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Interactive Probabilistic Post-Mining of User-Preferred Spatial Co-Location Patterns

Lizhen Wang, Xuguang Bao, Longbing Cao
2018 2018 IEEE 34th International Conference on Data Engineering (ICDE)  
We first introduce a framework of interactively post-mining preferred co-location patterns, which enables a user to effectively discover the co-location patterns tailored to his/her specific preference  ...  To satisfy user preferences, this work proposes an interactive probabilistic post-mining method to discover user-preferred colocation patterns from the early-round of mined results by iteratively involving  ...  Problem Statement The problem of post-mining preferred spatial co-location patterns through interactive feedback can be stated as follows.  ... 
doi:10.1109/icde.2018.00124 dblp:conf/icde/WangBC18 fatcat:rwm4grjp7nf65mkdaoetfaxojm

Geo-Social Co-location Mining

Michael Weiler, Klaus Arthur Schmid, Nikos Mamoulis, Matthias Renz
2015 Second International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data - GeoRich'15  
For this purpose, we propose a probabilistic model to estimate the probability of a user to be located at a given location at a given time, creating the notion of probabilistic co-locations.  ...  The second sub-problem of mining the resulting probabilistic co-location instances requires efficient for large databases having a high degree of uncertainty.  ...  Figure 2 : 2 Workflow of probabilistic spatial co-location mining.  ... 
doi:10.1145/2786006.2786010 dblp:conf/sigmod/WeilerSMR15 fatcat:nqf3glfrtjcrlfinsp3axceefe

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  
It also investigates novel application areas as well as the key challenges and techniques of CrowdBI. Furthermore, we make discussions about the future research directions of CrowdBI.  ...  Social media data contains a lot of user-generated content, such as text posts or comments, images or videos, and users' interactions.  ...  contain valuable information of customers in business, include customer profile, customer preferences, mobility patterns, social relationship, interaction patterns, and so on.  ... 
doi:10.1109/access.2019.2901027 fatcat:a5vz6vl7urckpdsreplkvjalea

Finding suitable places for live campaigns using location-based services

Md. Khaledur Rahman, Muhammad Ali Nayeem
2017 Proceedings of the Fourth International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data - GeoRich '17  
We study the predictive power of various spatio-temporal mining features on the capability of gathering audience through the use of a dataset collected from Foursquare of New York City.  ...  In this paper, we address the challenge of nding a suitable location from online location based services for arranging a live campaign according to given schedule among a set of candidate locations.  ...  They evaluate a diverse set of data mining features, modeling spatial and semantic information about places and patterns of user movements in the surrounding area.  ... 
doi:10.1145/3080546.3080630 dblp:conf/sigmod/RahmanN17 fatcat:vhqvp3ef5nddbknso6xbvyv7la

Recommendations in location-based social networks: a survey

Jie Bao, Yu Zheng, David Wilkie, Mohamed Mokbel
2015 Geoinformatica  
This addition of vast geo-spatial datasets has stimulated research into novel recommender systems that seek to facilitate users' travels and social interactions.  ...  Location data bridges the gap between the physical and digital worlds and enables a deeper understanding of users' preferences and behavior.  ...  Similarity inference between users (and locations etc.) can also be done by analyzing the pattern of location co-visitation.  ... 
doi:10.1007/s10707-014-0220-8 fatcat:3ivmtrnvkfhshl72gd33h4aola

Public checkins versus private queries

James Caverlee, Zhiyuan Cheng, Wai Gen Yee, Roger Liew, Yuan Liang
2012 Proceedings of the 5th International Workshop on Location-Based Social Networks - LBSN '12  
However, traditional sources of spatial preference -which reflect the patterns of geo-spatial interest of large numbers of users -have typically been expensive to collect, proprietary, and unavailable  ...  Understanding the spatial preference of mobile and web users is of great significance to creating and improving location-based recommendation systems, travel planners, search engines, and other emerging  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.  ... 
doi:10.1145/2442796.2442806 dblp:conf/gis/CaverleeCYLL12 fatcat:zitow3g7qzgmxl3ug652e6iuqu

A Graph-Based Taxonomy of Recommendation Algorithms and Systems in LBSNs

Pavlos Kefalas, Panagiotis Symeonidis, Yannis Manolopoulos
2016 IEEE Transactions on Knowledge and Data Engineering  
Recently, location-based social networks (LBSNs) gave the opportunity to users to share geo-tagged information along with photos, videos, and SMSs.  ...  Index Terms-Recommender systems, location-based recommendations Ç The authors are with the  ...  Other Approaches Hu and Ester [16] proposed a spatial model to capture the spatial (textual) perspectives of a post and to be able to predict future user's locations.  ... 
doi:10.1109/tkde.2015.2496344 fatcat:6gikvhjovvaj5dqvsu7tqvayu4

