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A Survey on Serendipity-Oriented Recommendations

Kenta OKU
2013 Journal of Japan Society for Fuzzy Theory and Intelligent Informatics  
Conference on Recommender Systems RecSys ISMIR Proceedings of the 6th International Conference on Music Information Retrieval Three Princes of Serendip Intelligent and Evolutionary Systems, Studies in  ...  and Queryingin Digital Libraries Proceedings of the Twenty First National Con ference on Artificial Intelligence DiveRS Pro ceedings of the Workshop on Novelty and Diversity in Recommender Systems  ... 
doi:10.3156/jsoft.25.1_2 fatcat:5eqzhxty5jgvzbcvaa46glffiy

Serendipity Identification Using Distance-Based Approach

Widhi Hartanto, Noor Akhmad Setiawan, Teguh Bharata Adji
2021 IJITEE (International Journal of Information Technology and Electrical Engineering)  
Consumers expect recommendations that are novel, unexpected, and relevant. It requires the development of a serendipity recommendation system that matches the serendipity data character.  ...  The recommendation system is a method for helping consumers to find products that fit their preferences. However, recommendations that are merely based on user preference are no longer satisfactory.  ...  A recommendation system dealing with this serendipity criteria is known as a serendipity recommendation system.  ... 
doi:10.22146/ijitee.62344 fatcat:4h55v233yrbqbeoji5fnky7qdu

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  
However, one of the current challenges in the area refers to how to properly evaluate the predictions generated by a recommender system.  ...  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.  ...  [33] addressed the issue of the performances of recommender systems in a temporally dynamic system.  ... 
doi:10.1007/s13042-017-0762-9 fatcat:o77u7tg4yva47nlo6vto2xeaee

User Curiosity Factor in Determining Serendipity of Recommender System

Arseto Satriyo Nugroho, Igi Ardiyanto, Teguh Bharata Adji
2021 IJITEE (International Journal of Information Technology and Electrical Engineering)  
Since the concept of a recommendation system is still evolving today, formalizing the definition of serendipity in a recommendation system is very challenging.One known subjective factor of serendipity  ...  Recommender rystem (RS) is created to solve the problem by recommending some items among a huge selection of items that will be useful for the e-commerce users.  ...  SERENDIPITY Serendipity can be measured by comparing the output of a recommendation system with a primitive recommendation system based on accuracy [20] .  ... 
doi:10.22146/ijitee.67553 fatcat:mravfisbhvdwvmo7qfvczqkyfy

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

Valentina Maccatrozzo
2012 Lecture Notes in Computer Science  
To break this "personalization bubble" we introduce the notion of serendipity as a performance measure for recommendation algorithms.  ...  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.  ...  As described above, serendipity in the context of recommender systems is represented by a well balanced mix of diversity, novelty and relevance of the recommended items with respect to the users' interests  ... 
doi:10.1007/978-3-642-35173-0_28 fatcat:5ia7k36ph5havpjo4bfeaoepra

Serendipity in Recommender Systems

Ashishkumar Patel, Kiran Amin
2018 International Journal of Engineering and Technology  
This paper is detailed survey about serendipity in various aspects in study, equations, components, related works and measures of serendipity in RS.  ...  To solve this problem Recommender System (RS) required to explicit preferences and monitoring of implicit behaviour of user. The traditional RS recommends the items to the user based on their choice.  ...  Using Content Based Recommender System Iaquinta et. al. finds the serendipity in digital library [8] .  ... 
doi:10.21817/ijet/2018/v10i1/181001067 fatcat:lacweveofnbivmsdun2orfqo3i

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

Deep Content Analytics Methods To Improve Transparency And Serendipity Of Recommender Systems

Marco De Gemmis
2017 Zenodo  
The talk will show a semantic approach designed to provide explanations of suggestions, and a method for the discovery of hidden correlations among items, exploited to find "serendipitous" recommendations  ...  The talk will provide a basic survey of semantic techniques: top-down approaches, based on the use of different open knowledge sources (ontologies, Wikipedia, DBpedia, BabelNet) bottom-up approaches, based  ...  An Investigation on the Serendipity Problem in Recommender Systems.  ... 
doi:10.5281/zenodo.1000933 fatcat:acbtb6lubjcetb7otubpcmewoi

How does serendipity affect diversity in recommender systems? A serendipity-oriented greedy algorithm

Denis Kotkov, Jari Veijalainen, Shuaiqiang Wang
2018 Computing  
Evaluation metrics The main objective of our algorithm is to improve serendipity of a recommender system. A change of serendipity might affect other properties of a recommender system.  ...  on the definition of serendipity in recommender systems [19, 21, 32] .  ... 
doi:10.1007/s00607-018-0687-5 fatcat:6fiohjom3renncuxrucfzpgvw4


