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Context-Aware Attention-Based Data Augmentation for POI Recommendation

Yang Li, Yadan Luo, Zheng Zhang, Shazia Sadiq, Peng Cui
2019 2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW)  
Recently, the next POI recommendation, a natural extension of POI recommendation, has attracted much attention.  ...  In this paper, we propose an attention-based sequence-to-sequence generative model, namely POI-Augmentation Seq2Seq (PA-Seq2Seq), to address the sparsity of training set by making check-in records to be  ...  To the best of our knowledge, this is the first study on data augmentation for next POI recommendation task.  ... 
doi:10.1109/icdew.2019.00-14 dblp:conf/icde/LiLZSC19 fatcat:oaanmu64wng57mhhqmt3nf6ykm

Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentation [article]

Yang Li, Tong Chen, Yadan Luo, Hongzhi Yin, Zi Huang
2022 arXiv   pre-print
Being an indispensable component in location-based social networks, next point-of-interest (POI) recommendation recommends users unexplored POIs based on their recent visiting histories.  ...  Furthermore, the sparse POI-POI transitions restrict the ability of a model to learn effective sequential patterns for recommendation.  ...  In SGRec, we first build a category-aware graph attention layer, which embeds every POI in the sequence by merging the contexts from its neighbour POI nodes.  ... 
arXiv:2106.15814v2 fatcat:apyhlu3hkfdgtmtqelamu4ypei

Self-supervised Representation Learning for Trip Recommendation [article]

Qiang Gao, Wei Wang, Kunpeng Zhang, Xin Yang, Congcong Miao
2021 arXiv   pre-print
They even provide recommendations that deviate from tourists' real travel intention when the trip data is sparse.  ...  Trip recommendation is a significant and engaging location-based service that can help new tourists make more customized travel plans.  ...  Accordingly, the self-supervised POI learning is proposed to formulate the context-aware POI representation. • We design four data augmentation strategies to mimic human travel behaviors based on the sparse  ... 
arXiv:2109.00968v2 fatcat:lkuwvghvwzb5tp3nzxnqi5k4y4

A Survey on Deep Learning Based Point-Of-Interest (POI) Recommendations [article]

Md. Ashraful Islam, Mir Mahathir Mohammad, Sarkar Snigdha Sarathi Das, Mohammed Eunus Ali
2020 arXiv   pre-print
This review can be considered a cookbook for researchers or practitioners working in the area of POI recommendation.  ...  Huge volume of data generated from LBSNs opens up a new avenue of research that gives birth to a new sub-field of recommendation systems, known as Point-of-Interest (POI) recommendation.  ...  check-in information by using spatial-aware memory-augmented LSTM with timeaware attention  ... 
arXiv:2011.10187v1 fatcat:3uampnqerfdvnpuzrxcrsjviwq

GARG: Anonymous Recommendation of Point-of-Interest in Mobile Networks by Graph Convolution Network

Shiwen Wu, Yuanxing Zhang, Chengliang Gao, Kaigui Bian, Bin Cui
2020 Data Science and Engineering  
To cope with the challenge, we propose a novel attentive model to recommend appropriate new POIs for users, namely Geographical Attentive Recommendation via Graph (GARG), which takes full advantage of  ...  One core issue for the industry to exploit the economic interest of the LBSs is to make appropriate pointof-interest (POI) recommendation based on users' interests.  ...  Anonymous Recommendation of POI by GARG Based on the three observations in Sect. 3, we introduce a novel recommender system, named Geographical Attentive Recommendation via Graph (GARG) for addressing  ... 
doi:10.1007/s41019-020-00135-z fatcat:qlo77xrwdzbknfvqco5qjxwcdy

Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction

Mengyue Hang, Ian Pytlarz, Jennifer Neville
2018 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '18  
We propose a heterogeneous graph-based method to encode the correlations between users, POIs, and activities, and then jointly learn embeddings for the vertices.  ...  This not only limits our understanding of users' daily routines, but more importantly the modeling assumptions developed based on characteristics of recreation-based data may not be suitable for richer  ...  Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation hereon.  ... 
doi:10.1145/3219819.3219902 dblp:conf/kdd/HangPN18 fatcat:otcygqdcerffhlzagaxgtm23qe

Mobile recommender systems in tourism

Damianos Gavalas, Charalampos Konstantopoulos, Konstantinos Mastakas, Grammati Pantziou
2014 Journal of Network and Computer Applications  
Hence, MTRS captures context-aware user evaluations and ratings and uses such data to provide recommendations to other users with similar interests, using a collaborative filtering-based RS engine.  ...  Barranco et al. (2012) proposed a context-aware system for mobile devices that incorporates the user's location, trajectory and speed (while driving) to personalize POIs recommendations.  ... 
doi:10.1016/j.jnca.2013.04.006 fatcat:k7ks4oftvbai7ctmy6h7iltgfa

Embedding Taxonomical, Situational or Sequential Knowledge Graph Context for Recommendation Tasks [chapter]

