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Personalized Context-Aware Point of Interest Recommendation [article]

Mohammad Aliannejadi, Fabio Crestani
2018 arXiv   pre-print
Personalized recommendation of Points of Interest (POIs) plays a key role in satisfying users on Location-Based Social Networks (LBSNs).  ...  We investigate four approaches to use our proposed mapping for addressing the data sparsity problem: one model to reduce the dimensionality of location taste keywords and three models to predict user tags  ...  For UT-ML, instead of the keyword boosting score (S boost ), we use the score based on the predicted user tags following maximum likelihood criterion.  ... 
arXiv:1806.05736v1 fatcat:lblylvjqpbh2vlppf55s5alssi

GeoSRS: A hybrid social recommender system for geolocated data

Joan Capdevila, Marta Arias, Argimiro Arratia
2016 Information Systems  
We present GeoSRS, a hybrid recommender system for a popular locationbased social network (LBSN), in which users are able to write short reviews on the places of interest they visit.  ...  Finally, we study the performance of GeoSRS on our collected dataset and conclude that by combining sentiment analysis and text modelling, GeoSRS generates more accurate recommendations.  ...  A good deal of researchers have been combining multiple recommendation techniques to boost the performance of the so-called hybrid systems (Burke, 2002) .  ... 
doi:10.1016/ fatcat:7taan6vfwrhjhp3jm7pz72wpta

Context-Aware Recommender Systems for Social Networks: Review, Challenges and Opportunities

Areej Bin Suhaim, Jawad Berri
2021 IEEE Access  
The paper presents the detail of the review study, provides a synthesis of the results, proposes an evaluation based on measurable evaluation tools developed in this study, and advocates future research  ...  In this research, we present a comprehensive review of context-aware recommender systems developed for social networks.  ...  The authors are grateful for this support.  ... 
doi:10.1109/access.2021.3072165 fatcat:i3igbxd44jhrzcyvynevpidcwq

Harnessing the Power of the General Public for Crowdsourced Business Intelligence: A Survey

Bin Guo, Yan Liu, Yi Ouyang, Vincent W. Zheng, Daqing Zhang, Zhiwen Yu
2019 IEEE Access  
Compared with the traditional business intelligence that is based on the firm-owned data and survey data, CrowdBI faces numerous unique issues, such as customer behavior analysis, brand tracking, and product  ...  This paper first characterizes the concept model and unique features and presents a generic framework for CrowdBI.  ...  Recognizing the business venue (e.g. cafe shops, local restaurants) in an image can help many applications for personalization and location-based services/marketing. Chen et al.  ... 
doi:10.1109/access.2019.2901027 fatcat:a5vz6vl7urckpdsreplkvjalea

Regularity and Conformity

Yingzi Wang, Nicholas Jing Yuan, Defu Lian, Linli Xu, Xing Xie, Enhong Chen, Yong Rui
2015 Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15  
We group the columns of the hub matrix H in the same way as suggests the necessity to use heterogeneous data for learning the Q∗ , based on the group structure learned from Sec 3.2 to obtain  ...  and predict movement across multiple users. Personal and [23] A. Monreale, F. Pinelli, R. Trasarti, and F. Giannotti.  ... 
doi:10.1145/2783258.2783350 dblp:conf/kdd/WangYLXXCR15 fatcat:er7kf2hiv5etncxlq4xzq23spi

Transport-domain applications of widely used data sources in the smart transportation: A survey [article]

Sina Dabiri, Kevin Heaslip
2018 arXiv   pre-print
categorized into: 1) traffic flow sensors, 2) video image processors, 3) probe people and vehicles based on Global Positioning Systems (GPS), mobile phone cellular networks, and Bluetooth, 4) location-based  ...  social networks, 5) transit data with the focus on smart cards, and 6) environmental data.  ...  While the former criterion measures the closeness of venues to each other, the latter one is the social similarity between each pair of venues based on the number of times a venue is visited (128) .  ... 
arXiv:1803.10902v3 fatcat:tc67qy4x4vbtjb76qi6mbwrqy4

Do your friends make you buy this brand?

Minh-Duc Luu, Ee-Peng Lim
2017 Data mining and knowledge discovery  
The former refers to user preference for each brand, the latter refers to the extent to which a user relies on brand to make her adoption decisions.  ...  Specifically, both SocBIT and SocBIT + offer an improvement of at least 22% over these state-of-the-art models in rating prediction for various realworld datasets.  ...  Dataset from FourSquare (4SQDB) FourSquare is a popular location-based social network (LBSN) which allows users and venues to interact with one another.  ... 
doi:10.1007/s10618-017-0535-9 fatcat:dvvpnhrhgnbs3f6m4aahxro3om

Crowdsourced Data Mining for Urban Activity: Review of Data Sources, Applications, and Methods

Haifeng Niu, Elisabete A. Silva
2020 Journal of urban planning and development  
Dev., 2020, 146(2): 04020007 Downloaded from by Cambridge University on 01/21/21. Copyright ASCE. For personal use only; all rights reserved.  ...  Dev., 2020, 146(2): 04020007 Downloaded from by Cambridge University on 01/21/21. Copyright ASCE. For personal use only; all rights reserved. © ASCE 04020007-3 J. Urban Plann. Dev.  ...  We thank the anonymous reviewers for their many insightful comments and suggestions.  ... 
doi:10.1061/(asce)up.1943-5444.0000566 fatcat:vec2lz2olbfbjoem2lfnulzswi

