{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:20:12Z","timestamp":1760232012989,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T00:00:00Z","timestamp":1652659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science and Technology, Taiwan","award":["MOST 110-2121-M-224-001","MOST110-2221-E-006-176"],"award-info":[{"award-number":["MOST 110-2121-M-224-001","MOST110-2221-E-006-176"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Spatial information analysis has gained increasing attention in recent years due to its wide range of applications, from disaster prevention and human behavioral patterns to commercial value. This study proposes a novel application to help businesses identify optimal locations for new stores. Optimal store locations are close to other stores with similar customer groups. However, they are also a suitable distance from stores that might represent competition. The style of a new store also exerts a significant effect. In this paper, we utilized check-in data and user profiles from location-based social networks to calculate the degree of influence of each store in a road network on the query user to identify optimal new store locations. As calculating the degree of influence of every store in a road network is time-consuming, we added two accelerating algorithms to the proposed baseline. The experiment results verified the validity of the proposed approach.<\/jats:p>","DOI":"10.3390\/ijgi11050314","type":"journal-article","created":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T13:06:23Z","timestamp":1652706383000},"page":"314","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Applying Check-in Data and User Profiles to Identify Optimal Store Locations in a Road Network"],"prefix":"10.3390","volume":"11","author":[{"given":"Yen-Hsun","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701401, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0353-7340","authenticated-orcid":false,"given":"Yi-Chung","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management, National Yunlin University of Science and Technology, Yunlin 640301, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheng-Min","family":"Chiu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701401, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chiang","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701401, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fu-Cheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering and Management, National Yunlin University of Science and Technology, Yunlin 640301, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,16]]},"reference":[{"key":"ref_1","unstructured":"Zhang, J., Ku, W.-S., Sun, M., Qin, X., and Lu, H. (April, January 29). Multi-criteria optimal location query with overlapping voronoi diagrams. Proceedings of the 17th International Conference on Extending Database Technology (EDBT), Edinburgh, UK."},{"key":"ref_2","unstructured":"Arvanitis, A., Deligiannakis, A., and Vassiliou, Y. (November, January 29). Efficient influence-based processing of market research queries. Proceedings of the 21st ACM International Conference on Information and Knowledge Management, Maui, HI, USA."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Xiao, X., Yao, B., and Li, F. (2011, January 11\u201316). Optimal location queries in road network databases. Proceedings of the 2011 IEEE 27th International Conference on Data Engineering, Washington, DC, USA.","DOI":"10.1109\/ICDE.2011.5767845"},{"key":"ref_4","unstructured":"Lee, C. (2015). Finding the k-Most Suitable Locations under Minimum Average Distance. [Master\u2019s Thesis, National Cheng-Kung University]."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Lin, Y., Wang, E.T., Chiang, C., and Chen, A.L.P. (2014, January 24\u201328). Finding targets with the nearest favor neighbor and farthest disfavor neighbor by a skyline query. Proceedings of the 29th Annual ACM Symposium on Applied Computing, Gyeongju, Korea.","DOI":"10.1145\/2554850.2554863"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sacharidis, D., and Deligiannakis, A. (2015, January 2\u20135). Spatial cohesion queries. Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, Beijing, China.","DOI":"10.1145\/2820783.2820834"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Qi, J., Zhang, R., Kulik, L., Lin, D., and Xue, Y. (2012, January 2\u20135). The min-dist location selection query. Proceedings of the 2012 IEEE 28th International Conference on Data Engineering, Arlington, VA, USA.","DOI":"10.1109\/ICDE.2012.45"},{"key":"ref_8","unstructured":"Su, I., Huang, Y., Chung, Y., and Shen, I. (2012, January 16\u201319). Finding both aggregate nearest positive and farthest negative neighbors. Proceedings of the International Conference on Information and Knowledge Engineering (IKE), Las Vegas, NV, USA."},{"key":"ref_9","unstructured":"(2022, February 17). Foursquare. Available online: https:\/\/foursquare.com\/."},{"key":"ref_10","unstructured":"(2022, February 17). Facebook. Available online: https:\/\/www.facebook.com\/."