Simon Werner, Achim Rettinger, Lavdim Halilaj, Jürgen Lüttin
2021 Applications and Practices in Ontology Design, Extraction, and Reasoning  
In this paper, we investigate how well state-of-the-art approaches do exploit those different dimensions relevant to POI recommendation tasks.  ...  This is a fundamentally limiting restriction for many tasks and applications, since the latent state can depend on a) abstract background information, b) the current situational context and c) the history  ...  • We evaluate these methods on a context aware POI recommendation task to gain insights for the individual benefits of the dimensions to the recommendation performance.  ... 
doi:10.3233/ssw210046 fatcat:rfsad4zo7zhybdjloyor4zjczu

Demystifying the design of mobile augmented reality applications

Panos E. Kourouthanassis, Costas Boletsis, George Lekakos
2013 Multimedia tools and applications  
This research proposes a set of interaction design principles for the development of mobile augmented reality (MAR) applications.  ...  The design recommendations adopt a user-centered perspective and, thus, they focus on the necessary actions to ensure high-quality MAR user experiences.  ...  •No preferences, recommendations or any other data would be going public in the non-personalized version; POIs' recommendations would be publicly available to users of the same cluster in the personalized  ... 
doi:10.1007/s11042-013-1710-7 fatcat:5cmh2avpmvfw5bnbvhi5yrsf6m

Incorporating Geo-Tagged Mobile Videos into Context-Aware Augmented Reality Applications

Hien To, Hyerim Park, Seon Ho Kim, Cyrus Shahabi
2016 2016 IEEE Second International Conference on Multimedia Big Data (BigMM)  
In this study, we propose an approach to search and filter big multimedia data, specifically geo-tagged mobile videos, for context-aware AR applications.  ...  In recent years, augmented-reality (AR) has been attracting extensive attentions from both the research community and industry as a new form of media, mixing virtual content into the physical world.  ...  For developing AR as a new media, it is essential to provide rich content, based on context-aware filtering system.  ... 
doi:10.1109/bigmm.2016.64 dblp:conf/bigmm/ToPKS16 fatcat:thj7cqjsavd4hpugmcgju65uky

OUTMedia – Symbiotic Service for Music Discovery in Urban Augmented Reality [chapter]

Pirkka Åman, Lassi A. Liikkanen, Giulio Jacucci, Atte Hinkka
2014 Lecture Notes in Computer Science  
Our findings call for service designers to support the symbiotic interplay between media and places for enriching urban cultural experiences with user-created content.  ...  The rise of the mobile Internet has led to emergence of location-based services, but not to commercial breakthroughs in media applications.  ...  We also presented design insights based on user data for how to design location-based mobile AR services.  ... 
doi:10.1007/978-3-319-13500-7_5 fatcat:kquwfgzdorfr3p3vouvweqmnmy

Location Regularization-Based POI Recommendation in Location-Based Social Networks

Lei Guo, Haoran Jiang, Xinhua Wang
2018 Information  
To be specific, the weighted Bayesian framework that was proposed for personalized ranking is first introduced as our basic POI recommendation method.  ...  Although the methods that exploit geographical information for POI recommendation have been studied, few of these studies have addressed the implicit feedback problem.  ...  Other Context Aware POI Recommendation Except the geographical information, other types of contexts have also been explored [19] [20] [21] [22] , such as temporal influence, social influence, etc.  ... 
doi:10.3390/info9040085 fatcat:s2yel2kdsvf33blmwnxvmb7ehy

Smart tourism: State of the art and literature review for the last six years

Aristea Kontogianni, Efthimios Alepis
2020 Array  
In this study, "key concepts" include: Privacy Preserving, Context Awareness, Cultural Heritage, Recommender Systems, Social Media, Internet of Things, User Experience, Real Time, User Modeling, Augmented  ...  Reality and Big Data.  ...  In particular, a case study is presented of a context-aware recommendation system named TreSight that integrates IoT and big data analytics for Smart Tourism and sustainable cultural heritage in the city  ... 
doi:10.1016/j.array.2020.100020 fatcat:isv7axev7fdz3n7hfx3jsv67aa

On the effects of aggregation strategies for different groups of users in venue recommendation

Pablo Sánchez, Alejandro Bellogín
2021 Information Processing & Management  
We provide an experimental comparison of several recommendation algorithms in a temporal split, where we analyze two strategies to select cities and augment the available data: based on the number of interactions  ...  for the users in a specific (target) city.  ...  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

Want a coffee?

Wen Li, Carsten Eickhoff, Arjen P. de Vries
2012 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12  
This grants an opportunity for better understanding users' physical locations which can be used as context to facilitate other applications, e.g., location contextaware advertisement.  ...  The results from the preliminary experiments show promising performance of a basic Markov Chain-based model.  ...  The method can also be easily integrated into applications on mobile devices which may facilitate a location recommendation or context-aware advertising.  ... 
doi:10.1145/2348283.2348524 dblp:conf/sigir/LiEV12 fatcat:wqryqu4lljhczhr6tec72myvha
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