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Social Recommendation Model Regularized with User Trust and Item Ratings
2017
International Journal of Science and Research (IJSR)
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Based on the above observations, we propose to learn a trust aware personalized ranking method with multi-faceted trust relations for implicit feedback. ...
Social trust aware recommender systems have been well studied in recent years. ...
For example, Ma Unfortunately, most of these existing trust aware recommendation methods are proposed for social networks with explicit feedback of users. ...
doi:10.21275/art20174948
fatcat:ka3dkzhq2rfmfbqgwolz64vwnq
Group Recommender Systems Based on Members' Preference for Trusted Social Networks
2020
Security and Communication Networks
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The focus of this paper is group recommendation based on an average strategy, where group members have preferential differences and use trusted social networks to correct for their preferences. ...
However, group members' preferences are not fully considered in group recommendations, and how to use trusted social networks based on their preferences remains unclear. ...
implicit feedback dataset average strategy; and IFpre (G, i) (implicit feedback prediction) indicates a group recommendation based on the implicit feedback of dataset member preferences by trusted social ...
doi:10.1155/2020/1924140
fatcat:rwq7saeqkne2zfkhsraqgbsbcu
Location-aware computing to mobile services recommendation: Theory and practice
2020
Journal of Ambient Intelligence and Smart Environments
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implicit trust relationships from user data and integrates the explicit social information of users. ...
The implicit trust relationships are mined from the user's historical data and are then fused with explicit social trust relationships to obtain a crossover data fusion model. ...
The implicit trust relationships are mined from the user's historical data and are then fused with explicit social trust relationships to obtain a crossover data fusion model. ...
doi:10.3233/ais-200588
fatcat:kq5kxix6u5b3fcyopk7edkfs3i
Extracting Implicit Social Relation for Social Recommendation Techniques in User Rating Prediction
2017
Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion
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the prediction of items for an active user. ...
Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. ...
context-aware trust inference in social networks ...
doi:10.1145/3041021.3051153
dblp:conf/www/TaheriMFKGM17
fatcat:yanuoi47pvdcxbj4e2lfktv4fy
SURVEY ON RECOMMENDER SYSTEMS FOR SOLVING COLD START PROBLEM
2019
International Journal of Recent Trends in Engineering and Research
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The task of recommender system is to predict the user's ratings for each item and ranking the items. In research area RS plays a major role. ...
For example, the ratings are very high for the most popular items and some items are rated without considering the knowledge in utilizing it. ...
The intelligence of social relation of a user together with the information of ratings is used by the social recommender system for providing recommendations [22] . ...
doi:10.23883/ijrter.conf.20190322.055.4z5km
fatcat:l7man4gpvndwhmavchvj2mouse
Social temporal collaborative ranking for context aware movie recommendation
2013
ACM Transactions on Intelligent Systems and Technology
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Social temporal collaborative ranking for context aware movie recommendation. ...
In this work, we address several challenges for the context aware movie recommendation tasks in CAMRa 2010: (1) how to combine multiple heterogeneous forms of user feedback? ...
Social Network Aware Recommendation Online social networking services have enjoyed enormous growth in recent years. ...
doi:10.1145/2414425.2414440
fatcat:v6b25oszajddzbyn5yi3hesq74
Factored similarity models with social trust for top-N item recommendation
2017
Knowledge-Based Systems
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In this article, we propose three factored similarity models with the incorporation of social trust for item recommendation based on implicit user feedback. ...
Trust-aware recommender systems have attracted much attention recently due to the prevalence of social networks. ...
Although many studies have been conducted on the top-N recommender systems on the basis of implicit user feedback, very few have incorporated social trust relationships for item recommendation. ...
doi:10.1016/j.knosys.2017.01.027
fatcat:gywlivbivjhdplymsib25luj3y
Relational Metric Learning with Dual Graph Attention Networks for Social Recommendation
[chapter]
2020
Lecture Notes in Computer Science
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Specifically, relations in two domains are modeled as two types of relation vectors, with which each user can be regarded as being translated to both multiple item-aware and social-aware representations ...
Existing social recommenders typically incorporate all social relations into user preference modeling, while social connections are not always built on common interests. ...
