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Social-group-based ranking algorithms for cold-start video recommendation

Chunfeng Yang, Yipeng Zhou, Liang Chen, Xiaopeng Zhang, Dah Ming Chiu
2016 International Journal of Data Science and Analytics  
In this paper, by collaborating with Tencent Video, we propose a social-group-based algorithm to produce personalized video recommendations by ranking candidate videos from the groups a user is affiliated  ...  Cold start, a problem relatively common in the practical online video recommendation service, occurs when the user who needs video recommendation has no viewing history.  ...  An alternative strategy for solving the cold-start problem is to use social information [29] . By exploiting online social networks, videos viewed by a user's friend can be used for recommendation.  ... 
doi:10.1007/s41060-016-0015-0 dblp:journals/ijdsa/YangZCZC16 fatcat:sg75pbtrones7azbujtlbufaz4

Eliciting Auxiliary Information for Cold Start User Recommendation: A Survey

Nor Aniza Abdullah, Rasheed Abubakar Rasheed, Mohd Hairul Nizam Md. Nasir, Md Mujibur Rahman
2021 Applied Sciences  
Similar users are clustered into sub-groups so that a cold start user could be allocated and inferred to a sub-group having similar profiles for recommendations.  ...  Results show that auxiliary information for cold start recommendation is obtained by adapting traditional filtering and matrix factorization algorithms typically with machine learning algorithms to build  ...  This was achieved through the use of video-ranking algorithms to rank the videos within a group and outside a group which a cold start user is affiliated to.  ... 
doi:10.3390/app11209608 fatcat:foxbu3gt4fdxhdxuhijtufkyiu

Two Birds One Stone

Jingjing Li, Ke Lu, Zi Huang, Heng Tao Shen
2017 Proceedings of the 2017 ACM on Multimedia Conference - MM '17  
For the cold-start problem, we learn from side information, e.g., user attributes, user social relationships, etc. Then, we transfer the learned knowledge to new users.  ...  This paper, for the rst time, proposes a novel approach which can simultaneously handle both cold-start and long-tail recommendation in a uni ed objective.  ...  Long-Tail Recommendation For the long-tail recommendation problems, Yin et al. [37] propose a novel suite of graph-based algorithms.  ... 
doi:10.1145/3123266.3123316 dblp:conf/mm/LiLHS17 fatcat:ojjjhyhccfegbdvkzkef2qcs4q

Natural Language Processing via LDA Topic Model in Recommendation Systems [article]

Hamed Jelodar, Yongli Wang, Mahdi Rabbani, SeyedValyAllah Ayobi
2019 arXiv   pre-print
Collaborative Filtering (CF) and Content-Based (CB) are Well-known techniques for building recommendation systems.  ...  In the past few years, many articles have been published based on LDA technique for building recommendation systems.  ...  Also Some researchers investigated the cold-start problem in tag recommendation, for example; In Hariri et al. (2012) , presented a system recommendation based on LDA for Cold-Start in Music Recommendation  ... 
arXiv:1909.09551v1 fatcat:ok3piccvx5agfds6adyiny2aom

Trust Based Novel Recommendation Regularized with Item Ratings

R. Priyadharshini
2017 International Journal for Research in Applied Science and Engineering Technology  
In order to enhance the novel recommendation model, we propose a trust based recommendation model with item rating where data sparsity and cold start problem are rectified.We make use of personalized social  ...  They use various projections as a basis for issuing recommendations. Item rating is a group of classifications designed to extract information about a quantitative or qualitative attribute.  ...  Our work focuses on the rating prediction task while most algorithmic approaches where only designed for either one of the recommendations tasks. The major issues are data sparsity and cold start.  ... 
doi:10.22214/ijraset.2017.4086 fatcat:lzwdh4eimzaa3junt2yng6i7lu

A Survey on Recommendation Techniques in Numerous Domains

Gourav Jain, Nishchol Mishra, Sanjeev Sharma
2013 International Journal of Computer Applications  
Various algorithms were proposed by different researchers for recommendation of web pages, items, movie, video etc.  ...  A Recommendation System is a sturdy and valuable tool used for decision making and provides a ranking of the most popular items based on user preference.  ...  The authors would like to thank the anonymous reviewers for their detailed, valuable comments and constructive suggestions.  ... 
doi:10.5120/11745-7379 fatcat:wgfr3oac55hgbnci37gpd65hbe

A Random Walk Based Model Incorporating Social Information for Recommendations [article]

Shang Shang, Sanjeev R. Kulkarni, Paul W. Cuff, Pan Hui
2013 arXiv   pre-print
In this paper, we propose a hybrid collaborative filtering model based on a Makovian random walk to address the data sparsity and cold start problems in recommendation systems.  ...  The model provides personalized recommendations and predictions to individuals and groups. The proposed algorithms are evaluated on MovieLens and Epinions datasets.  ...  Discussions Recommendations for groups Because of the special structure of the rank graph, we can naturally extend the recommendation for individual users to groups.  ... 
arXiv:1208.0787v2 fatcat:7h4pdjo6yve3vhneptcbhpqi5m

