English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 52333/87441 (60%)
造訪人次 : 9102537      線上人數 : 201
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/106215

    題名: Mining Temporal Patterns in Time Interval-Based Data
    作者: Chen, Yi-Cheng;Peng, Wen-Chih;Lee, Suh-Yin
    關鍵詞: data mining;interval-based event;representation;sequential pattern;temporal pattern
    日期: 2015-12-01
    上傳時間: 2016-04-22 13:42:04 (UTC+8)
    出版者: IEEE
    摘要: Sequential pattern mining is an important subfield in data mining. Recently, applications using time interval-based event data have attracted considerable efforts in discovering patterns from events that persist for some duration. Since the relationship between two intervals is intrinsically complex, how to effectively and efficiently mine interval-based sequences is a challenging issue. In this paper, two novel representations, endpoint representation and endtime representation, are proposed to simplify the processing of complex relationships among event intervals. Based on the proposed representations, three types of interval-based patterns: temporal pattern, occurrence-probabilistic temporal pattern and duration-probabilistic temporal pattern, are defined. In addition, we develop two novel algorithms, Temporal Pattern Miner (TPMiner) and Probabilistic Temporal Pattern Miner (P-TPMiner), to discover three types of interval-based sequential patterns. We also propose three pruning techniques to further reduce the search space of the mining process. Experimental studies show that both algorithms are able to find three types of patterns efficiently. Furthermore, we apply proposed algorithms to real datasets to demonstrate the effectiveness and validate the practicability of proposed patterns.
    關聯: IEEE Transactions on Knowledge and Data Engineering 27(12), pp.3318-3331
    DOI: 10.1109/TKDE.2015.2454515
    顯示於類別:[資訊工程學系暨研究所] 期刊論文


    檔案 描述 大小格式瀏覽次數



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