A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial Networks [article]

Yashar Deldjoo and Tommaso Di Noia and Felice Antonio Merra
2020 arXiv   pre-print
This review serves as a reference for the RS community, working on the security of RS or on generative models using GANs to improve their quality.  ...  Latent-factor models (LFM) based on collaborative filtering (CF), such as matrix factorization (MF) and deep CF methods, are widely used in modern recommender systems (RS) due to their excellent performance  ...  or bundle recommendations for items from multiple domains [17] .  ... 
arXiv:2005.10322v2 fatcat:4wqcluqgnbbwpkicunn42et5te

(So) Big Data and the transformation of the city

Gennady Andrienko, Natalia Andrienko, Chiara Boldrini, Guido Caldarelli, Paolo Cintia, Stefano Cresci, Angelo Facchini, Fosca Giannotti, Aristides Gionis, Riccardo Guidotti, Michael Mathioudakis, Cristina Ioana Muntean (+6 others)
2020 International Journal of Data Science and Analytics  
In this paper, we provide a wide perspective on the role that big data have in reshaping cities.  ...  The paper covers the main aspects of urban data analytics, focusing on privacy issues, algorithms, applications and services, and georeferenced data from social media.  ...  For this analysis, the tweets were classified according to their topics, such as family, work, education, food, and sports, based on the occurrences of topic-specific keywords.  ... 
doi:10.1007/s41060-020-00207-3 fatcat:k4eh5k2epjblzf6myc7tiw5gam

A survey of Big Data dimensions vs Social Networks analysis

Michele Ianni, Elio Masciari, Giancarlo Sperlí
2020 Journal of Intelligent Information Systems  
This survey will focus on the analyses performed in last two decades on these kind of data w.r.t. the dimensions defined for Big Data paradigm (the so called Big Data 6 V's).  ...  Thus, traditional approaches quickly became unpractical for real life applications due their intrinsic properties: large amount of user-generated data (text, video, image and audio), data heterogeneity  ...  In the authors propose a context-aware user preferences prediction algorithm for location recommendation on LBSNs, using a dataset from Foursquare.  ... 
doi:10.1007/s10844-020-00629-2 pmid:33191981 pmcid:PMC7649712 fatcat:3hvd5sshwzd67lxi4qlo2sgnwe

Research Commentary on Recommendations with Side Information: A Survey and Research Directions [article]

Zhu Sun, Qing Guo, Jie Yang, Hui Fang, Guibing Guo, Jie Zhang, Robin Burke
2019 arXiv   pre-print
One involves the different methodologies of recommendation: the memory-based methods, latent factor, representation learning, and deep learning models.  ...  This Research Commentary aims to provide a comprehensive and systematic survey of the recent research on recommender systems with side information.  ...  ACKNOWLEDGEMENTS This work was partly conducted within the Delta-NTU Corporate Lab for Cyber-Physical Systems with funding support from Delta Electronics Inc. and the National Research Foundation (NRF)  ... 
arXiv:1909.12807v2 fatcat:2nj4crzcd5attidhd3kneszmki

Recommendation models for dynamic spatiotemporal big data

Παύλος Φ. Κεφαλάς
This research area is called recommendation systems and focuses on modelling and analyzing data in order to retrieve relevant information based on users' preferences and to suggest some new alternatives  ...  To over come this problem many researchers focused on creating models that provide personalized recommendation in order to assist users making choices.  ...  On the other hand, personalized recommendations are based on the users’ profile such as log history, friend’s suggestions etc.  ... 
doi:10.26262/ fatcat:7hfpfcz5bvchlmoxon2ntcozeu

Modeling and Multiple Perceptions [chapter]

Christine Parent, Stefano Spaccapietra, Esteban Zimányi
2017 Encyclopedia of GIS  
Modeling with Pictogrammic Languages OGC's Open Standards for Geospatial Interoperability Vector Data Cross-References Indexing, Query and Velocity-Constrained Privacy Threats in Location-Based Services  ...  processes and for contributing to our research.  ...  Increasingly, the producer is not the user: Most geospatial data is used multiple times, perhaps by more than one person.  ... 
doi:10.1007/978-3-319-17885-1_805 fatcat:d4t4ossygvcutpfabqn6f3hjcm

GEOProcessing 2016 Committee GEOProcessing Advisory Committee

Monica De Martino, Consiglio Nazionale Delle Ricerche -Genova, Claus-Peter Rückemann, Monica De Martino, Consiglio Nazionale Delle Ricerche -Genova, Claus-Peter Rückemann, Zaher Al Aghbari, Mirko Albani, Riccardo Albertoni, Imati-Cnr, Italy Francesc, Antón Castro (+69 others)
2016 unpublished
Geographical sensors and satellites provide a huge volume of spatial data which is available on the Web.  ...  Making use of Web Services, the users are able for provisioning and using these services instead of only for document searching.  ...  ACKNOWLEDGMENT The research was funded through the ARC grant for Concerted Research Actions and through the Special Fund for Research, both financed by the Wallonia-Brussels Federation.  ... 
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