教師資料查詢 | 類別: 期刊論文 | 教師: 洪智傑 HUNG CHIH-CHIEH (瀏覽個人網頁)

標題:Exploring Sequential Probability Tree for Movement-based Community Discovery
學年103
學期1
出版(發表)日期2014/11/01
作品名稱Exploring Sequential Probability Tree for Movement-based Community Discovery
作品名稱(其他語言)
著者Zhu, Wen-Yuan; Peng, Wen-Chih; Hung, Chih-Chieh; Lei, Po-Ruey; Chen, Ling-Jyh
單位
出版者
著錄名稱、卷期、頁數IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 26(11), pp.2717-2730
摘要In this paper, we tackle the problem of discovering movement-based communities of users, where users in the same community have similar movement behaviors. Note that the identification of movement-based communities is beneficial to location-based services and trajectory recommendation services. Specifically, we propose a framework to mine movement-based communities which consists of three phases: 1) constructing trajectory profiles of users, 2) deriving similarity between trajectory profiles, and 3) discovering movement-based communities. In the first phase, we design a data structure, called the Sequential Probability tree (SP-tree), as a user trajectory profile. SP-trees not only derive sequential patterns, but also indicate transition probabilities of movements. Moreover, we propose two algorithms: BF (standing for breadth-first) and DF (standing for depth-first) to construct SP-tree structures as user profiles. To measure the similarity values among users\' trajectory profiles, we further develop a similarity function that takes SP-tree information into account. In light of the similarity values derived, we formulate an objective function to evaluate the quality of communities. According to the objective function derived, we propose a greedy algorithm Geo-Cluster to effectively derive communities. To evaluate our proposed algorithms, we have conducted comprehensive experiments on two real data sets. The experimental results show that our proposed framework can effectively discover movement-based user communities.
關鍵字Trajectory profile;community structure;trajectory pattern mining
語言英文(美國)
ISSN1041-4347;1558-2191
期刊性質國外
收錄於SCI;EI;
產學合作
通訊作者
審稿制度
國別中華民國
公開徵稿
出版型式,電子版,紙本
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