Hierarchical LSTM:Modeling Temporal Dynamics and Taxonomy in Location-Based Mobile Check-Ins

摘要：

　　“Is there any pattern in location-based,mobile check-in activities? “If yes,is it possible to accurately predict the intention of a users next check-in,given his/her check-in history? To answer these questions,we study and analyze probably the largest mobile check-in datasets,containing 20 millions check-in activities from 0.4 million users.We provide two observations: “work-n-relax and “diurnal-n-nocturnal showing that the intentions of users check-ins are strongly associated with time.Furthermore,the category of each check-in venue,which reveals users intentions,has structure and forms taxonomy.In this paper,we propose Hierarchical LSTM that takes both(a)check-in time and(b)taxonomy structure of venues from check-in sequences into consideration,providing accurate predictions on the category of a users next check-in location.Hierarchical LSTM also projects each category into an embedding space,providing a new representation with stronger semantic meanings.Experimental results are poised to demonstrate the effectiveness of the proposed Hierarchical LSTM:(a)Hierarchical LSTM improves Accuracy@5 by 4.22%on average,and(b)Hierarchical LSTM learns a better taxonomy embedding for clustering categories,which improves Silhouette Coefficient by 1.5X.

关键词： Long Short-Term Memory Location-Based Social Network Point of Interest Behavior model

作者: Chun-Hao Liu Da-Cheng Juan Xuan-An Tseng Wei Wei Yu-Ting Chen Jia-Yu Pan Shih-Chieh Chang

作者单位: National Tsing Hua University,Hsinchu,Taiwan Carnegie Mellon University,Pittsburgh,USA University of California,Los Angeles,Los Angeles,USA National Tsing Hua University,Hsinchu,Taiwan;Electronic and Optoelectronic System Research Laborator

会议类型: 国际会议

会议名称: The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (第23届亚太知识发现和数据挖掘国际会议(PAKDD2019)

会议地点: 澳门

会议语种:英文

页码: 217-228

在线出版日期: 2019-04-14（万方平台首次上网日期，不代表论文的发表时间）