A randomwalk based model incorporating social information for recommendations

Shang Shang, Sanjeev R. Kulkarni, Paul W. Cuff, Pan Hui
2012 2012 IEEE International Workshop on Machine Learning for Signal Processing  
In this paper, we propose a hybrid collaborative filtering model based on a Makovian random walk to address the data sparsity and cold start problems in recommendation systems.  ...  The model provides personalized recommendations and predictions to individuals and groups. The proposed algorithms are evaluated on MovieLens and Epinions datasets.  ...  Discussions Recommendations for groups Because of the special structure of the rank graph, we can naturally extend the recommendation for individual users to groups.  ... 
doi:10.1109/mlsp.2012.6349732 dblp:conf/mlsp/ShangKCH12 fatcat:fzthmck2drdr5kpp6lcfojaw2m

An Efficient Content-Based Video Recommendation

walaa hassan, Youssef Roshdy, Mennat Allah Hassan, foad osama
2022 Journal of Computing and Communication (Online)  
This is known as cold-start that affects newly uploaded videos, since they start without any data or user comments.  ...  In this paper, a recommendation system by content is proposed, the system detects the objects and sounds inside the video, and also adds the feature to search using uploaded scenes or filter scenes based  ...  [25] tried to solve the cold-start problem by using the advantages of deep convolution neural networks to boost the content-based video recommendations.  ... 
doi:10.21608/jocc.2022.218455 fatcat:y7hmey6wifeexighguf3h6uvhi

YouTube Video Recommendation via Cross-Network Collaboration

Tejal T., Sheetal A.
2016 International Journal of Computer Applications  
We have proposed YouTube video cross network recommendation system; it extracts users auxiliary information on Twitter to address the three typical problems: new user, cold start and sparsity which are  ...  Finally, we compared our cross-relevance method with other single network based methods a) the average relevance of videos automatically recommended by our system for new YouTube users is 76% with Top  ...  F. cold-start problem in recommender systems with social tags [10] Diffusion based recommendation Algorithm is used to improve diversity of recommendation and solve problems in social tagging.  ... 
doi:10.5120/ijca2016910896 fatcat:pknulwa675e7xpmwwjbib3juw4

Joint Social and Content Recommendation for User-Generated Videos in Online Social Network

Zhi Wang, Lifeng Sun, Wenwu Zhu, Shiqiang Yang, Hongzhi Li, Dapeng Wu
2013 IEEE transactions on multimedia  
In this framework, we first propose a user-content matrix update approach which updates and fills in cold user-video entries to provide the foundations for the recommendation.  ...  Then, based on the updated user-content matrix, we construct a joint social-content space to measure the relevance between users and videos, which can provide a high accuracy for video importing and re-sharing  ...  algorithm.  ... 
doi:10.1109/tmm.2012.2237022 fatcat:pmk2ebjik5gytlfxoh6q4dtqxi

A SURVEY ON COMPREHENSIVE TRENDS IN RECOMMENDATION SYSTEMS & APPLICATIONS

Ssvr Kumar Addagarla
2019 International Journal of Electronic Commerce Studies  
Various improvements and limitations in Recommendation systems have been listed out with evolution metrics for analyzing the accuracy of the algorithms.  ...  This paper investigates the various traditional Recommendation System like Content-based (CB), Collaboration Filtering-based (CF), Demographic-based, Knowledge-based and discussed current trends in recommendation  ...  For this author used similarity measures for the videos and ranked for top N-recommendations 57 .  ... 
doi:10.7903/ijecs.1705 fatcat:puqvc6uhd5dhppuatartqqq6ki

Exploring Social Approach to Recommend Talks at Research Conferences

Danielle Lee, Peter Brusilovsky
2012 Proceedings of the 8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing  
Content-boosted Recommendation, Cold Start Problem, Social Networks, Social Network-based Recommendations, Hybrid Recommendation, ConferenceNavigator I.  ...  Moreover, for cold-start users who have insufficient number of items to express their preferences, the recommendations based on their social connections generated significantly better predictions than  ...  For cold-start users, all kinds of the social network-based recommendations generated significantly better suggestions than other CF and community-based recommendations, across all rank levels of the precisions  ... 
doi:10.4108/icst.collaboratecom.2012.250415 dblp:conf/colcom/LeeB12 fatcat:gjk6egjmwbddxklsx5oh3dyft4

Online Product Recommendation using Relationships and Demographic Data on Social Networks

R. Satish Srinivas, C. S. Anish Balaji, P. Saravanan
2016 Indian Journal of Science and Technology  
It then feeds these into the proposed ranking algorithm to find the relevance scores of the products to the target user and based on this the recommended product links are displayed.  ...  This approach leads to sparsity and cold-start issues.  ...  Even though CF algorithms for recommender systems were easily portable, they suffered from data sparsity and cold start problems.  ... 
doi:10.17485/ijst/2016/v9i44/99896 fatcat:7trspsqinvetzgzdn3g4juajzi

Design of a Personalized Recommendation System for Learning Resources based on Collaborative Filtering

Mingxia Zhong, Rongtao Ding
2022 North atlantic university union: International Journal of Circuits, Systems and Signal Processing  
Based on the data on learning behaviors of the online learning platform of our university, the authors explored the classic cold start problem of the popular collaborative filtering algorithm, and improved  ...  the algorithm based on the data features of the platform.  ...  ACKNOWLEDGMENT This research was supported by 2020 Zhejiang Provincial Department of education general research project "Research on the talent training mechanism of social recruitment under the background  ... 
doi:10.46300/9106.2022.16.16 fatcat:2ubjner4t5hwxotidmavxd6rda
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