Presentation 2011-11-21
A Working Pattern Extraction Method From Low Level PC Usage Logs
Ryohei SAITO, Tetsuji KUBOYAMA, Yuta YAMAKAWA, Hiroshi YASUDA,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper proposes a novel method for analyzing PC usage logs aiming to find working patterns and behaviors of employees at work. The logs we analyze are recorded at individual PCs for employees in a company, and include active window transitions, our method consists of two levels of abstraction: (1) task summarization by HMM; (2) user behavior comparison by kernel Principle Component Analysis based on graph kernel. The experimental results show that our method reveals implicit user behavior at a high level of abstraction, and allows us to understand individual user behavior among groups, and over time.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Log Analysis / Pattern Extraction / Data Mining / Clustering / Graph Kernel
Paper # AI2011-19
Date of Issue

Conference Information
Committee AI
Conference Date 2011/11/14(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Working Pattern Extraction Method From Low Level PC Usage Logs
Sub Title (in English)
Keyword(1) Log Analysis
Keyword(2) Pattern Extraction
Keyword(3) Data Mining
Keyword(4) Clustering
Keyword(5) Graph Kernel
1st Author's Name Ryohei SAITO
1st Author's Affiliation R&D Division, Humming Heads, Inc.()
2nd Author's Name Tetsuji KUBOYAMA
2nd Author's Affiliation Gakushuin University, Computer Centre
3rd Author's Name Yuta YAMAKAWA
3rd Author's Affiliation R&D Division, Humming Heads, Inc.
4th Author's Name Hiroshi YASUDA
4th Author's Affiliation Tokyo Denki University
Date 2011-11-21
Paper # AI2011-19
Volume (vol) vol.111
Number (no) 310
Page pp.pp.-
#Pages 6
Date of Issue