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Novelty and Diversity in Recommender Systems [chapter]

Pablo Castells, Neil J. Hurley, Saul Vargas
2015 Recommender Systems Handbook  
In the present work we propose an Information Retrieval approach to the evaluation and enhacement of novelty and diversity in Recommender Systems.  ...  We propose a framework that includes and unifies the main state of the art metrics for novelty and diversity in Recommender Systems, generalizing and extending them with further properties and flexibility  ...  A Unified Metric Framework for Recommendation Novelty and Diversity Evaluation Different evaluation metrics for novelty and diversity in Recommender Systems have been reported in the literature but the  ... 
doi:10.1007/978-1-4899-7637-6_26 fatcat:53veooy4dzgzxcr3volnel46w4

Rank and relevance in novelty and diversity metrics for recommender systems

Saúl Vargas, Pablo Castells
2011 Proceedings of the fifth ACM conference on Recommender systems - RecSys '11  
The Recommender Systems community is paying increasing attention to novelty and diversity as key qualities beyond accuracy in real recommendation scenarios.  ...  diversity of recommendations.  ...  NOVELTY AND DIVERSITY IN RECOMMENDER SYSTEMS Novelty is a highly desirable feature for recommendation: in most scenarios, the purpose of recommendation is inherently linked to a notion of discovery, as  ... 
doi:10.1145/2043932.2043955 fatcat:byrroapfazajxjywcfjh7d5dbe

Diversity and novelty in web search, recommender systems and data streams

Rodrygo L.T. Santos, Pablo Castells, Ismail Sengor Altingovde, Fazli Can
2014 Proceedings of the 7th ACM international conference on Web search and data mining - WSDM '14  
This tutorial aims to provide a unifying account of current research on diversity and novelty in the domains of web search, recommender systems, and data stream processing.  ...  Diversity in Recommender Systems • Motivation and Notions • Novelty and Diversity Enhancement • Novelty and Diversity Evaluation 4.  ...  and novelty in web search, recommender systems, and data streams; • learn the fundamental evaluation metrics and have an overview of past and current evaluation campaigns; • get an overview of other related  ... 
doi:10.1145/2556195.2556199 dblp:conf/wsdm/SantosCAC14 fatcat:xn764sew4bgjzh4du44vinyduq

Novelty and diversity enhancement and evaluation in recommender systems and information retrieval

Saúl Vargas
2014 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14  
Properties such as novelty and diversity have been explored in both fields for assessing and enhancing the usefulness of search results and recommendations. In this doctoral research we study  ...  The development and evaluation of Information Retrieval and Recommender Systems has traditionally focused on the relevance and accuracy of retrieved documents and recommendations, respectively.  ...  Furthermore, the thesis delves into the definition of new methods to both assess and enhance novelty and diversity in recommender systems.  ... 
doi:10.1145/2600428.2610382 dblp:conf/sigir/Vargas14 fatcat:my6jsfk2ongfxc33t6lbelj3fy

New Approaches to Diversity and Novelty in Recommender Systems

Súul Vargas
2011 unpublished
Beyond accuracy, novelty and diversity have attracted increasing interest as quality factors of Recommender Systems (RS) in the last few years.  ...  This paper presents work in progress towards the application of intentoriented IR diversity techniques to the RS field, and the formalization of novelty and diversity metrics for RS.  ...  Item novelty and diversity Together with similarity between items, we have identified three fundamental properties of items in a recommender system related to novelty and diversity: • Discovery: whether  ... 
doi:10.14236/ewic/fdia2011.2 fatcat:5hjovmxgkbdjdaldigt7zbzbcy

Priors for Diversity and Novelty on Neural Recommender Systems

Alfonso Landin, Daniel Valcarce, Javier Parapar, Álvaro Barreiro
2019 Proceedings (MDPI)  
In this work we study how the system behaves in terms of novelty and diversity under different configurations of item prior probability estimations.  ...  Our results show the versatility of the framework and how its behavior can be adapted to the desired properties, whether accuracy is preferred or diversity and novelty are the desired properties, or how  ...  In this work we focus on studying the behavior of the system in terms of diversity and novelty and how the choice of prior information affects the performance of the system in these metrics.  ... 
doi:10.3390/proceedings2019021020 fatcat:ffqewpjtobcgjg6ykrhiibts6u

A knowledge reuse framework for improving novelty and diversity in recommendations

Apurva Pathak, Bidyut Kr. Patra
2015 Proceedings of the Second ACM IKDD Conference on Data Sciences - CoDS '15  
However, recent study shows that novelty and diversity in recommendations are equally important factors from both user and business view points.  ...  In this paper, we introduce a knowledge reuse framework to increase novelty and diversity in the recommended items of individual users while compromising very little recommendation accuracy.  ...  to increase novelty and diversity in recommendation.  ... 
doi:10.1145/2732587.2732590 dblp:conf/cods/PathakP15 fatcat:rcdnvrha3jd3hlont22xp4meui