Internet of Things-based student performance evaluation framework

Prabal Verma, Sandeep K. Sood
2017 Behavior and Information Technology  
The system deduces important results about the performance of the students by discovering daily spatial-temporal patterns.  ...  These patterns are based on the data collected by the sensory nodes (objects) in the institution learning environment.  ...  Co-location pattern mining from spatial datasets To retrieve the requisite information from spatial patterns of IoT devices, we can apply spatial-co-location mining technique.  ... 
doi:10.1080/0144929x.2017.1407824 fatcat:zqiv6nmhdfekzgaga24juumooy

A Survey of Context-Aware Recommendation Schemes in Event-Based Social Networks

Xiaomei Huang, Guoqiong Liao, Naixue Xiong, Athanasios V. Vasilakos, Tianming Lan
2020 Electronics  
., sharing comments and photos), but also promote face-to-face offline social interactions.  ...  To provide better service for users, Context-Aware Recommender Systems (CARS) in EBSNs have recently been singled out as a fascinating area of research.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/electronics9101583 fatcat:hdapa7y4vfcefcprlngjnjn5ai

Analyzing multimodal time series as dynamical systems

Shohei Hidaka, Chen Yu
2010 International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction on - ICMI-MLMI '10  
interactions.  ...  In light this, our approach is based on the concept of generating partition which is the theoretically best symbolization of time series maximizing the information of the underlying original continuous  ...  This research is supported by NSF BCS 0924248, AFOSR FA9550-09-1-0665 and The Ogasawara Foundation for the Promotion of Science and Emgineering.  ... 
doi:10.1145/1891903.1891968 dblp:conf/icmi/HidakaY10 fatcat:5df37633f5h6zgzn527jezbhjm

Using VGI and Social Media Data to Understand Urban Green Space: A Narrative Literature Review

Nan Cui, Nick Malleson, Victoria Houlden, Alexis Comber
2021 ISPRS International Journal of Geo-Information  
In addition, analysis approaches can be extended to examine the network suggested by social media posts that are shared, re-posted or reacted to and by being combined with textual, image and geographical  ...  The current state of the art is described through the analysis of 177 papers to (1) summarise the characteristics and usage of data from different platforms, (2) provide an overview of the research topics  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijgi10070425 fatcat:lu7ovue34new3ayrex3kn3p44a

A General Geographical Probabilistic Factor Model for Point of Interest Recommendation

Bin Liu, Hui Xiong, Spiros Papadimitriou, Yanjie Fu, Zijun Yao
2015 IEEE Transactions on Knowledge and Data Engineering  
Index Terms-Recommender systems, point of interest (POI), probabilistic factor model, location-based social networks The authors are with the  ...  The decision process for a user to choose a POI is complex and can be influenced by numerous factors, such as personal preferences, geographical considerations, and user mobility behaviors.  ...  ACKNOWLEDGMENTS This is a extended and revised version of [23] , which appears in the Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2013).  ... 
doi:10.1109/tkde.2014.2362525 fatcat:5eyarpctt5fwplbcdkeilr3mpq

Spatial topic modeling in online social media for location recommendation

Bo Hu, Martin Ester
2013 Proceedings of the 7th ACM conference on Recommender systems - RecSys '13  
Mobile networks enable users to post on social media services (e.g., Twitter) from anywhere. The activities of mobile users involve three major entities: user, post, and location.  ...  We propose the first ST (Spatial Topic) model to capture the correlation between users' movements and between user interests and the function of locations.  ...  In recommender systems, [20, 2, 13] have proposed probabilistic matrix factorization models mining latent user and location preferences to predict user locations, but they totally ignore one of the key  ... 
doi:10.1145/2507157.2507174 dblp:conf/recsys/HuE13 fatcat:rt4dc447wbha3ayklbjgdkpcxa

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

Areej Bin Suhaim, Jawad Berri
2021 IEEE Access  
These systems are able to detect specific user needs and adapt recommendations to actual user context.  ...  Her research interests include recommender system, information retrieval, social network, data mining and machine learning.  ...  ACKNOWLEDGEMENTS This work was supported by the Research Center of College of Computer and Information Sciences, King Saud University. The authors are grateful for this support.  ... 
doi:10.1109/access.2021.3072165 fatcat:i3igbxd44jhrzcyvynevpidcwq

Exploring recommendations in internet of things

Lina Yao, Quan Z. Sheng, Anne H.H. Ngu, Helen Ashman, Xue Li
2014 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14  
In particular, we propose a unified probabilistic based framework by fusing information across relationships between users (i.e., users' social network) and things (i.e., things correlations) to make more  ...  The proposed approach not only inherits the advantages of the matrix factorization, but also exploits the merits of social relationships and thingthing correlations.  ...  In constructing this graph, we integrate the spatial and temporal information to capture periodic patterns between locations and timestamps for improved performance.  ... 
doi:10.1145/2600428.2609458 dblp:conf/sigir/YaoSNAL14 fatcat:5iynga6odjec5aluhy5zuoxenu
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