@article{aea42b02fe9643c695ade7830ff3fe0f,
title = "MPTR: A maximal-marginal-relevance-based personalized trip recommendation method",
abstract = "Personalized trip recommendation has drawn much attention recently with the development of location-based services. How to utilize the data in the location-based social network to recommend a single Point of Interest (POI) or a sequence of POIs for users is an important question to answer. Recommending the latter is called trip recommendation that is a challenging study because of the diversity of trips and complexity of involved computation. This work proposes a maximal-marginal-relevance-based personalized trip recommendation method that considers both relevance and diversity of trips in trip planning. An ant-colony-optimization-based trip planning algorithm is developed to efficiently plan a trip. Finally, case studies and experiments illustrate the effectiveness of our method.",
keywords = "Ant colony optimization, Location-based social networks, Personalized trip recommendation",
author = "Wenjing Luan and Guanjun Liu and Changjun Jiang and Mengchu Zhou",
note = "Funding Information: Manuscript received December 17, 2016; revised May 20, 2017 and September 12, 2017; accepted November 22, 2017. Date of publication March 5, 2018; date of current version November 9, 2018. This work was supported in part by the National Key R&D Program of China under Grant 2017YFB1001804, in part by the Shanghai Science and Technology Innovation Action Plan Project under Grant 16511100900, in part by the National Natural Science Foundation of China under Grant 61572360, and in part by the Fundo para o Desenvolvimento das Ciencias e da Tecnologia under Grant 119/2014/A3. The Associate Editor for this paper was K. Savla. (Corresponding authors: GuanJun Liu; MengChu Zhou.) W. Luan, G. Liu, and C. Jiang are with the Key Laboratory of Embedded System and Service Computing, Ministry of Education, Shanghai Electronic Transactions and Information Service Collaborative Innovation Center, Department of Computer Science, Tongji University, Shanghai 201804, China. (e-mail: wenjingmengjing@163.com; liugj1116@ 163.com; cjjiang@tongji.edu.cn). Publisher Copyright: {\textcopyright} 2000-2011 IEEE.",
year = "2018",
month = nov,
doi = "10.1109/TITS.2017.2781138",
language = "English (US)",
volume = "19",
pages = "3461--3474",
journal = "IEEE Transactions on Intelligent Transportation Systems",
issn = "1524-9050",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "11",
}