{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T14:24:01Z","timestamp":1766067841250,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,10,22]],"date-time":"2023-10-22T00:00:00Z","timestamp":1697932800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Faculty of Informatics, Burapha University","award":["02\/2565"],"award-info":[{"award-number":["02\/2565"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Location-based recommender systems (LBRSs) have exhibited significant potential in providing personalized recommendations based on the user\u2019s geographic location and contextual factors such as time, personal preference, and location categories. However, several challenges (such as data sparsity, the cold-start problem, and tedium problem) need to be addressed to develop more effective LBRSs. In this paper, we propose a novel POI recommendation system, called LACF-Rec3, which employs a hybrid approach of link analysis (HITS-3) and collaborative filtering (CF-3) based on three visiting behaviors: frequency, variety, and repetition. HITS-3 identifies distinctive POIs based on user- and POI-visit patterns, ranks them accordingly, and recommends them to cold-start users. For existing users, CF-3 utilizes collaborative filtering based on their previous check-in history and POI distinctive aspects. Our experimental results conducted on a Foursquare dataset demonstrate that LACF-Rec3 outperforms prior methods in terms of recommendation accuracy, ranking precision, and matching ratio. In addition, LACF-Rec3 effectively solves the challenges of data sparsity, the cold-start issue, and tedium problems for cold-start and existing users. These findings highlight the potential of LACF-Rec3 as a promising solution to the challenges encountered by LBRS.<\/jats:p>","DOI":"10.3390\/ijgi12100431","type":"journal-article","created":{"date-parts":[[2023,10,22]],"date-time":"2023-10-22T07:02:53Z","timestamp":1697958173000},"page":"431","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Hybrid POI Recommendation System Combining Link Analysis and Collaborative Filtering Based on Various Visiting Behaviors"],"prefix":"10.3390","volume":"12","author":[{"given":"Sumet","family":"Darapisut","sequence":"first","affiliation":[{"name":"Faculty of Informatics, Burapha University, Chonburi 20131, Thailand"}]},{"given":"Komate","family":"Amphawan","sequence":"additional","affiliation":[{"name":"Faculty of Informatics, Burapha University, Chonburi 20131, Thailand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8883-3629","authenticated-orcid":false,"given":"Nutthanon","family":"Leelathakul","sequence":"additional","affiliation":[{"name":"Faculty of Informatics, Burapha University, Chonburi 20131, Thailand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8827-2902","authenticated-orcid":false,"given":"Sunisa","family":"Rimcharoen","sequence":"additional","affiliation":[{"name":"Faculty of Informatics, Burapha University, Chonburi 20131, Thailand"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zheng, Y., and Zhou, X. (2011). Computing with Spatial Trajectories, Springer.","DOI":"10.1007\/978-1-4614-1629-6"},{"key":"ref_2","unstructured":"Yu, Y., and Chen, X. (2015, January 25\u201330). A survey of point-of-interest recommendation in location-based social networks. Proceedings of the Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, Austin, TX, USA."},{"key":"ref_3","unstructured":"Zhao, S., King, I., and Lyu, M.R. (2016). A survey of point-of-interest recommendation in location-based social networks. arXiv."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1621","DOI":"10.1007\/s11280-019-00777-8","article-title":"Survey on user location prediction based on geo-social networking data","volume":"23","author":"Xu","year":"2020","journal-title":"World Wide Web"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Bao, J., Zheng, Y., and Mokbel, M.F. (2012, January 6\u20139). Location-based and preference-aware recommendation using sparse geo-social networking data. Proceedings of the 20th International Conference on Advances in Geographic Information Systems, Redon Beach, CA, USA.","DOI":"10.1145\/2424321.2424348"},{"key":"ref_6","unstructured":"Kosseim, L., and Inkpen, D. (2012, January 28\u201330). A Study of Recommending Locations on Location-Based Social Network by Collaborative Filtering. Proceedings of the Advances in Artificial Intelligence, Toronto, ON, Canada."