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Chen, Y.C., Huang, H.H., Chiu, S.M., and Lee, C. (2021). Joint Promotion Partner Recommendation Systems Using Data from Location-Based Social Networks. ISPRS Int. J. Geo-Inf., 10.","DOI":"10.3390\/ijgi10020057"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1287\/isre.2015.0617","article-title":"Research Note\u2014When Do Consumers Value Positive vs. Negative Reviews? An Empirical In-vestigation of Confirmation Bias in Online Word of Mouth","volume":"27","author":"Yin","year":"2016","journal-title":"Inf. Syst. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1007\/s12525-020-00416-5","article-title":"A personalized point-of-interest recommendation system for O2O commerce","volume":"31","author":"Kang","year":"2022","journal-title":"Electron. Mark."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Chen, Z., Liu, Y., Wong, R.C., Xiong, J., Mai, G., and Long, C. (2014, January 22\u201327). Efficient algorithms for optimal location queries in road networks. Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, Snowbird, UT, USA.","DOI":"10.1145\/2588555.2612172"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Xu, L., Mai, G., Chen, Z., Liu, Y., and Dai, G. (2017, January 27\u201330). Minsum based optimal location query in road networks. Proceedings of the International Conference on Database Systems for Advanced Applications, Suzhou, China.","DOI":"10.1007\/978-3-319-55699-4_27"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4933","DOI":"10.1007\/s10489-020-02035-1","article-title":"TBTF: An effective time-varying bias tensor factorization algorithm for recommender system","volume":"51","author":"Zhao","year":"2021","journal-title":"Appl. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Cui, L., and Wang, X. (2022). A Cascade Framework for Privacy-Preserving Point-of-Interest Recommender System. Electronics, 11.","DOI":"10.3390\/electronics11071153"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Galal, S., Nagy, N., and El-Sharkawi, M.E. (2021). CNMF: A Community-Based Fake News Mitigation Framework. Information, 12.","DOI":"10.3390\/info12090376"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Li, H., Hong, R., Zhu, S., and Ge, Y. (2015, January 14\u201317). Point-of-interest recommender systems: A separate-space perspective. Proceedings of the 2015 IEEE International Conference on Data Mining, Atlantic City, NJ, USA.","DOI":"10.1109\/ICDM.2015.27"},{"key":"ref_20","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, Redondo Beach, CA, USA.","DOI":"10.1145\/2424321.2424348"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Hsieh, H., Li, C., and Lin, S. (2012, January 16\u201320). Triprec: Recommending trip routes from large scale check-in data. Proceedings of the 21st International Conference on World Wide Web, Lyon, France.","DOI":"10.1145\/2187980.2188111"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lu, E.H., Chen, C., and Tseng, V.S. (2012, January 6\u20139). Personalized trip recommendation with multiple constraints by mining user check-in behaviors. Proceedings of the 20th International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, USA.","DOI":"10.1145\/2424321.2424349"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Wen, Y.T., Cho, K.J., Peng, W.C., Yeo, J., and Hwang, S.W. (2015, January 14\u201317). Kstr: Keyword-aware skyline travel route recommendation. Proceedings of the 2015 IEEE International Conference on Data Mining, Atlantic City, NJ, USA.","DOI":"10.1109\/ICDM.2015.37"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Wang, X., Zhang, Y., Zhang, W., and Lin, X. (2016, January 16\u201320). Distance-aware influence maximization in geo-social network. Proceedings of the IEEE 32nd International Conference on Data Engineering (ICDE), Helsinki, Finland.","DOI":"10.1109\/ICDE.2016.7498224"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Jin, X., and Han, J. (2017). Expectation maximization clustering. Encyclopedia of Machine Learning and Data Mining, Springer.","DOI":"10.1007\/978-1-4899-7687-1_344"},{"key":"ref_26","first-page":"547","article-title":"\u00c9tude comparative de la distribution florale dans une portion des Alpes et du Jura","volume":"37","author":"Jaccard","year":"1901","journal-title":"Bull. Soc. Vaud. Sci. Nat."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1858","DOI":"10.1109\/TIT.2003.813506","article-title":"A new metric for probability distributions","volume":"49","author":"Endres","year":"2003","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2175","DOI":"10.1109\/TKDE.2015.2399306","article-title":"G-tree: An efficient and scalable index for spatial search on road networks","volume":"27","author":"Zhong","year":"2015","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_29","unstructured":"(2022, February 17). Real Datasets for Spatial Databases: Road Networks and Points of Interest. Available online: https:\/\/www.cs.utah.edu\/~lifeifei\/SpatialDataset.htm."},{"key":"ref_30","unstructured":"(2019, January 14). OpenStreetMap Project. Available online: https:\/\/www.openstreetmap.org\/."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/5\/314\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:11:27Z","timestamp":1760137887000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/5\/314"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,16]]},"references-count":30,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["ijgi11050314"],"URL":"https:\/\/doi.org\/10.3390\/ijgi11050314","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2022,5,16]]}}}