博碩士論文 etd-0801106-122022 詳細資訊


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姓名 李宗翰(Chung-Han Lee) 電子郵件信箱 E-mail 資料不公開
畢業系所 資訊管理學系研究所(Information Management)
畢業學位 碩士(Master) 畢業時期 94學年第2學期
論文名稱(中) 以時間曆為基礎的移動群組型態探勘
論文名稱(英) The Discovery of Calendar-Based Mobile Group Patterns in Spatial-Temporal Databases
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    摘要(中) 近幾年來,由於行動設備的普及,以及相關設備軟硬體的發展,行動資料已可廣泛取得,根據地理資訊判斷物體是否為同一群組是一個新興的研究。本研究考量在時間與空間兩個面向上,移動群組的發掘。先前的研究將時間視為整段區塊或是簡單的時間循環,但是考慮到一般群組的聚集情況往往遵循某個時間型態,尤其是人類的群組的出現情況,常與約定俗成的時間曆有關,但卻又不一定嚴格遵守特定的規律。所以我們提出一個更具彈性的時間曆表示法(flexible calendar pattern),並針對建構在新的時間面向表示法上的移動群組發掘發展出有效率的演算法。本文以IBM City Simulator產生的合成資料進行演算法的效率評估。實驗結果證明本研究所提出的方法可以有效的降低所需的執行時間。
    摘要(英) In the past few years, due to the development of the mobile devices and the improvement of database technology, the geometric information has become widely available. Identifying object groups based on spatial-temporal dimension is an emerging research topic. Previous work has incorporating the spatial and temporal information pertaining to moving objects in finding mobile groups. Considering that mobile groups tend to exhibit some calendar-like temporal features, we define a new temporal presentation mechanism called flexible calendar pattern, which allows users to specify the desired calendar patterns at a coarse level. In addition, we developed efficient algorithms for mining mobile groups pertaining some user-specified flexible calendar pattern. The proposed algorithms are evaluated via the synthetic data generated by IBM City Simulator. The results show that our approaches prove to perform more efficiently than other intuitive approaches.
    關鍵字(中)
  • 時間
  • 群組
  • 關鍵字(英)
  • calendar pattern
  • group pattern mining
  • mobile group pattern
  • 論文目次 CHAPTER 1 INTRODUCTION 5
    1.1 BACKGROUND 5
    1.2 MOTIVATION 6
    1.3 THESIS OUTLINE 6
    CHAPTER 2 LITERATURE REVIEW 9
    2.1 MOBILE GROUP MINING 9
    2.2 TEMPORAL ASSOCIATION RULE MINING 10
    2.3 CALENDAR-BASED SPATIO-TEMPORAL ASSOCIATION RULE MINING 12
    CHAPTER 3 THE PROBLEM 20
    3.1 AUXILIARY DEFINITIONS 20
    3.2 THE MINING PROBLEM 23
    CHAPTER 4 THE MINING ALGORITHMS 26
    4.1 CAGP 26
    4.2 CVG-GROWTH 33
    CHAPTER 5 PERFORMANCE EVALUATION 39
    5.1 EXPERIMENTAL DESIGN 39
    5.2 EVALUATING CAGP 42
    5.3 EVALUATING CVG-GROWTH 46
    5.4 COMPARING CAGP AND CVG-GROWTH 49
    CHAPTER 6 CONCLUSIONS 52
    REFERENCES 53
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    口試委員
  • 魏志平 - 召集委員
  • 楊婉秀 - 委員
  • 黃三益 - 指導教授
  • 口試日期 2006-07-21 繳交日期 2006-08-01

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