Yuan Cao Zhang, Diarmuid Ó Séaghdha, Daniele Quercia, Tamas Jambor
2012 Proceedings of the fifth ACM international conference on Web search and data mining - WSDM '12  
Recommendation systems exist to help users discover content in a large body of items.  ...  An ideal recommendation system should mimic the actions of a trusted friend or expert, producing a personalised collection of recommendations that balance between the desired goals of accuracy, diversity  ...  This work was in part funded by RCUK through the Horizon Digital Economy Research grant (EP/G065802/1).  ... 
doi:10.1145/2124295.2124300 dblp:conf/wsdm/ZhangSQJ12 fatcat:ajzweapzfvaqvfbsqbxcxm763e

From Chance to Serendipity: Knowledge Workers' Experiences of Serendipitous Social Encounters

Ekaterina Olshannikova, Thomas Olsson, Jukka Huhtamäki, Susanna Paasovaara, Hannu Kärkkäinen
2020 Advances in Human-Computer Interaction  
We provide a detailed account of the experiential characteristics and contextual qualities of the reported instances of social serendipity.  ...  However, serendipity in the context of social encounters has been the subject of few empirical studies.  ...  In the context of information retrieval, a typical example of artificial serendipity is enabling surprising, novel discoveries in content-based recommender systems to improve the diversity of recommendations  ... 
doi:10.1155/2020/1827107 fatcat:3mk7rsafkbdvxlqwtm4vwjmj6e

INDUSTRY_There's Nothing On: The Future of Serendipitous Discovery in Television Interfaces [article]

ACM TVX2018, Ariel Braverman, Maria Cipollone
2018 Figshare  
user research and design processes in future iterations of our products.At a higher level, we strive to engineer the serendipity that delights our users.  ...  At Comcast we aim to continue to discern signals in our data to fulfill user needs lost by a shift in content delivery systems.Having identifying the serendipity gap as an absent user need drives our ongoing  ...  Rejection When recommender systems don't get it right, users lose confidence in the system. TVX-In-Industry  ... 
doi:10.6084/m9.figshare.6651908.v1 fatcat:pwcqyzihnrcmbhtdntzi75pg4a

Assessment Methods for Evaluation of Recommender Systems: A Survey

Madhusree Kuanr, Puspanjali Mohapatra
2021 Foundations of Computing and Decision Sciences  
A recommender system is the subclass of information filtering systems that can anticipate the needs of the user before the needs are recognized by the user in the near future.  ...  The recommender system (RS) filters out important information from a large pool of dynamically generated information to set some important decisions in terms of some recommendations according to the user's  ...  Recommender Systems: A Survey 405 3.3.2.  ... 
doi:10.2478/fcds-2021-0023 fatcat:e2ocoh7hhnastms6q3a6pbgoyu

A serendipity-biased Deepwalk for collaborators recommendation

Zhenzhen Xu, Yuyuan Yuan, Haoran Wei, Liangtian Wan
2019 PeerJ Computer Science  
In this paper, we design a novel recommender system to provide serendipitous scientific collaborators, which learns the serendipity-biased vector representation of each node in the co-author network.  ...  Serendipity in the recommender system has attracted increasing attention from researchers in recent years. Serendipity traditionally denotes the faculty of making surprising discoveries.  ...  Serendipity in recommender systems Increasing researchers are interested in investigating serendipity in recommender systems, wrote a survey to summarize the serendipity problem in recommender systems  ... 
doi:10.7717/peerj-cs.178 pmid:33816831 pmcid:PMC7924530 fatcat:n3hqtt324ffrtdxfbgynnkfrbm

Recommending Serendipitous Items using Transfer Learning

Gaurav Pandey, Denis Kotkov, Alexander Semenov
2018 Proceedings of the 27th ACM International Conference on Information and Knowledge Management - CIKM '18  
Therefore, the efforts in recommender systems recently shifted towards serendipity, but generating serendipitous recommendations is difficult due to the lack of training data.  ...  Therefore, in the absence of any known deep learning algorithms for recommending serendipitous items and the lack of large serendipity oriented datasets, we introduce SerRec our novel transfer learning  ...  RESULTS DISCUSSION Our results mostly corresponded to our expectations and the literature on serendipity in recommender systems, i.e.: a) transfer learning improves serendipity (observation 3), b) serendipity  ... 
doi:10.1145/3269206.3269268 dblp:conf/cikm/PandeyKS18 fatcat:brhmmkne3jcgvcfs5snclolvxm
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