Results 11 to 20 of about 200 (160)
Exploiting Two-Dimensional Geographical and Synthetic Social Influences for Location Recommendation
With the rapid development of location-based social networks (LBSNs), because human behaviors exhibit specific distribution patterns, personalized geo-social recommendation has played a significant role for LBSNs.
Jiping Liu +4 more
doaj +1 more source
Sentiment Severity on Location-Based Social Network (LBSN) Data of Natural disasters
Social media emerged as one of the key components to reach disaster affected people, as they supplement planning and operational coordination. Sentiment analysis was expended to identify, extract or characterize subjective information, such as opinions, expressed in a tweet.
Dr. K Shyamala* +2 more
openaire +1 more source
In order to improve the willingness of continuous use of mobile social network information services, this study combines user behavior perception to analyze the continuous use of mobile social network information services and proposes a data coverage optimization strategy based on service quality perception.
Jingjing Lv +4 more
wiley +1 more source
With the advent of the “Internet+” era, with the rapid development of emerging technologies such as the Internet of Things, cloud computing, big data, and artificial intelligence, the era of the technological change in education has arrived, with diversification of resources and large‐scale data.
Jianfeng Hou +3 more
wiley +1 more source
The rapid development of location-based social networks (LBSNs) produces the increasing number of check-in records and corresponding heterogeneous information which bring big challenges of points-of-interest (POIs) recommendation in our daily lives.
Bin Xia +4 more
doaj +1 more source
College students are the main group of Internet users. With the development of electronic technology and mobile communication technology in China, most college students can easily use computers to access the Internet, and almost all college students use mobile phones, and using mobile phones to access the Internet has become very common in Colleges and
Yahong Su, Zhaojie Lv, Lianhui Li
wiley +1 more source
Exploring IoT Location Information to Perform Point of Interest Recommendation Engine: Traveling to a New Geographical Region. [PDF]
With the development of wireless Internet and the popularity of location sensors in mobile phones, the coupling degree between social networks and location sensor information is increasing.
Yang X, Zimba B, Qiao T, Gao K, Chen X.
europepmc +2 more sources
Friendship prediction model based on factor graphs integrating geographical location
With the development of network services and location-based systems, many mobile applications begin to use users’ geographical location to provide better services. In terms of social networks, geographical location is actively shared by users.
Liang Chen +7 more
doaj +1 more source
Session‐Based Graph Attention POI Recommendation Network
Point‐of‐interest (POI) recommendation which aims at predicting the locations that users may be interested in has attracted wide attentions due to the development of Internet of Things and location‐based services. Although collaborative filtering based methods and deep neural network have gain great success in POI recommendation, data sparsity and cold
Zhuohao Zhang +3 more
wiley +1 more source
User Model‐Based Personalized Recommendation Algorithm for News Media Education Resources
Traditional recommendations for news and media education resources usually ignore the importance of sequential patterns in user check‐in behavior and fail to effectively capture the complex and dynamically changing interests of users. As a result, this study provides a recommendation model for news and media education materials based on a user model ...
Zhu Shilin, Naeem Jan
wiley +1 more source

