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Information and knowledge management in online rich presence services
2013
Information Systems Frontiers
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The rapid development of Web 2.0 for massive social network collaboration facilitates the "rich presence services" to expose information and knowledge gathered through online social networks which assists ...
filtering, services compositions, supply chain management, trust framework, grid and cloud computing. ...
The second paper "Web 2.0 Recommendation Service by Multi-Collaborative Filtering Trust Network Algorithm" (Wei et al. 2013 ), Wei et al. present a Multi-Collaborative Filtering Trust Network algorithm ...
doi:10.1007/s10796-013-9441-x
fatcat:xb4bamkdlzb4zjbhmig2qhp76q
Systematic Evaluation of Social Recommendation Systems: Challenges and Future
2016
International Journal of Advanced Computer Science and Applications
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This paper also analyses key aspects of any generic recommender system namely Domain, Personalization Levels, Privacy and Trustworthiness, Recommender algorithms to give a better understanding to researchers ...
Social Recommender System (SRS) exploits social contextual information in the form of social links of users, social tags, user-generated data that contain huge supplemental information about items or services ...
Among these techniques, Collaborative Filtering (CF) is has been the most popular in recommendation algorithm. ...
doi:10.14569/ijacsa.2016.070420
fatcat:wwvyumdr5ffohiphirbb3ycuoa
Exploiting Semantic Web Technologies for Recommender Systems: A Multi View Recommendation Engine (Short Paper)
2009
International Joint Conference on Artificial Intelligence
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We propose a multi view recommendation engine integrating, in addition of the collaborative recommendations, social and semantic recommendations. ...
Collaborative filtering systems are probably the most known recommendation techniques in the recommender systems field. They have been deployed in many commercial and academic applications. ...
The rest of the paper is organized as follows: First we present the introduction of new Web 2.0 aspects in recommender systems. ...
dblp:conf/ijcai/Oufaida09
fatcat:rvm5brcpenhjbewcjrih6r64d4
Trust-based rating prediction for recommendation in Web 2.0 collaborative learning social software
2010
2010 9th International Conference on Information Technology Based Higher Education and Training (ITHET)
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In this paper, a trust-based rating prediction approach for recommendation in Web 2.0 collaborative learning social software is proposed. ...
Trust network is exploited in the rating prediction scheme and a multi-relational trust metric is developed in an implicit way. ...
Deriving from the 3A trust network in the collaborative learning environment, a so-called "Web of Trust" for a particular user is built. ...
doi:10.1109/ithet.2010.5480038
fatcat:cuqnaribcnd5pmmmxnpf5xxmoi
Recommender systems survey
2013
Knowledge-Based Systems
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Recommender systems have developed in parallel with the web. They were initially based on demographic, content-based and collaborative filtering. ...
This article provides an overview of recommender systems as well as collaborative filtering methods and algorithms; it also explains their evolution, provides an original classification for these systems ...
Fig. 11 shows the recommender methods and algorithms (labeled as ''collaborative filtering algorithms''). ...
doi:10.1016/j.knosys.2013.03.012
fatcat:z3gc5qjhkrcd5dsaah2gjdyu3y
A Hybrid Social Network-based Collaborative Filtering Method for Personalized Manufacturing Service Recommendation
2017
International Journal of Computers Communications & Control
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Nowadays, social network-based collaborative filtering (CF) methods are widely applied to recommend suitable products to consumers by combining trust relationships and similarities in the preference ratings ...
Hence, this study has developed a hybrid social network-based CF method for recommending personalized manufacturing services. ...
Acknowledgement The work has been supported by National Natural Science Foundation of China (No. 51475410, No. 51375429) and Zhejiang Natural Science Foundation of China (No. LY17E050010). ...
doi:10.15837/ijccc.2017.5.2930
fatcat:bjtw7txrjjcrlbf5kbtemuakt4
Collaborative Services to Maintain Electronic Business Relationships
[chapter]
2007
Establishing the Foundation of Collaborative Networks
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Electronic collaborative networks are a prevailing concept in actual scientific business management literature. ...
Because of the occurrence of newly concepts as "service orientation" and service oriented architectures, electronic networks and business intelligence, has gained momentum and revival. ...
Accordingly, advanced collaborative services (e.g. filtering and pre-selection of business partners) aim at establishing zones of trust. ...
doi:10.1007/978-0-387-73798-0_46
dblp:conf/ifip5-5/WeissK07
fatcat:s6jodxwnwrh3zknhv5f5p7z5em
Research on Data Mining Algorithm of Associated User Network Based on Multi-Information Fusion
2022
Journal of Sensors
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This method recommends key technical problems and solutions based on multi-information fusion to explore the research of user network data mining. ...
