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Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering [chapter]

Aleksandra Karpus, Iacopo Vagliano, Krzysztof Goczyła
2017 Communications in Computer and Information Science  
We evaluated our approach through an offline study which showed that when used with well-known recommendation algorithms it can improve the accuracy and serendipity.  ...  In this paper, we study how an ontology-based and context-aware pre-filtering technique which can be combined with existing recommendation algorithm performs in ranking tasks.  ...  contextual information in the recommendation process improve not only accuracy but also serendipity of recommendations?  ... 
doi:10.1007/978-3-319-58274-0_21 fatcat:vmoleg7lbzf35fvrjec42kozjq

Burst the Filter Bubble: Using Semantic Web to Enable Serendipity [chapter]

Valentina Maccatrozzo
2012 Lecture Notes in Computer Science  
The use case for this work focuses on TV recommender systems, however the ultimate goal is to explore the transferability of this method to different domains.  ...  This paper covers the work done in the first eight months of research and describes the plan for the entire PhD trajectory.  ...  Acknowledgments This research is supported by the FP7 STREP "ViSTA-TV" project, as well as partially supported by the FP7 IP "NoTube" project and the ONR Global NICOP "COMBINE" project.  ... 
doi:10.1007/978-3-642-35173-0_28 fatcat:5ia7k36ph5havpjo4bfeaoepra

Discovery is never by chance

Paul André, m.c. schraefel, Jaime Teevan, Susan T. Dumais
2009 Proceeding of the seventh ACM conference on Creativity and cognition - C&C '09  
In this paper we show, through a formal consideration of serendipity and analysis of how various systems have seized on attributes of interpreting serendipity, that there is a richer space for design to  ...  Computer scientists, valuing the role of serendipity in discovery, have attempted to design systems that encourage serendipity.  ...  The recommender systems literature has considered how going beyond pure accuracy metrics such as precision and recall may improve user experience.  ... 
doi:10.1145/1640233.1640279 dblp:conf/candc/AndresTD09 fatcat:cm4muaibevaszeicsa5apethk4

Towards Serendipity for Content–Based Recommender Systems

Nur Izyan Yasmin Saat, Shahrul Azman Mohd Noah, Masnizah Mohd
2018 International Journal on Advanced Science, Engineering and Information Technology  
Having a serendipitous recommendation let users explore new items that they least expect. This has resulted in the issues of serendipity in recommender systems.  ...  Thus, in this paper, we aim to formally define the concept of serendipity in recommender systems based on the literature work done.  ...  Both systems might be improved if they have a specific definition of serendipity in recommender system.  ... 
doi:10.18517/ijaseit.8.4-2.6807 fatcat:sjg7a23bcvflnldjc2xz2wq3my

Comparison of group recommendation algorithms

Toon De Pessemier, Simon Dooms, Luc Martens
2013 Multimedia tools and applications  
The group recommendations are not only assessed in terms of accuracy, but also in terms of other qualitative aspects that are important for users such as diversity, coverage, and serendipity.  ...  In recent years recommender systems have become the common tool to handle the information overload problem of educational and informative web sites, content delivery systems, and online shops.  ...  Although accuracy metrics are well known and generally accepted in the domain of recommender systems, a metric for evaluating the serendipity of a recommendation list is still an open problem.  ... 
doi:10.1007/s11042-013-1563-0 fatcat:qjzo6fhgurfsvp2im36fpl2ioq

Current challenges and visions in music recommender systems research

Markus Schedl, Hamed Zamani, Ching-Wei Chen, Yashar Deldjoo, Mehdi Elahi
2018 International Journal of Multimedia Information Retrieval  
Music recommender systems (MRS) have experienced a boom in recent years, thanks to the emergence and success of online streaming services, which nowadays make available almost all music in the world at  ...  In particular when it comes to build, incorporate, and evaluate recommendation strategies that integrate information beyond simple user--item interactions or content-based descriptors, but dig deep into  ...  Another solution to cold start is cross-domain recommendation techniques, which aim at improving recommendations in one domain (here music) by making use of information about the user preferences in an  ... 
doi:10.1007/s13735-018-0154-2 fatcat:56jsdgp5v5g3be7stpwnfvtkdi

How good your recommender system is? A survey on evaluations in recommendation

Thiago Silveira, Min Zhang, Xiao Lin, Yiqun Liu, Shaoping Ma
2017 International Journal of Machine Learning and Cybernetics  
Recommender Systems have become a very useful tool for a large variety of domains. Researchers have been attempting to improve their algorithms in order to issue better predictions to the users.  ...  In the extent of offline evaluations, some traditional concepts of evaluation have been explored, such as accuracy, Root Mean Square Error and P@N for top-k recommendations.  ...  [38] attempted to balance novelty, diversity and serendipity, while Ribeiro et al. [28] attempted improving accuracy, novelty and diversity, accordingly.  ... 
doi:10.1007/s13042-017-0762-9 fatcat:o77u7tg4yva47nlo6vto2xeaee

Hybrid recommender systems: A systematic literature review

Erion Çano, Maurizio Morisio
2017 Intelligent Data Analysis  
Besides this, newer challenges were also identified such as responding to the variation of user context, evolving user tastes or providing cross-domain recommendations.  ...  Hybrid recommender systems combine two or more recommendation strategies in different ways to benefit from their complementary advantages.  ...  The system is used in the domain of tourism and provides improved accuracy.  ... 
doi:10.3233/ida-163209 fatcat:rqskvan7lrhmtcncsid2dpdata

