble Model |
| Paper # | DE2017-20 |
| Date of Issue | 2017-09-11 (DE) |
| Conference Information | |
| Committee | DE / IPSJ-DBS / IPSJ-IFAT |
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| Conference Date | 2017/9/18(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Ochanomizu University |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Big Data Management, Information Retrieval, Knowledge Discovery, etc. |
| Chair | Akiyo Nadamoto(Konan Univ.) |
| Vice Chair | Koji Eguchi(Kobe Univ.) / Shingo Otsuka(Kanagawa Inst. of Tech.) |
| Secretary | Koji Eguchi(Kogakuin Univ.) / Shingo Otsuka(Univ. of Marketing and Distrbution Science) |
| Assistant | Kazuo Goda(Univ. of Tokyo) / Yuroaki Shiokawa(Tsukuba Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Data Engineering / Special Interest Group on Database System / Special Interest Group on Information Fundamentals and Access Technologies |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Model Ensemble for Failure Event Detection using Multiple User Activity Data on the Web |
| Sub Title (in English) | |
| Keyword(1) | Failure Prediction |
| Keyword(2) | Event Detection |
| Keyword(3) | Social Network |
| Keyword(4) | Machine Learning |
| Keyword(5) | Ensemble Model |
| 1st Author's Name | Motoyuki Oki |
| 1st Author's Affiliation | NTT Communications Corporation(NTT Communications) |
| 2nd Author's Name | Koh Takeuchi |
| 2nd Author's Affiliation | NTT Communication Science Laboratories(NTT) |
| 3rd Author's Name | Yukio Uematsu |
| 3rd Author's Affiliation | NTT Communications Corporation(NTT Communications) |
| Date | 2017-09-19 |
| Paper # | DE2017-20 |
| Volume (vol) | vol.117 |
| Number (no) | DE-212 |
| Page | pp.pp.123-128(DE), |
| #Pages | 6 |
| Date of Issue | 2017-09-11 (DE) |