The data mining algorithm of associated user network based on multi-information fusion is about 35% higher than the previous method. ...
Nowadays, social networking sites have become an indispensable part of the Web 2.0 environment. ...
doi:10.1155/2022/2417826
fatcat:pa6iealo3raytizwdbux6euqsi
An Application-oriented Review of Deep Learning in Recommender Systems
2019
International Journal of Intelligent Systems and Applications
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Recommender systems have been proved helpful in choosing relevant items. Several algorithms for recommender systems have been proposed in previous years. ...
But recommender systems implementing these algorithms suffer from various challenges. Deep learning is proved successful in speech recognition, image processing and object detection. ...
Reference [2] presents the evolution of RS into three generations, namely web 1.0, web 2.0 and web 3.0. ...
doi:10.5815/ijisa.2019.05.06
fatcat:67fgexfbfjh2no5b3phvohbole
A Community Detection and Recommendation System
2017
International Journal of Recent Trends in Engineering and Research
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This approach will improve scalability, coverage and cold start issue of collaborative filtering based recommendation system. ...
A social recommendation system using community detection approaches is proposed. We use community detection algorithm to extract friendship relations among users by analysing user-user social graph. ...
OBJECTIVES Collaboration, interaction and information sharing are the main driving forces of the current generation of web applications referred to as "Web 2.0". ...
doi:10.23883/ijrter.2017.3039.sfq1e
fatcat:5sw2g6d4ifclfgkfbkpyczmgz4
Recommendation of Points of Interest from User Generated Data Collection
2012
Proceedings of the 8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing
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We recommend three types of items: services, photos and GPS routes that are points of interests in user's surrounding. ...
In this paper, we present a context aware personalized recommendation system on web and mobile, which recommends relevant location-based data from user collection and consisting of GPS routes and photos ...
The collaborative filtering and recommendation algorithm is described in [15] . The service proposed in [13] uses web 2.0 technologies along with location-based services. ...
doi:10.4108/icst.collaboratecom.2012.250451
dblp:conf/colcom/WagaTF12
fatcat:mk47zsmvjvd6behggxpcmbb5ae
Recommender Systems Using Social Network Analysis: Challenges and Future Trends
[chapter]
2014
Encyclopedia of Social Network Analysis and Mining
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Recommendation systems, Information filtering, Collaborative filtering, Content-based filtering Glossary Recommender System (RS): Special type of information filtering system that provides a prediction ...
Also, the structure of the underlying social network in a social platform can contribute to generate recommendations that are more trusted by users (e.g., by considering the social distance in the recommendation ...
In the collaborative filtering approach, an item is recommended to a given user by following another way: the collaborative filtering methods produce user specific recommendations of items based on patterns ...
doi:10.1007/978-1-4614-6170-8_35
fatcat:ytjvcrsgtvelpfaxr5ew4obe5q
Recommender Systems Using Social Network Analysis: Challenges and Future Trends
[chapter]
2017
Encyclopedia of Social Network Analysis and Mining
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Recommendation systems, Information filtering, Collaborative filtering, Content-based filtering Glossary Recommender System (RS): Special type of information filtering system that provides a prediction ...
Also, the structure of the underlying social network in a social platform can contribute to generate recommendations that are more trusted by users (e.g., by considering the social distance in the recommendation ...
In the collaborative filtering approach, an item is recommended to a given user by following another way: the collaborative filtering methods produce user specific recommendations of items based on patterns ...
doi:10.1007/978-1-4614-7163-9_35-1
fatcat:5jms2mowibfvtaiw62c72ai7t4
Accurate and Diverse Recommendations Based on Communities of Interest and Trustable Neighbors
2015
International Journal of Security and Its Applications
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However, the limitation of most data-mining recommender systems and the algorithms lies in that they have only paid attention to improving the accuracy of recommendation algorithms while neglected the ...
The most useful recommendations may not be the most similar, but ones that offer the unexpected by introducing diversity. ...
Using news sharing and recommendations in Web 2.0 systems as an example, Medo, et al., proposed an adaptive network-based social filtering mechanism that improved their user experience [20] . ...
doi:10.14257/ijsia.2015.9.3.07
fatcat:2lt27qgshbfvrc6ymhtjnntwme
Act 2.0: The Next Generation of Assistive Consumer Technology Research
2010
Social Science Research Network
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consumers (ACT 2.0). ...
Findings -The paper argues that, while substantial advances have been made in the technical design of ACTs -and the algorithms that power recommendation systems, there are substantial barriers to wide-scale ...
Movie recommendations are then made by a collaborative filtering algorithm that uses the strength of connection value to weight the movie ratings made by people within the network. ...
doi:10.2139/ssrn.1596135
fatcat:amqutycmezdq3cnxyneve3mpve
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