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1007\/s10115-017-1056-y","article-title":"Personalized Trip Recommendation for Tourists Based on User Interests, Points of Interest Visit Durations and Visit Recency","volume":"54","author":"Lim","year":"2018","journal-title":"Knowl. Inf. Syst."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1145\/324133.324140","article-title":"Authoritative sources in a hyperlinked environment","volume":"46","author":"Kleinberg","year":"1999","journal-title":"J. ACM"},{"key":"ref_9","first-page":"84","article-title":"N-Most Interesting Location-based Recommender System","volume":"16","author":"Darapisut","year":"2022","journal-title":"ECTI Trans. Comput. Inf. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Baral, R., Wang, D., Li, T., and Chen, S.C. (2016, January 28\u201330). GeoTeCS: Exploiting Geographical, Temporal, Categorical and Social Aspects for Personalized POI Recommendation (Invited Paper). Proceedings of the 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI), Pittsburgh, PA, USA.","DOI":"10.1109\/IRI.2016.20"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1007\/s13278-023-01106-8","article-title":"Trust-aware spatial\u2013temporal feature estimation for next POI recommendation in location-based social networks","volume":"13","author":"Acharya","year":"2023","journal-title":"Soc. Netw. Anal. Min."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Gan, M., and Gao, L. (2019). Discovering Memory-Based Preferences for POI Recommendation in Location-Based Social Networks. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8060279"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"36215","DOI":"10.1007\/s11042-021-11407-9","article-title":"A Tensor Decomposition Based Collaborative Filtering Algorithm for Time-Aware POI Recommendation in LBSN","volume":"80","author":"Yin","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Long, X., and Joshi, J. (2013, January 25\u201328). A HITS-based POI recommendation algorithm for Location-Based Social Networks. Proceedings of the 2013 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013), Niagara Falls, ON, Canada.","DOI":"10.1145\/2492517.2492652"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.neucom.2017.02.067","article-title":"A temporal-aware POI recommendation system using context-aware tensor decomposition and weighted HITS","volume":"242","author":"Ying","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_16","unstructured":"Wang, Y., Wang, L., Li, Y., He, D., and Liu, T.Y. (2013, January 12\u201314). A theoretical analysis of NDCG type ranking measures. Proceedings of the Conference on Learning Theory, PMLR, Princeton, NJ, USA."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/S0169-7552(98)00087-7","article-title":"Automatic resource compilation by analyzing hyperlink structure and associated text","volume":"30","author":"Chakrabarti","year":"1998","journal-title":"Comput. Netw. ISDN Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1007\/s10707-014-0220-8","article-title":"Recommendations in location-based social networks: A survey","volume":"19","author":"Bao","year":"2015","journal-title":"GeoInformatica"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Darapisut, S., Amphawan, K., Rimcharoen, S., and Leelathakul, N. (2020, January 17\u201319). NILR: N-Most Interesting Location-based Recommender System. Proceedings of the Conference on Smart Media and Applications, Jeju, Republic of Korea.","DOI":"10.1145\/3426020.3426145"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Zhang, L., Xie, X., and Ma, W.Y. (2009, January 20\u201324). Mining interesting locations and travel sequences from GPS trajectories. Proceedings of the 18th International Conference on World Wide Web, Madrid, Spain.","DOI":"10.1145\/1526709.1526816"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s10115-015-0857-0","article-title":"Context-aware location recommendation by using a random walk-based approach","volume":"47","author":"Bagci","year":"2016","journal-title":"Knowl. Inf. