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Network Embedding-Aware Point-of-Interest Recommendation in Location-Based Social Networks
2019
Complexity
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., social and geographical information). ...
As one of the important techniques to explore unknown places for users, the methods that are proposed for point-of-interest (POI) recommendation have been widely studied in recent years. ...
of POI v from geographical relationships (D t is the dimension of T v ) and Y ∈ R d×D t is the weight matrix that transforms the learned POI representations from location network into the collaborative ...
doi:10.1155/2019/3574194
fatcat:yvdlqwr77jahlovqada6e2zs2e
A Geographical Factor of Interest Recommended Strategies in Location Based Social Networks
2018
International Journal of Engineering & Technology
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Contingent upon which sort of LBSNs records used to be completely used in buyer displaying forms for POI proposals, we separate client demonstrating calculations into four classifications: pure check-in ...
This paper centers on evaluating the scientific classification of client displaying for POI proposals through the information investigation of LBSNs. ...
proposed a personalized ranking metric that embeds a model for the next new POI recommendation. ...
doi:10.14419/ijet.v7i3.27.17649
fatcat:xbhdedvfkbe6tgacryx7fbwyke
Points-of-interest Recommendation Algorithm Based on LBSN in Edge Computing Environment
2020
IEEE Access
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Then interact with the geographic information stored in the Cloud to cluster the POIs. And embeds the geographic information into the framework to get the candidate points of interest. ...
This algorithm effectively integrates the time information and geographic information of users' check-in in the LBSN, and proposes a POIs recommendation algorithm that comprehensively considers edge devices ...
[7] integrated geographical influence, user preference and social influence into collaborative filtering recommendation, and designed a check-in probability prediction model for a given user's access ...
doi:10.1109/access.2020.2979922
fatcat:zaacjuvo35hohceprw54xsqnoq
An Attention-Based Spatiotemporal Gated Recurrent Unit Network for Point-of-Interest Recommendation
2019
ISPRS International Journal of Geo-Information
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Point-of-interest (POI) recommendation is one of the fundamental tasks for location-based social networks (LBSNs). ...
We first designed a novel variant of GRU, which acquired the user's sequential preference and spatiotemporal preference by feeding the continuous geographical distance and time interval information into ...
[35] proposed a ranking based geographical factorization method, which exploits both geographical and temporal contexts for POI recommendation. ...
doi:10.3390/ijgi8080355
fatcat:bwj5scixkjenhkbm6sparmgnjq
Research on Personalized Minority Tourist Route Recommendation Algorithm Based on Deep Learning
2022
Scientific Programming
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significantly higher than other POI recommendation methods in terms of the accuracy or recall rate of the recommendation algorithm. ...
Among them, the accuracy rates of the top five, top ten, and top twenty recommended POIs are increased by 9.9%, 7.4%, and 7%, respectively, and the recall rate is increased by 4.2%, 7.5%, and 14.4%, respectively ...
POI that is close to his frequent area. erefore, geographic factor features can be integrated into the personalized recommendation model, and the user's preference for POI in different geographic locations ...
doi:10.1155/2022/8063652
fatcat:673kpgz2dbh4thmmnhxwoepdw4
User Data Driven Recommendation for Location
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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users. complicated methodology is to convey them into explicit- feedback- based mostly content-aware (cf)collaborative filtering, however they have to draw negative attributes for higher learning performance ...
Final performance show that ICCF outperforms many different competitory baselines,so that user attribute info isn't solely effective for up recommendations however additionally addressing initial knowledge ...
The effectiveness from the projected distributed and rank one constant plans has been widely estimated, showing its very important profit for rising recommendation, in particular for locations at rich ...
doi:10.35940/ijitee.k1223.09811s19
fatcat:7x7cnyn6xfe6vfommyr2zicy4y
On the effects of aggregation strategies for different groups of users in venue recommendation
2021
Information Processing & Management
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In this context, we categorize users into two different groups (tourists and locals) according to their movement patterns and analyze the potential biases in the recommendations received by each of these ...
In this paper, we address the problem of venue recommendation from a novel perspective: we propose two strategies to select a set of candidate cities in order to use their information when performing recommendations ...
