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An empirical comparison of social, collaborative filtering, and hybrid recommenders

Alejandro Bellogín, Iván Cantador, Fernando Díez, Pablo Castells, Enrique Chavarriaga
2013 ACM Transactions on Intelligent Systems and Technology  
We use this metric together with precision metrics in an empirical comparison of several social, collaborative filtering, and hybrid recommenders.  ...  The obtained results show that a better balance between precision and coverage can be achieved by combining social-based filtering (high accuracy, low coverage) and collaborative filtering (low accuracy  ...  We present some well-known state-of-the-art collaborative filtering, social and hybrid recommender systems, and present extensions and adaptations of some of these recommenders in order to exploit social  ... 
doi:10.1145/2414425.2414439 fatcat:bxc56kudc5g3bmya7sjxfvbxha

Utilizing Physical and Social Context to Improve Recommender Systems

Wolfgang Woerndl, Georg Groh
2007 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops  
Our evaluation shows that the social recommender outperforms traditional collaborative filtering algorithms in our scenario.  ...  Finally, we describe our approach to utilize social networks to enhance collaborative filtering.  ...  Figure 2 . 2 Hybrid recommender with context Figure 3 :Figure 4 : 34 Comparison of F-measure performance of social recommender vs.  ... 
doi:10.1109/wiiatw.2007.4427555 dblp:conf/iat/WoerndlG07 fatcat:cgyb7sofxnhjvl6ufxvcdvxusy

Utilizing Physical and Social Context to Improve Recommender Systems

Wolfgang Woerndl, Georg Groh
2007 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops  
Our evaluation shows that the social recommender outperforms traditional collaborative filtering algorithms in our scenario.  ...  Finally, we describe our approach to utilize social networks to enhance collaborative filtering.  ...  Figure 2 . 2 Hybrid recommender with context Figure 3 :Figure 4 : 34 Comparison of F-measure performance of social recommender vs.  ... 
doi:10.1109/wi-iatw.2007.123 fatcat:goaslgdsfncqpcj3dcy6by3n4y

Product Recommendation based on Shared Customer's Behaviour

Fátima Rodrigues, Bruno Ferreira
2016 Procedia Computer Science  
An empirical comparison of social, collaborative filtering, and hybrid recommenders, ACM Transactions on Intelligent Systems and Technology (TIST) 4, 1-29, 2013. 10. , 26 (3), 766-779, 2014  ...  Customer Lifetime Value Analysis and RFM An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data.  ... 
doi:10.1016/j.procs.2016.09.133 fatcat:vxnoect6wner5hy2dwt7ampxoe

A study of heterogeneity in recommendations for a social music service

Alejandro Bellogín, Iván Cantador, Pablo Castells
2010 Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems - HetRec '10  
Aiming to identify which are the sources of information (ratings, tags, social contacts, etc.) most valuable for recommendation, we evaluate a number of content-based, collaborative filtering and social  ...  The obtained results show that, in Last.fm, social tagging and explicit social networking information provide effective and heterogeneous item recommendations.  ...  [22] present an empiric comparison of a large number of recommenders that estimate item ratings by exploiting user tags, ratings and clickthrough data.  ... 
doi:10.1145/1869446.1869447 fatcat:o5xusuzo3jgjfpj7557wwmwlze

Using Social Tags and User Rating Patterns for Collaborative Filtering

Iljoo Kim, Vipul Gupta
2017 International Journal of Information Systems and Social Change  
They evaluate the proposed hybrid approach, illustrated in the context of movie recommendation.  ...  The authors also empirically evaluate various existing recommendation approaches (in comparison with the newly proposed approach) using sensitivity analyses to investigate the potential use of varied user  ...  Among various techniques introduced in prior studies, content-based, collaborative-filtering, and hybrid methods are the three most popular recommendation approaches.  ... 
doi:10.4018/ijissc.2017040102 fatcat:kdh2vgsj6vbozhyjuosnxopcci

Leveraging Semantic Similarity for Folksonomy-Based Recommendation

Daniela Godoy, Gustavo Rodriguez, Franco Scavuzzo
2014 IEEE Internet Computing  
Experiments carried out with data from two social sites showed that associating semantics to tags results in more accurate similarities among elements in tagging systems and, consequently, enhances recommendations  ...  Here, we analyze the role of semantic similarity to calculate the resemblance between user profiles and published resources in folksonomies.  ...  ), a user-to-user (similar to the collaborative filtering approach) and a hybrid recommendation method.  ... 
doi:10.1109/mic.2013.26 fatcat:yjmdupwwlnctjl2dqtyrufagda

A graph model for E-commerce recommender systems

Zan Huang, Wingyan Chung, Hsinchun Chen
2004 Journal of the American Society for Information Science and Technology  
Evaluation results showed that combining product content information and historical customer transaction information achieved more accurate predictions and relevant recommendations than using only collaborative  ...  We used a data set from an online bookstore as our research test-bed.  ...  We would also like to thank Thian-Huat Ong and Hui Liu for their involvement in system design and development.  ... 
doi:10.1002/asi.10372 fatcat:uyuo5j6ykbdibc6wojchezapne

