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Group recommendations with rank aggregation and collaborative filtering

Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
2010 Proceedings of the fourth ACM conference on Recommender systems - RecSys '10  
This paper analyzes the effectiveness of group recommendations obtained aggregating the individual lists of recommendations produced by a collaborative filtering system.  ...  We compare the effectiveness of individual and group recommendation lists using normalized discounted cumulative gain.  ...  We have adopted that approach and used rank aggregation methods for combining the ranking independently produced for each group member by a collaborative filtering RS.  ... 
doi:10.1145/1864708.1864733 dblp:conf/recsys/BaltrunasMR10 fatcat:3qd2qtq46rft3piy32yujfeu2i

Enhancing Recommendation using Ranking in Multidimensional Space

R. Suganya Devi, A. P. Chitra, D. Manjula
2016 Indian Journal of Science and Technology  
In our work, similar queries are extracted using Memory based Collaborative Filtering (MCF) and those individual ranked lists are combined to produce single superior ranked lists using Top-k Event Scanning  ...  (TES) approach, a rank aggregation algorithm which employs B+ trees for indexing.  ...  Baltrunas 8 introduce Group recommendation with rank aggregation and collaborative filtering based on the ranking of the products with the main consideration of the ranking of the users on the products  ... 
doi:10.17485/ijst/2016/v9i27/89853 fatcat:llqifxetwndsdmxe7frlsfvn3y

Privacy Preserving Recommendation System Based on Groups [article]

Shang Shang and Yuk Hui and Pan Hui and Paul Cuff and Sanjeev Kulkarni
2013 arXiv   pre-print
We construct a hybrid collaborative filtering model based on Markov random walks to provide recommendations and predictions to group members.  ...  Trade-offs between quality and privacy in recommendation systems naturally arise. In this paper, we present a privacy preserving recommendation framework based on groups.  ...  In this way, a group recommendation could be made. However, traditional collaborative filtering methods are challenged by problems such as cold start and data sparsity.  ... 
arXiv:1305.0540v2 fatcat:am4inqyqmzeynnpkizsjsvggya

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  ...  In this work, we utilize social groups with richer information to recommend videos. It is common that users may be affiliated with multiple groups in OSNs.  ...  Video aggregation With the ranked video lists from multiple groups as well as the score of each group, we should address the weighted ranking aggregation problem.  ... 
doi:10.1007/s41060-016-0015-0 dblp:journals/ijdsa/YangZCZC16 fatcat:sg75pbtrones7azbujtlbufaz4

A Novel Nonadditive Collaborative-Filtering Approach Using Multicriteria Ratings

Yi-Chung Hu
2013 Mathematical Problems in Engineering  
Experimental results demonstrate that the generalization ability of the proposed approach performs well compared with other similarity-based collaborative-filtering approaches using multicriteria ratings  ...  The applicability of the proposed approach to the recommendation of the initiators on a group-buying website is examined.  ...  Compared with the traditional single-criterion rating approach, several collaborative-filtering approaches using multicriteria ratings, and the aggregation-functionbased approach using the WAM, it can  ... 
doi:10.1155/2013/957184 fatcat:wxrgkujkg5e4jfk5ylwlqfebdu

Aggregate Diversity Techniques in Recommender Systems

Sebabatso J. Metla, Tranos Zuva, Seleman M. Ngwira
2014 Lecture Notes on Information Theory  
Index Terms-collaborative filtering, cross-check approach, recommendation diversity, recommender systems, ranking functions I.  ...  However more focus has been on improving recommendation accuracy while aggregate recommendation quality received less attention.  ...  The first one calculates the rating predictions using existing filtering approaches like CF 2 (collaborative filtering) then re-rank the items with the highest predicted ratings to make space for long  ... 
doi:10.12720/lnit.2.3.238-242 fatcat:os5rpfwcm5hnbgkju7fmjbzll4

Technical Job Recommendation System Using APIs and Web Crawling

Naresh Kumar, Manish Gupta, Deepak Sharma, Isaac Ofori, Arpit Bhardwaj
2022 Computational Intelligence and Neuroscience  
A hybrid system of Content-Based Filtering and Collaborative Filtering is implemented to recommend these jobs.  ...  The intention is to aggregate and recommend appropriate jobs to job seekers, especially in the engineering domain.  ...  to go forth with developing a fully functional user interface supporting a job aggregator and recommendation system.  ... 
doi:10.1155/2022/7797548 pmid:35774438 pmcid:PMC9239795 fatcat:wvkye2ytwnbwlhgntiem54gj24

Exploring Social Influence for Recommendation - A Probabilistic Generative Model Approach [article]

Mao Ye and Xingjie Liu and Wang-Chien Lee
2011 arXiv   pre-print
In this paper, we propose a probabilistic generative model, called unified model, which naturally unifies the ideas of social influence, collaborative filtering and content-based methods for item recommendation  ...  The experimental results also confirm that our social influence based group recommendation algorithm outperforms the state-of-the-art algorithms for group recommendation.  ...  Aggregation-based Recommendation For group recommendation, one popular approach is the ranking aggregation method which finds a "consensus" ranking/score for each item for the whole group.  ... 
arXiv:1109.0758v1 fatcat:2m6yemtg4bgu3omf5owk2skxhu