Recently, top-N recommendation based on implicit feedback has attracted much research interest since implicit feedback is much more abundant and easier to collect in practice [10] . ...
doi:10.1007/978-3-030-47426-3_9
fatcat:fmwcfmqurbhe3afka6unw5as6a
Trust and Trustworthiness in Social Recommender Systems
[article]
2019
arXiv
pre-print
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Ranking algorithms for social recommendation often encode broad assumptions about network structure (like homophily) and group cognition (like, social action is largely imitative). ...
The constituent dimensions of trustworthiness (diversity, transparency, explainability, disruption) highlight new opportunities for discouraging dogmatization and building decision-aware, transparent news ...
FUTURE WORK This study explores the theoretical foundations of trust-aware ranking in social recommenders. ...
arXiv:1903.01780v1
fatcat:qchpnqpbrzevxmjfgm3bdpee2e
SPMC: Socially-Aware Personalized Markov Chains for Sparse Sequential Recommendation
2017
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
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Dealing with sparse, long-tailed datasets, and cold-start problems is always a challenge for recommender systems. ...
In this paper, we propose new methods to combine both social and sequential information simultaneously, in order to further improve recommendation performance. ...
In addition to the feedback itself, we assume that timestamps are also available for each action, as well as the social relations (or trust relationships) of each user. ...
doi:10.24963/ijcai.2017/204
dblp:conf/ijcai/CaiHM17
fatcat:7w3ehhex4zc2repopg6iy5dlk4
SPMC: Socially-Aware Personalized Markov Chains for Sparse Sequential Recommendation
[article]
2017
arXiv
pre-print
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Dealing with sparse, long-tailed datasets, and cold-start problems is always a challenge for recommender systems. ...
In this paper, we propose new methods to combine both social and sequential information simultaneously, in order to further improve recommendation performance. ...
In addition to the feedback itself, we assume that timestamps are also available for each action, as well as the social relations (or trust relationships) of each user. ...
arXiv:1708.04497v1
fatcat:d2y3jv2f4vfcnaaxsouzb2ydwe
TrustSVD: A Novel Trust-Based Matrix Factorization Model with User Trust and Item Ratings
2017
International Journal of Advanced Research in Computer Science and Software Engineering
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implicit influence of trusted users on the prediction of items for an active user. ...
By analyzing the social trust data from four real-world data sets, we conclude that not only the explicit but also the implicit influence of both ratings and trust should be taken into consideration in ...
LITERATURE SURVEY Trust-aware recommender systems have been studied because social trust provides an alternative view of user preferences other than item ratings. ...
doi:10.23956/ijarcsse.v7i11.422
fatcat:gwqftsrkozbg5a3rurtpthg2bi
Learning Consumer and Producer Embeddings for User-Generated Content Recommendation
[article]
2018
arXiv
pre-print
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In this work, we propose a method CPRec (consumer and producer based recommendation), for recommending content on UGC-based platforms. ...
We model each interaction by the ternary relation between the consumer, the consumed item, and its producer. ...
Socially-Aware Recommendation: Leveraging social networks can help us understand user-user relationships and improve the performance of item recommendation [7, 8, 10, 16] . ...
arXiv:1809.09739v1
fatcat:jgpjhkqkorcczgaz2jbbhmx3ni
Recommender Systems: Sources of Knowledge and Evaluation Metrics
[chapter]
2013
Studies in Computational Intelligence
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Recommender or Recommendation Systems (RS) aim to help users dealing with information overload: finding relevant items in a vast space of resources. ...
Research on RS has been active since the development of the first recommender system in the early 1990s, Tapestry, and some articles and books that survey algorithms and application domains have been published ...
Social recommender systems can be categorized by three groups: social recommenders for recommending items, social recommenders for recommending people, and group recommender systems. ...
doi:10.1007/978-3-642-33326-2_7
fatcat:j3377tftmfagfg7txt3qzrhjyi
Determining Trust Based Examination on Social Networks for Hotel Recommendation
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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The proposed technique is used to merge with social trust information thus from that we can get the trusted network. Thus, by using the trusted network reviews we can avoid the fake reviews. ...
The objective of this research work is to enhance the performance of a novel recommendation site for tavern by mining the data about all kinds of hotel in websites. ...
on feedback that are implicit. ...
doi:10.35940/ijitee.i1134.0789s419
fatcat:acbua4ijl5eivev5r2iwih3wsq
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