A Novel Approach to Mining Travel Sequences Using Collections of Geotagged Photos
作者： Slava Kisilevich , Daniel Keim , Lior Rokach
DOI: 10.1007/978-3-642-12326-9_9
关键词:
摘要: In this paper we present a novel approach for analyzing the trajectories of moving objects and people in particular. The mined data from these sequences can provide valuable information understanding surrounding locations, discovering attractive place or mining frequent visited places. Based on geotagged photos, our framework mines semantically annotated sequences. Our is capable any length to discover patterns that are not necessarily immediate antecedents. consists four main steps. first step, every photo location by assigning it known nearby point interest. second density-based clustering algorithm applied all unassigned creating regions unknown points third travel sequence individual built. final using semantics were obtained two Case studies Guimaraes, Portugal (where conference takes place) Berlin, Germany demonstrate capabilities proposed framework.
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