{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T07:41:33Z","timestamp":1772696493443,"version":"3.50.1"},"reference-count":23,"publisher":"World Scientific Pub Co Pte Ltd","issue":"06","funder":[{"DOI":"10.13039\/501100018529","name":"Major Project of Philosophy and Social Science Research in Colleges and Universities of Jiangsu Province","doi-asserted-by":"publisher","award":["2022ND0331"],"award-info":[{"award-number":["2022ND0331"]}],"id":[{"id":"10.13039\/501100018529","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:p> With the rapid development of Internet technology, people can learn all kinds of travel information anytime and anywhere. However, the serious information overload causes travelers to be unable to make accurate and reasonable travel routes that meet tourists\u2019 tastes for a while, thus reducing the quality of travel. The recommendation system as the mainstream solution to the information explosion of two means has received the attention of the majority of scholars and industry. Based on the research theory of tourist route recommendation, this paper analyzes the characteristics of attractions, factors affecting travelers\u2019 travel experience when touring attractions and factors affecting travelers\u2019 travel experience along tourist routes. Furthermore, we propose a tourist route recommendation model that meets tourists\u2019 preferences. Then, this paper uses the graph neural network (GNN) algorithm to build a framework for tourist route recommendations based on the GNN using the relationship of preference and commonality existing among groups, tourists and attractions. The GNN algorithm is optimized and improved using multiple graphs and an attention mechanism. Finally, the effectiveness of this paper\u2019s algorithm is verified by conducting experiments on different data sets. <\/jats:p>","DOI":"10.1142\/s0218126623501025","type":"journal-article","created":{"date-parts":[[2022,9,25]],"date-time":"2022-09-25T14:11:06Z","timestamp":1664115066000},"source":"Crossref","is-referenced-by-count":9,"title":["Travelling Route Recommendation Method Based on Graph Neural Network for Improving Travel Experience"],"prefix":"10.1142","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2257-8810","authenticated-orcid":false,"given":"Lang","family":"Wang","sequence":"first","affiliation":[{"name":"School of Economics and Management, Xianyang Normal University, Xianyang, Shaanxi 712000, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2022,10,25]]},"reference":[{"key":"S0218126623501025BIB001","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1109\/TITS.2019.2897776","volume":"21","author":"Qu B.","year":"2019","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"S0218126623501025BIB002","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1007\/s00779-020-01476-2","volume":"26","author":"Park S. T.","year":"2020","journal-title":"Pers. Ubiquitous Comput."},{"key":"S0218126623501025BIB003","doi-asserted-by":"crossref","first-page":"3357","DOI":"10.3390\/su11123357","volume":"11","author":"Malik S.","year":"2019","journal-title":"Sustainability"},{"key":"S0218126623501025BIB004","doi-asserted-by":"crossref","first-page":"3551","DOI":"10.1007\/s12652-018-1081-z","volume":"10","author":"Du S.","year":"2019","journal-title":"J. Ambient Intell. Humanized Comput."},{"key":"S0218126623501025BIB005","doi-asserted-by":"crossref","first-page":"33365","DOI":"10.1007\/s11042-018-6776-9","volume":"79","author":"Hu G.","year":"2020","journal-title":"Multimedia Tools Appl."},{"key":"S0218126623501025BIB006","doi-asserted-by":"crossref","first-page":"90760","DOI":"10.1109\/ACCESS.2019.2926675","volume":"7","author":"Ahmad S.","year":"2019","journal-title":"IEEE Access"},{"key":"S0218126623501025BIB007","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.ins.2020.01.043","volume":"521","author":"Eng H.","year":"2020","journal-title":"Inf. Sci."},{"key":"S0218126623501025BIB008","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/s00521-018-3728-2","volume":"31","author":"Huang Z.","year":"2019","journal-title":"Neural Comput. Appl."},{"key":"S0218126623501025BIB009","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.trc.2020.01.010","volume":"112","author":"Bogaerts T.","year":"2020","journal-title":"Transp. Res. C, Emerg. Technol."},{"key":"S0218126623501025BIB010","doi-asserted-by":"crossref","first-page":"3301","DOI":"10.17762\/turcomat.v12i3.1581","volume":"12","author":"Sujawat G. S.","year":"2021","journal-title":"Turk. J. Comput. Math. Educ. (TURCOMAT)"},{"key":"S0218126623501025BIB011","doi-asserted-by":"crossref","first-page":"113240","DOI":"10.1016\/j.eswa.2020.113240","volume":"149","author":"Shahverdy M.","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"S0218126623501025BIB012","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1080\/17538947.2017.1326535","volume":"11","author":"Cui G.","year":"2018","journal-title":"Int. J. Digit. Earth"},{"key":"S0218126623501025BIB013","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13634-020-00710-6","volume":"2021","author":"Cheng X.","year":"2021","journal-title":"EURASIP J. Adv. Signal Process."},{"key":"S0218126623501025BIB014","doi-asserted-by":"crossref","first-page":"506","DOI":"10.3390\/electronics8050506","volume":"8","author":"Mehmood F.","year":"2019","journal-title":"Electronics"},{"key":"S0218126623501025BIB015","first-page":"328","volume":"38","author":"Xiaolu W.","year":"2021","journal-title":"Int. J. Ind. Syst. Eng."},{"key":"S0218126623501025BIB016","doi-asserted-by":"crossref","first-page":"342","DOI":"10.14778\/3430915.3430924","volume":"14","author":"Liu H.","year":"2020","journal-title":"Proc. VLDB Endowment"},{"key":"S0218126623501025BIB017","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.1007\/s10115-018-1297-4","volume":"60","author":"Lim K. H.","year":"2019","journal-title":"Knowl. Inf. Syst."},{"key":"S0218126623501025BIB018","doi-asserted-by":"crossref","first-page":"60588","DOI":"10.1109\/ACCESS.2021.3071274","volume":"9","author":"Asif N. A.","year":"2021","journal-title":"IEEE Access"},{"key":"S0218126623501025BIB019","first-page":"29476","volume":"34","author":"Zhu Z.","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"S0218126623501025BIB020","doi-asserted-by":"crossref","first-page":"179","DOI":"10.3390\/chemosensors10050179","volume":"10","author":"Shen X.","year":"2022","journal-title":"Chemosensors"},{"key":"S0218126623501025BIB021","doi-asserted-by":"crossref","first-page":"905583","DOI":"10.3389\/fbioe.2022.905583","volume":"10","author":"Shen X.","year":"2022","journal-title":"Front. Bioeng. Biotechnol."},{"key":"S0218126623501025BIB022","first-page":"9501811","volume":"70","author":"Shi G.","year":"2020","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"S0218126623501025BIB023","doi-asserted-by":"crossref","first-page":"106511","DOI":"10.1016\/j.knosys.2020.106511","volume":"211","author":"Zhu G.","year":"2021","journal-title":"Knowl.-Based Syst."}],"container-title":["Journal of Circuits, Systems and Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218126623501025","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T05:49:05Z","timestamp":1681796945000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S0218126623501025"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,25]]},"references-count":23,"journal-issue":{"issue":"06","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["10.1142\/S0218126623501025"],"URL":"https:\/\/doi.org\/10.1142\/s0218126623501025","relation":{},"ISSN":["0218-1266","1793-6454"],"issn-type":[{"value":"0218-1266","type":"print"},{"value":"1793-6454","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,25]]},"article-number":"2350102"}}