博碩士論文 etd-0721105-171155 詳細資訊


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姓名 周祐平(Yu-ping Chou) 電子郵件信箱 m924020031@student.nsysu.edu.tw
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 93學年第2學期
論文名稱(中) 一個以時間曆為基礎的移動物件群組探勘研究
論文名稱(英) The Discovery of Calendar-Based Mobile Groups
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    摘要(中) 先前移動物件行動群組探勘的研究,使我們對於如何依照物件移動資料,去判別是否為物件群組有了認知。由於尖端的行動設備,移動資料已可被廣泛取得。然而,現有行動群組探勘的方法並沒有考慮時間層面,因此無法產出更有應用價值的資訊。考量人類行為常常遵循某些時間特性,像是定期的活動、假日、和某些重要日子等,本研究於是致力於發掘遵循某個時間型態而聚集的移動群組。在我們的研究中,我們採用了時間曆表示機制作為我們在時間層面的表示法。基於這個新的考量,我們提出一個新的問題,稱之為時間曆為基礎的移動物件群組探勘問題,並對此問題發展出有效率的演算法。我們也利用合成資料來評估這些提出的演算法。
    摘要(英) Previous work on moving object mobile group pattern mining defined and proposed algorithms for mobile group mining based on their individual movement data. Movement data is expected to be widely available owing to the increasing popularity of tractable mobile devices on the cutting edge. However, existing approaches of mobile group pattern mining do not consider temporal dimension. Considering that human beings often act as a group according to some temporal features such as routine activities, in this thesis, we engage in the discovery of valid mobile groups that pertain to the some temporal patterns. In our research, we introduce the calendar-based representation mechanism to be our representation of temporal dimension. Taking the calendar patterns into account, we define a new problem called calendar-based mobile group mining problem and develop efficient algorithms for the problem. The proposed algorithms are evaluated via synthetic location data generated by a sensible data generator.
    關鍵字(中)
  • 時間曆
  • 行動群組
  • 關鍵字(英)
  • Calendar
  • Mobile group
  • 論文目次 CHAPTER 1 INTRODUCTION 1
    1.1 Background 1
    1.2 Motivation 2
    1.3 Thesis Outline 3
    CHAPTER 2 LITERATURE REVIEW 4
    2.1. Group Pattern Mining 4
    2.1.1 Apriori
    參考文獻 [AR00] J. M. Ale, G. H. Rossi, “An approach to discovering temporal association rules,” In Proceedings of the 2000 ACM Symposium on Applied Computing, pp. 294-300, Como, Italy, Mar 2000.
    [AS94] R. Agrawal and R. Srikant, “Fast algorithms for mining association rules,” In Proceedings of the VLDB Conference, pp. 478-499, Sept 1994.
    [AIS93] R. Agrawal, T. Imilienski, and A. Swami, “Mining association rules between sets of items in large databases,” In Proceedings of the ACM SIGMOD International Conference on Management of Database, pp. 207-216, 1993.
    [BJW00] C. Bettini, S. G. Jajodia, and S. X. Wang, “Time Granularities in Databases, Data Mining and Temporal Reasoning,” Springer-Verlag New York Inc, 2000.
    [HDY99] J. Han, G. Dong, Y. Yin, “Efficient mining of partial periodic patterns in time series database,” In Proceedings of the 15th International Conference on Data Engineering, pp. 106-115, Sydney, Australia, Mar 1999.
    [HLC05] S. Y. Hwang, Y. H. Liu, J. K. Chiu and E. P. Lim, “Mining Mobile Group Patterns: A Trajectory-based Approach,” In Proceedings of the 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD05), Hanoi, Vietnam, 2005.
    [LMF86] B. Leban, D. McDonald, and D. Foster, “A representation for collections of temporal intervals,” In Proceedings of the 5th International Conference on Artificial Intelligence, pp. 367-371, 1986.
    [LN03] Y. Li, P. Ning, X. S. Wang, and S. Jajodia, “Discovering Calendar-based Temporal Association Rules,” Data and Knowledge Engineering, pp. 192-218, 2003.
    [LWJ00] Y. Li, X. S. Wang, and S. Jajodia, “Discovering temporal patterns in multiple granularities,” In Proceedings of Int'l Workshop on Temporal, Spatial and Spatio-temporal Data Mining, 2000.
    [ORS98] B. Özden, S. Ramaswamy, and A. Sillberschatz, “Cyclic association rules,” In Proceedings of the 14th International Conference on Data Engineering, pp. 412-421, Feb 1998.
    [RMS98] S. Ramaswamy, S. Mahajan, and A. Sillberschatz, “On the discovery of interesting patterns in association rules,” In Proceedings of the 1998 International Conference on Very Large Data Base, pp. 368-379, Aug 1998.
    [WLH03] Y. Wang, E. P. Lim, and S.Y. Hwang, “On Mining Group Patterns of Mobile Users,” In Proceedings Of the 14th International Conference on Database and Expert Systems Applications-DEXA 2003, pp. 1-5, Sept 2003.
    [WLH04]Y. Wang, E. P. Lim, and S. Y. Hwang, “Efficient Group Pattern Mining Using Data Summarization,” In Proceedings of the 9th International Conference on Database Systems for Advanced Application (DASFAA2004), Seoul, Korea, 2004.
    [ZSA02] G. Zimbrão, J. M. de Souza, V. T. de Almeida, W. A. da Silva, “An algorithm to discover calendar-based temporal association rules with item's lifespan restriction”, In Proceedings of the Eight ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - 2nd Workshop on Temporal Data Mining, pp. 701–706, Edmonton, Alberta, Canada, Jul 2002.
    口試委員
  • 魏志平 - 召集委員
  • 林福仁 - 委員
  • 黃三益 - 指導教授
  • 口試日期 2005-07-19 繳交日期 2005-07-21

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