When Diversity Met Accuracy: A Story of Recommender Systems

Alfonso Landin, Eva Suárez-García, Daniel Valcarce
2018 Proceedings (MDPI)  
Diversity and accuracy are frequently considered as two irreconcilable goals in the field of Recommender Systems.  ...  We performed a battery of experiments measuring precision, diversity and novelty on different algorithms.  ...  The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.  ... 
doi:10.3390/proceedings2181178 fatcat:7kh6wmxqufhyzlpzujad6yjaxa

Recommendation system based on Singular Value Decomposition and Multi-Objective Immune Optimization

Zhengyi Chai, Yalun Li, Yamin Han, Sifeng Zhu
2018 IEEE Access  
However, accuracy and diversity are two conflicting goals for recommendation system.  ...  Traditional recommendation systems focus on the recommendation accuracy, which is not sufficient. In this paper, we also consider the various needs of users to achieve more diverse recommendation.  ...  , novelty and diversity.  ... 
doi:10.1109/access.2018.2842257 fatcat:uzea727v3re4jc2ushrmg24fum

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  
In recent years, more research have proposed some new concepts such as novelty, diversity and serendipity. These concepts have been addressed with the goal to satisfy the users' requirements.  ...  However, one of the current challenges in the area refers to how to properly evaluate the predictions generated by a recommender system.  ...  [38] evaluated their recommender against novelty, diversity, serendipity and also used rank and recall in their metrics. Hurley and Zhang [15] also uses precision in their evaluations.  ... 
doi:10.1007/s13042-017-0762-9 fatcat:o77u7tg4yva47nlo6vto2xeaee

Diversity and Novelty on the Web

Rodrygo L.T. Santos, Pablo Castells, Ismail Sengor Altingovde, Fazli Can
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion  
This tutorial aims to provide a unifying account of current research on diversity and novelty in different web information systems.  ...  In particular, the tutorial will cover the motivations, as well as the most established approaches for producing and evaluating diverse results in search engines, recommender systems, and data streams,  ...  In recent years his research has focused on diversity, novelty and evaluation in IR and recommender systems, with publications in venues such as RecSys and SIGIR.  ... 
doi:10.1145/2740908.2741988 dblp:conf/www/SantosCAC15 fatcat:f64nwvj67vdojlttfadjmpnqpm

Beyond Accuracy Optimization: On the Value of Item Embeddings for Student Job Recommendations [article]

Emanuel Lacic, Dominik Kowald, Markus Reiter-Haas, Valentin Slawicek, Elisabeth Lex
2017 arXiv   pre-print
We evaluate our job recommendation system on a dataset of the Austrian student job portal Studo using prediction accuracy, diversity and an adapted novelty metric.  ...  In this work, we address the problem of recommending jobs to university students.  ...  In this work, we apply the Doc2Vec algorithm [8] to obtain fixed-length job vectors to improve recommendation diversity and novelty.  ... 
arXiv:1711.07762v1 fatcat:uhuzexbrb5gtnhvdr3hfqfsevu

Diversity and novelty in information retrieval

Rodrygo L.T. Santos, Pablo Castells, Ismail Sengor Altingovde, Fazli Can
2013 Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '13  
This tutorial aims to provide a unifying account of current research on diversity and novelty in different IR domains, namely, in the context of search engines, recommender systems, and data streams.  ...  for the multitude of users' needs in modern information retrieval systems, such as search engines and recommender systems.  ...  This tutorial aims to provide a unifying account of current research on diversity and novelty in different IR domains.  ... 
doi:10.1145/2484028.2484187 dblp:conf/sigir/SantosCAC13 fatcat:si7b4du6tber5jym74msqfg3gm

Exploring the Semantic Gap for Movie Recommendations

Mehdi Elahi, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Leonardo Cella, Stefano Cereda, Paolo Cremonesi
2017 Proceedings of the Eleventh ACM Conference on Recommender Systems - RecSys '17  
In the last years, there has been much a ention given to the semantic gap problem in multimedia retrieval systems.  ...  Results from both studies show that the introduction of mise-en-scène features in conjunction with traditional movie a ributes improves both o ine and online quality of recommendations.  ...  diversity and novelty in video recommendations [16] .  ... 
doi:10.1145/3109859.3109908 dblp:conf/recsys/ElahiDMCCC17 fatcat:2yflumh7ubcmxp7dzpv5v2cvym

An Empirical Analysis on Transparent Algorithmic Exploration in Recommender Systems [article]

Kihwan Kim
2021 arXiv   pre-print
Besides, users evaluated that our new interface is better than the conventional mix-in interface in terms of novelty, diversity, transparency, trust, and satisfaction.  ...  To mitigate this risk, recommender systems have mixed items chosen for exploration into a recommendation list, disguising the items as recommendations to elicit feedback on the items to discover the user's  ...  Specifically, revealed exploration not only got higher scores in novelty, diversity, transparency, trust and satisfaction in a user-centric evaluation, but also gathered more implicit feedback on the exploratory  ... 
arXiv:2108.00151v2 fatcat:copt7dvm55acjaysb2uullzexa
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