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Popularity estimation of interesting locations from visitor’s trajectories using fuzzy inference system

Popularity estimation of interesting locations from visitor’s trajectories using fuzzy inference... AbstractIdentifying the interesting places through GPStrajectory mining has been well studied based on the visitor’sfrequency. However, the places popularity estimationbased on the trajectory analysis has not been explored yet.The limitation in the majority of the traditional popularityestimation and place user-rating based methods is that allthe participants are given the same importance. In reality,it heavily depends on the visitor’s category, for example,international visitors make distinct impact on popularity.The proposed method maintains a registry to keep the informationabout the visited users, their stay time and thetravel distance from their home location. Depending onthe travel nature the visitors are labeled as native, regionaland tourist for each place in question. It considers the factthat the higher stay in a place is an implicit measure of thegreater likings. Theweighted frequency is eventually fuzzified and applied rule based fuzzy inference system (FIS) tocompute popularity of the places in terms of the ratings∈ [0, 5]. We have evaluated the proposed method using alarge real road GPS trajectory of 182 users for identifyingthe ratings for the collected 26807 point of interests (POI)in Beijing (China). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Open Computer Science de Gruyter

Popularity estimation of interesting locations from visitor’s trajectories using fuzzy inference system

Tiwari, Shivendra; Kaushik, Saroj
Open Computer Science , Volume 6 (1): 17 – Jan 1, 2016
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Publisher
de Gruyter
Copyright
© 2016 S. Tiwari and S. Kaushik
eISSN
2299-1093
DOI
10.1515/comp-2016-0002
Publisher site
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Abstract

AbstractIdentifying the interesting places through GPStrajectory mining has been well studied based on the visitor’sfrequency. However, the places popularity estimationbased on the trajectory analysis has not been explored yet.The limitation in the majority of the traditional popularityestimation and place user-rating based methods is that allthe participants are given the same importance. In reality,it heavily depends on the visitor’s category, for example,international visitors make distinct impact on popularity.The proposed method maintains a registry to keep the informationabout the visited users, their stay time and thetravel distance from their home location. Depending onthe travel nature the visitors are labeled as native, regionaland tourist for each place in question. It considers the factthat the higher stay in a place is an implicit measure of thegreater likings. Theweighted frequency is eventually fuzzified and applied rule based fuzzy inference system (FIS) tocompute popularity of the places in terms of the ratings∈ [0, 5]. We have evaluated the proposed method using alarge real road GPS trajectory of 182 users for identifyingthe ratings for the collected 26807 point of interests (POI)in Beijing (China).

Journal

Open Computer Science – de Gruyter

Published: Jan 1, 2016

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