Folksonomy-Based Recommender Systems With User-S Recent Preferences

Cheng-Lung Huang, Han-Yu Chien, Michael Conyette
2011 Zenodo  
The proposed system includes the following stages: grouping similar users into clusters using an E-M clustering algorithm, finding similar resources based on the user-s bookmarks, and recommending the  ...  Social bookmarking is an environment in which the user gradually changes interests over time so that the tag data associated with the current temporal period is usually more important than tag data temporally  ...  Unlike previous researchers like this, the current study constructs a two-stage recommender approach that hybridizes the collaborative filtering and content-based filtering. A.  ... 
doi:10.5281/zenodo.1332346 fatcat:nxxasu7xyzdhjptuh52ifjpq3u

Collaborative And Content-Based Recommender System For Social Bookmarking Website

Cheng-Lung Huang, Cheng-Wei Lin
2010 Zenodo  
Experimental results show that the proposed tag-based collaborative and content-based filtering hybridized recommender system is promising and effectiveness in the folksonomy-based bookmarking website.  ...  The purpose of the proposed system is to recommend Internet resources (such as books, articles, documents, pictures, audio and video) to users.  ...  Unlike previous researches, this study constructs a two-stage recommender approach that hybridizes the collaborative filtering and content-based filtering.  ... 
doi:10.5281/zenodo.1082637 fatcat:ie5areovcrgvdas2u5uxuup7rq

Applying Clustering Approach in Blog Recommendation

Zeinab Borhani-Fard, Behrouz Minaei, Hamid Alinejad-Rokny
2013 Journal of Emerging Technologies in Web Intelligence  
This problem leads to an inaccurate comparison among users, and consequently it decreases the accuracy of collaborative filtering algorithms.  ...  Index Terms-Blog networks, Collaborative filtering, Hybrid recommendation system, Graph clustering. Hamid Alinejad-Rokny is a member of  ...  Methods in Collaborative filtering can be divided to memory-based, model-based and hybrid [6] .  ... 
doi:10.4304/jetwi.5.3.296-301 fatcat:ii7hchjalfh7biirwpjaaj5qai

Enhancing collaborative filtering systems with personality information

Rong Hu, Pearl Pu
2011 Proceedings of the fifth ACM conference on Recommender systems - RecSys '11  
Collaborative filtering (CF), one of the most successful recommendation approaches, continues to attract interest in both academia and industry.  ...  However, one key issue limiting the success of collaborative filtering in certain application domains is the cold-start problem, a situation where historical data is too sparse (known as the sparsity problem  ...  Collaborative filtering (CF) is one of the most successful and widely implemented recommendation technologies [26] .  ... 
doi:10.1145/2043932.2043969 dblp:conf/recsys/HuP11 fatcat:keeuihdyqbdfliyyeqqqiwrqhq

Quantifying and Recommending Expertise When New Skills Emerge

Dongping Fang, Kush R. Varshney, Jun Wang, Karthikeyan Natesan Ramamurthy, Aleksandra Mojsilovic, John H. Bauer
2013 2013 IEEE 13th International Conference on Data Mining Workshops  
These models include collaborative filtering, content-based, and novel hybrid recommendation approaches.  ...  We apply them in an empirical study of real-world corporate data, in which we compare and contrast the models to gain insight on the drivers of performance.  ...  ACKNOWLEDGMENT The authors thank members of the IBM Expertise project team from across the corporation.  ... 
doi:10.1109/icdmw.2013.33 dblp:conf/icdm/FangV0RMB13 fatcat:bgd653suqzbrhjt5wyl7wnv4r4

GeoSRS: A hybrid social recommender system for geolocated data

Joan Capdevila, Marta Arias, Argimiro Arratia
2016 Information Systems  
We present GeoSRS, a hybrid recommender system for a popular locationbased social network (LBSN), in which users are able to write short reviews on the places of interest they visit.  ...  Finally, we study the performance of GeoSRS on our collected dataset and conclude that by combining sentiment analysis and text modelling, GeoSRS generates more accurate recommendations.  ...  The authors gratefully acknowledge the extensive comments of the anonymous reviewers that lead to an improvement of the original manuscript.  ... 
doi:10.1016/j.is.2015.10.003 fatcat:7taan6vfwrhjhp3jm7pz72wpta

A Sentiment-Enhanced Hybrid Recommender System for Movie Recommendation: A Big Data Analytics Framework

Yibo Wang, Mingming Wang, Wei Xu
2018 Wireless Communications and Mobile Computing  
In this paper, a movie recommendation framework based on a hybrid recommendation model and sentiment analysis on Spark platform is proposed to improve the accuracy and timeliness of mobile movie recommender  ...  The hybrid recommendation model with sentiment analysis outperforms the traditional models in terms of various evaluation criteria.  ...  Therefore, the combination of collaborative filtering and content-based method with sentiment analysis makes our model performs better. For comparison, we also evaluate some recommendation method.  ... 
doi:10.1155/2018/8263704 fatcat:7jdlrnpdsfc4nhoapubcvmhv3u
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