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研究生:黃錦銘
研究生(外文):Chin-Ming Huang
論文名稱:探勘行動群組模式-利用軌跡概算
論文名稱(外文):Mining Mobile Group Patterns Using Trajectory Approximation
指導教授:黃三益黃三益引用關係
指導教授(外文):San -Yih Hwang
學位類別:碩士
校院名稱:國立中山大學
系所名稱:資訊管理學系研究所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:英文
論文頁數:54
中文關鍵詞:行動群組軌跡
外文關鍵詞:mobile group patterngroup pattern miningtrajectory approximationtrajectorymobile data mining
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近年來,隨著行動設備的普及,有越來越多的地理資訊應用軟體(如GPS,電子地圖等)被開發出來,對於這些行動裝置來說,它們必須先搜集到所有使用者位置,對於這些搜集到的資料,我們相當感興趣。對於相近的東西,或常聚在一起的群體,它們之間都會有某些關係性存在,基於這個觀點,我們便希望能利用這些地理資料可以找出這些有關係的群體。
現今,許多儲存行動裝置使用者的地理資訊,所使用的方式,是每固定時間點,便儲存一次其所在位置,這樣的儲存方式會造成資料量非常龐大;本篇論文中,我們便利用軌跡的方式,模擬出物體的移動情況,來改善資料儲存的問題,以軌跡的描述方式,可以降低原本龐大的資料量,進而有效的找出我們所感興趣的-行動群組模式。
In this paper, we present a novel approach to mine moving object group patterns from object movement database. At first, our approaches summarize the raw data in the source object movement database into trajectories, and then discover valid 2-groups mainly from the trajectory-based object movement database.
We propose two trajectory conversion methods, namely linear regression and vector conversion. We further propose a trajectory based mobile group mining algorithm that is intended to reduce the overhead of mining 2-Group Patterns. The use of trajectories allows valid 2-groups to be mined using smaller number of summarized records (in trajectory model) and examining smaller number of candidate 2-groups.
Finally, we conduct series of comprehensive experiments to evaluate and compare the performances of the proposed methods with existing approaches that use source object movement database or other summarization techniques. The experimental results demonstrate the superior performance of our proposed approach.
1.Introduction
2.Related Work
3.Problem Definition
4.Mining Valid 2-Groups Using Trajectory Approximation
5.Performance Evaluation
6.Conclusions
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