Hybrid group recommendations for a travel service

Toon De Pessemier, Jeroen Dhondt, Luc Martens
2016 Multimedia tools and applications  
The recommendation algorithm is a hybrid approach combining a content-based, collaborative filtering, and knowledge-based solution.  ...  For groups of users, such as families or friends, individual recommendations are aggregated into group recommendations, with an additional opportunity for users to give feedback on these group recommendations  ...  We opted to aggregate the individual recommendation lists into a group recommendation list instead of aggregating the individuals' ratings into group ratings and subsequently generating group recommendations  ... 
doi:10.1007/s11042-016-3265-x fatcat:qsaovalr4bbavcky2q45ksvkca

Profile aggregation-based group recommender systems: Moving from item preference profiles to deep profiles

Le Nguyen Hoai Nam
2022 IEEE Access  
INDEX TERMS Collaborative filtering, group recommender systems, recommender systems.  ...  In this paper, we introduce the concept of deep profiles of users, and we propose group recommendation methods based on the aggregation of group members' deep profiles, instead of item preference profiles  ...  COLLABORATIVE FILTERING The general structure of the implementation of memorybased collaborative filtering for a profile aggregation-based group recommender system is shown in Fig. 3 .  ... 
doi:10.1109/access.2021.3140121 fatcat:gih5nyhmqfbjbjhlujlsiq2t3y

Classified Ranking of Semantic Content Filtered Output Using Self-organizing Neural Networks [chapter]

Marios Angelides, Anastasis Sofokleous, Minaz Parmar
2006 Lecture Notes in Computer Science  
Cosmos-7 is an application that can create and filter MPEG-7 semantic content models with regards to objects and events, both spatially and temporally.  ...  ranking.  ...  In figure 2 we present the basic idea of the ranking module based on the collaborative filtering and recommendation principles, which define that a user should be recommended items that are preferable  ... 
doi:10.1007/11840930_6 fatcat:technavewfbd3hg3doj7o5iy44

Biclustering based Collaborative Filtering Algorithm for Personalized Web Service Recommendation

M. Chandralekha, Saranya K.G., G. Sudha
2016 International Journal of Computer Applications  
To deal with the data sparsity problem a novel collaborative filtering recommendation algorithm is proposed based on biclustering.  ...  Collaborative filtering (CF) is a technique to carry out automatic suggestions for a user based on the view of other users with similar taste.  ...  A very accurate recommendation was obtained with Biclustering based collaborative filtering approach when tested with web service data set.  ... 
doi:10.5120/ijca2016909871 fatcat:d3oxl3iz65cvfngtsbs6nv6ae4

Group Recommender Systems: New Perspectives in the Social Web [chapter]

Iván Cantador, Pablo Castells
2012 Intelligent Systems Reference Library  
In this chapter, we revise state of the art approaches on group formation, modelling and recommendation, and present challenging problems to be included in the group recommender system research agenda  ...  An increasingly important type of recommender systems comprises those that generate suggestions for groups rather than for individuals.  ...  Acknowledgements This work was supported by the Spanish Ministry of Science and Innovation (TIN2008-06566-C04-02), and the Community of Madrid (S2009TIC-1542).  ... 
doi:10.1007/978-3-642-25694-3_7 fatcat:774ktylwknef5coi3lkmvdricy

Recommending Ads from Trustworthy Relationships in Pervasive Environments

Francisco Martinez-Pabon, Juan Camilo Ospina-Quintero, Gustavo Ramirez-Gonzalez, Mario Munoz-Organero
2016 Mobile Information Systems  
However, there is no consensus about the variables to use during the trust inference process, and its integration into a classic collaborative filtering recommender system deserves a deeper research.  ...  Although recommender systems have been a traditional solution to decrease users' cognitive effort to find good and personalized items, the classic collaborative filtering needs to include contextual information  ...  Part of this work was conducted at Carlos III University of Madrid, Spain, where Francisco Martinez and Juan Camilo Ospina were visiting scholars in 2014 and 2015, respectively.  ... 
doi:10.1155/2016/8593173 fatcat:tdz7mzhkezfyxhy6grqxsuqmpu

A Review on User Recommendation System Based Upon Semantic Analysis

Lovedeep Kaur, Naveen Kumari
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
filtering to improve the coverage of recommendation.  ...  In this paper, we review the evaluation and improvement techniques for improving overall performance of recommendation systems and proposing a semantic analysis based approach for clustering based collaborative  ...  Basically the main motive of hybrid approach is to aggregate collaborative filtering and content-based filtering to improve recommendation accuracy.  ... 
doi:10.23956/ijarcsse.v7i11.465 fatcat:o3hz2q3x7vdudbxnisqk5xsx44
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