Acknowledgments This work has been co-funded by the European Social Fund (ESF) within the 2017 call for predoctoral contracts, the Ministerio de ...
doi:10.1016/j.ipm.2021.102609
fatcat:5kdcze476zhx3eke7kij6stcui
Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence
[article]
2018
arXiv
pre-print
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; (2) the difficulty of incorporating context information such as POIs' geographical coordinates. ...
The rapid growth of Location-based Social Networks (LBSNs) provides a great opportunity to satisfy the strong demand for personalized Point-of-Interest (POI) recommendation services. ...
The reason is that DeepAE does not adopt the geographical information which is distinct for POI recommendation. ...
arXiv:1809.10770v1
fatcat:4jbtumufrfbefc436kzqxufeku
Point-of-interest lists and their potential in recommendation systems
2021
Information Technology & Tourism
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Our hypothesis is that the information encoded in the lists can be utilized to estimate the similarities amongst POIs and, hence, these similarities can drive a personalized recommendation system or enhance ...
The results confirm the existence of rich similarity information within the lists and the effectiveness of our approach as a recommendation system. ...
We would also like to thank the anonymous reviewers who helped us improve our work, and especially for suggesting the offline experiment of Section 5.3. ...
doi:10.1007/s40558-021-00195-5
fatcat:z26fhtad7fhvvgok7hpu7umage
Recommendation of Heterogeneous Cultural Heritage Objects for the Promotion of Tourism
2019
ISPRS International Journal of Geo-Information
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This itinerary recommendation approach is original in many aspects: it not only considers the user preferences and popularity of POIs, but it also integrates different contextual information about the ...
The ability to export the cultural heritage data as open data and to recommend sequences of POIs are being integrated in a first prototype. ...
The advantage of collaborative filtering approaches is that they allow the recommendation of POIs without requiring specific information about them. ...
doi:10.3390/ijgi8050230
fatcat:xg75hw2jcjbodnobogcrpfj7kq
A Graph-Based Taxonomy of Recommendation Algorithms and Systems in LBSNs
2016
IEEE Transactions on Knowledge and Data Engineering
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Recommender systems can exploit this geographic information to provide much more accurate and reliable recommendations to users. ...
Moreover, we describe and compare extensively 43 state-of-the-art recommendation algorithms for LBSNs. ...
influence from POIs ðGÞ) combined linearly in a unified collaborative algorithm to recommend locations. ...
doi:10.1109/tkde.2015.2496344
fatcat:6gikvhjovvaj5dqvsu7tqvayu4
Computer Highlights Society Magazines
2021
Computer
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a user's geographical and diversity preferences for POI recommendation. ...
One challenge in POI recommendation is effectively exploiting geographical information since users usually care about the physical distance to the recommended POIs. ...
doi:10.1109/mc.2020.3038510
fatcat:xz3u2qnsongczn2r6iafzlk7xm
Personalized Next Point-of-Interest Recommendation via Latent Behavior Patterns Inference
[article]
2018
arXiv
pre-print
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By integrating categorical influence into mobility patterns and aggregating user's spatial preference on a POI, the proposed model deal with the next new POI recommendation problem by nature. ...
In this paper, we address the problem of personalized next Point-of-interest (POI) recommendation which has become an important and very challenging task for location-based social networks (LBSNs), but ...
[6] adopt linear interpolation to incorporate both social and geographical influences into the user-based CF framework for POI recommendation. ...
arXiv:1805.06316v1
fatcat:ns4r7irijjet5fk3sg7w5iexgu
Collaborative location and activity recommendations with GPS history data
2010
Proceedings of the 19th international conference on World wide web - WWW '10
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By using our system, for the first question, we can recommend her to visit a list of interesting locations such as Tiananmen Square, Bird's Nest, etc. ...
recommendations. ...
The authors would like to thank Yukun Chen for his great help in data processing. The authors would also thank the reviewers for their helpful comments and suggestions. ...
doi:10.1145/1772690.1772795
dblp:conf/www/ZhengZXY10
fatcat:kmtlalp5snghvjtlze3pjy2i54
LCARS
2014
ACM Transactions on Information Systems
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The results show the superiority of LCARS in recommending spatial items for users, especially when traveling to new cities, in terms of both effectiveness and efficiency. ...
The problem becomes even more challenging when people travel to a new city where they have no activity information. ...
The results also justify each component proposed in our system, for instance, taking into account of local preference and item content information. ...
doi:10.1145/2629461
fatcat:cwx5ozfuk5ff5mhakid4d5qjsi
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