A systematic study on the recommender systems in the e-commerce

Pegah Malekpour Alamdari, Nima Jafari Navimipour, Mehdi Hosseinzadeh, Ali Asghar Safaei, Aso Darwesh
2020 IEEE Access  
So, Recommender Systems (RSs) are a solution to overcome the information overload problem. They provide personalized recommendations to improve user satisfaction.  ...  The present article illustrates a comprehensive and Systematic Literature Review (SLR) regarding the papers published in the field of e-commerce recommender systems.  ...  They schemed a multi-mode recommender system in e-commerce to improve accuracy and comprehensively of recommendations.  ... 
doi:10.1109/access.2020.3002803 fatcat:kahxu2a5ezaohniix3rt74crhi

Fuzzy AHP and TOPSIS in Cross Domain Collaboration Recommendation with Fuzzy Visualization Representation

Maslina Zolkepli, Dept. of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia, Teh Noranis Mohd. Aris
2020 International Journal of Machine Learning and Computing  
Existing cross-domain recommendation tackles the problem of sparsity, scalability, cold-start and serendipity issues found in single-domain, therefore the combination of fuzzy AHP and TOPSIS with visualization  ...  Cross domain collaboration recommendation method is proposed by combining fuzzy Analytic Hierarchy Process (AHP), fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and fuzzy  ...  It compares the sparsity, scalability, cold-start and serendipity issues found in single-domain recommendation system.  ... 
doi:10.18178/ijmlc.2020.10.6.1000 fatcat:ddzbaq7rhfbhhns5uo2t34okom

Fuzzy AHP and TOPSIS in Cross Domain Collaboration Recommendation with Fuzzy Visualization Representation

Maslina Zolkepli, Dept. of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia, Teh Noranis Mohd. Aris
2019 International Journal of Machine Learning and Computing  
Existing cross-domain recommendation tackles the problem of sparsity, scalability, cold-start and serendipity issues found in single-domain, therefore the combination of fuzzy AHP and TOPSIS with visualization  ...  Cross domain collaboration recommendation method is proposed by combining fuzzy Analytic Hierarchy Process (AHP), fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and fuzzy  ...  It compares the sparsity, scalability, cold-start and serendipity issues found in single-domain recommendation system.  ... 
doi:10.18178/ijmlc.2019.9.6.882 fatcat:the7vnmnsvc7tddly3ugkqebpe

Recommendation System for Voters using Classifier Rule

Sarita Patil
2021 International Journal for Research in Applied Science and Engineering Technology  
Abstract: Recommender System gives suggestions based on the user's preferences and features of items. Ultimately its performance and efficiency depends on these factors and their representations.  ...  In the proposed system classification of the database is done with the help of rules of decision tree and PART in which all the attributes are included whichever given.  ...  Also observed that in recommendation system, user satisfaction might depend not only on accuracy but also on factors such as privacy, data security, diversity, serendipity, labeling, and presentation.  ... 
doi:10.22214/ijraset.2021.38164 fatcat:4gg3nzsrzjci5guz6z6ilodxge

Assessment Methods for Evaluation of Recommender Systems: A Survey

Madhusree Kuanr, Puspanjali Mohapatra
2021 Foundations of Computing and Decision Sciences  
This paper surveys and organizes the concepts and definitions of various metrics to assess recommender systems.  ...  But an evaluation of the recommender system is an important factor as it involves the trust of the user in the system.  ...  Using case-based reasoning and social trust to improve the performance of recommender system in e-commerce.  ... 
doi:10.2478/fcds-2021-0023 fatcat:e2ocoh7hhnastms6q3a6pbgoyu

News Recommender System: A review of recent progress, challenges, and opportunities [article]

Shaina Raza, Chen Ding
2021 arXiv   pre-print
In the first part, we present an overview of the conventional recommendation solutions, datasets, evaluation criteria beyond accuracy and recommendation platforms being used in NRS.  ...  In this paper, we highlight the major challenges faced by the news recommendation domain and identify the possible solutions from the state-of-the-art.  ...  Acknowledgment: This work is partially sponsored by Natural Science and Engineering Research Council of Canada (grant 2020-04760).  ... 
arXiv:2009.04964v4 fatcat:s7jl63nwm5e55myezsxpzquuje

Cross-Domain Recommender Systems [chapter]

Iván Cantador, Ignacio Fernández-Tobías, Shlomo Berkovsky, Paolo Cremonesi
2015 Recommender Systems Handbook  
Cross-domain recommender systems, thus, aim to generate or enhance recommendations in a target domain by exploiting knowledge from source domains.  ...  In this chapter, we formalize the cross-domain recommendation problem, unify the perspectives from which it has been addressed, analytically categorize, describe and compare prior work, and identify open  ...  On the one hand, the system must collect "enough" ratings in order to learn the users' preferences and improve the accuracy of recommendations.  ... 
doi:10.1007/978-1-4899-7637-6_27 fatcat:4kregbpxajbnxmg6xywfmm22ki
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