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Strauss, C., Kotsis, G., Tjoa, A.M., and Khalil, I. (2021, January 27\u201330). Property Analysis of Stay Points for POI Recommendation. Proceedings of the Database and Expert Systems Applications, Virtual Event.","DOI":"10.1007\/978-3-030-86472-9"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Fan, J., Pan, C., Geng, Y., and Li, S. (2023). A Privacy-Preserving Time-Aware Method for Next POI Recommendation. Electronics, 12.","DOI":"10.3390\/electronics12153208"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Sarwar, B., Karypis, G., Konstan, J., and Riedl, J. (2001, January 1\u20135). Item-based collaborative filtering recommendation algorithms. Proceedings of the 10th International Conference on World Wide Web, Hong Kong, China.","DOI":"10.1145\/371920.372071"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"421425","DOI":"10.1155\/2009\/421425","article-title":"A survey of collaborative filtering techniques","volume":"2009","author":"Su","year":"2009","journal-title":"Adv. Artif. Intell."},{"key":"ref_26","unstructured":"Koren, Y., Rendle, S., and Bell, R. (2021). Recommender Systems Handbook, Springer."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1007\/s10618-017-0537-7","article-title":"Exploiting the roles of aspects in personalized POI recommender systems","volume":"32","author":"Baral","year":"2018","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"105849","DOI":"10.1016\/j.knosys.2020.105849","article-title":"Personalized location recommendation by fusing sentimental and spatial context","volume":"196","author":"Zhao","year":"2020","journal-title":"Knowl.-Based Syst."},{"key":"ref_29","unstructured":"Yuan, Q., Cong, G., Ma, Z., Sun, A., and Thalmann, N.M. (August, January 28). Time-Aware Point-of-Interest Recommendation. Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, New York, NY, USA. SIGIR \u201913."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.knosys.2017.04.013","article-title":"CTF-ARA: An adaptive method for POI recommendation based on check-in and temporal features","volume":"128","author":"Si","year":"2017","journal-title":"Knowl.-Based Syst."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Khazaei, E., and Alimohammadi, A. (2019). Context-Aware Group-Oriented Location Recommendation in Location-Based Social Networks. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8090406"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zhang, H., Gan, M., and Sun, X. (2021). Incorporating Memory-Based Preferences and Point-of-Interest Stickiness into Recommendations in Location-Based Social Networks. ISPRS Int. J. Geo-Inf., 10.","DOI":"10.3390\/ijgi10010036"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Zhou, K., and Chen, S. (2023). Context-Aware Point-of-Interest Recommendation Based on Similar User Clustering and Tensor Factorization. ISPRS Int. J. Geo-Inf., 12.","DOI":"10.3390\/ijgi12040145"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1109\/TSMC.2014.2327053","article-title":"Modeling user activity preference by leveraging user spatial temporal characteristics in LBSNs","volume":"45","author":"Yang","year":"2014","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Yang, S., Liu, J., and Zhao, K. (2022, January 11\u201315). GETNext: Trajectory Flow Map Enhanced Transformer for Next POI Recommendation. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, New York, NY, USA. SIGIR \u201922.","DOI":"10.1145\/3477495.3531983"},{"key":"ref_36","unstructured":"(2022, August 01). Geocoding API. Available online: https:\/\/developers.google.com\/maps\/documentation\/geocoding\/."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3212509","article-title":"Efficient privacy-preserving matrix factorization for recommendation via fully homomorphic encryption","volume":"21","author":"Kim","year":"2018","journal-title":"ACM Trans. Priv. Secur."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ge, Z., Liu, X., Li, Q., Li, Y., and Guo, D. (2021). PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation. Int. J. Distrib. Sens. Netw., 17.","DOI":"10.1177\/15501477211061250"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3568954","article-title":"On the user behavior leakage from recommender system exposure","volume":"41","author":"Xin","year":"2023","journal-title":"ACM Trans. Inf. Syst."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/12\/10\/431\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:09:54Z","timestamp":1760130594000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/12\/10\/431"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,22]]},"references-count":39,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2023,10]]}},"alternative-id":["ijgi12100431"],"URL":"https:\/\/doi.org\/10.3390\/ijgi12100431","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2023,10,22]]}}}