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MyMediaLite
2011
Proceedings of the fifth ACM conference on Recommender systems - RecSys '11
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MyMediaLite is a fast and scalable, multi-purpose library of recommender system algorithms, aimed both at recommender system researchers and practitioners. ...
MyMediaLite is free/open source software, distributed under the terms of the GNU General Public License (GPL). ...
CONCLUSIONS We have presented MyMediaLite, a versatile library of recommender system algorithms for rating and item prediction from positive-only feedback. ...
doi:10.1145/2043932.2043989
dblp:conf/recsys/GantnerRFS11
fatcat:dhtb2dsfanbqvf5pmesepeuhoy
CARSKit: A Java-Based Context-Aware Recommendation Engine
2015
2015 IEEE International Conference on Data Mining Workshop (ICDMW)
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Context-aware recommender system (CARS) emerged as a novel research direction during the past decade and many contextual recommendation algorithms have been proposed. ...
Several recommendation algorithms have been developed and implemented by both commercial and open-source recommendation libraries. ...
MyMediaLite was one of the most popular recommendation libraries but it was no where LensKit only provides the implementation of classical recommendation algorithms, such as user-based and itembased kNN ...
doi:10.1109/icdmw.2015.222
dblp:conf/icdm/ZhengMB15
fatcat:23rjnmje2ngrhf7o6grhyfv2gy
Real-World Recommender Systems for Academia: The Pain and Gain in Building, Operating, and Researching them [Long Version]
[article]
2017
arXiv
pre-print
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Research on recommender systems is a challenging task, as is building and operating such systems. ...
In the past six years, we built three research-article recommender systems for digital libraries and reference managers, and conducted research on these systems. ...
MyMediaLite: A free
recommender system library. Proceedings of the fifth ACM conference on Recommender systems
(pp. 305–308). ACM.
Ge, M., Delgado-Battenfeld, C., & Jannach, D. (2010). ...
arXiv:1704.00156v1
fatcat:izfdxcmmo5dhrpr4ddoxak6cqy
Muse: A Music Recommendation Management System
2014
Zenodo
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MyMediaLite [8] is a library that offers state of the art algorithms for collaborative filtering in particular. ...
A case study of using Apache Mahout, a library for distributed recommenders based on MapReduce can be found in [15] . ...
doi:10.5281/zenodo.1418194
fatcat:3tcdqtw3kngfrb6mka3hlzsyhq
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations
2010
2010 IEEE International Conference on Data Mining
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Cold-start scenarios in recommender systems are situations in which no prior events, like ratings or clicks, are known for certain users or items. ...
We describe a method that maps such entity (e.g. user or item) attributes to the latent features of a matrix (or higherdimensional) factorization model. ...
According to the authors, by assuming Bernoullidistributed observations, fLDA and RLFM would also be suitable for item recommendation with positive and negative feedback; nevertheless, the suitability ...
doi:10.1109/icdm.2010.129
dblp:conf/icdm/GantnerDFRS10
fatcat:zt42li26kjggxbyvu5ay4vpp64
RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms
[article]
2021
arXiv
pre-print
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In the light of this challenge, we propose a unified, comprehensive and efficient recommender system library called RecBole, which provides a unified framework to develop and reproduce recommendation algorithms ...
Such a framework is useful to standardize the implementation and evaluation of recommender systems. The project and documents are released at https://recbole.io/. ...
Indeed, a considerable number of recommender system libraries have been released in the past decade [14, 15, 59, 64, 74] . ...
arXiv:2011.01731v3
fatcat:sxmbj42gkrerhbwb33t5zdpf2i
Real-time top-n recommendation in social streams
2012
Proceedings of the sixth ACM conference on Recommender systems - RecSys '12
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global trend, and it is also able to deliver highly competitive Top-N recommendations faster while using less space than Weighted Regularized Matrix Factorization (WRMF), a state-of-the-art matrix factorization ...
Our novel approach follows a selective sampling strategy to perform online model updates based on active learning principles, that closely simulates the task of identifying relevant items from a pool of ...
The baseline WRMF was run on a machine with a slightly faster CPU (Intel Xeon 2.27GHz). The experiments were conducted using GNU/Linux 64-bit as operating system. ...
doi:10.1145/2365952.2365968
dblp:conf/recsys/Diaz-AvilesDSN12
fatcat:pzemwfmflndn5iqe245p6mwpru
An Improved Hybrid Distributed Collaborative Filtering Model for Recommender Engine using Apache Spark
2018
International Journal of Intelligent Systems and Applications
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The present work keeps an eye on recommender system built with help of Apache Spark. Apart from this, it has been proposed and implemented the bisecting KMeans clustering algorithms. ...
The present scenario there is a serious need of scalability for efficient analytics of big data. ...
Recommendation system is a system used for predicting the right preference to the user. ...
doi:10.5815/ijisa.2018.07.08
fatcat:5nbtew3qizcf7f5okpeh7u6n7y
Are Real-World Place Recommender Algorithms Useful in Virtual World Environments?
2015
Proceedings of the 9th ACM Conference on Recommender Systems - RecSys '15
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To tackle this issue, game-designers usually deploy recommendation services with the aim of making the virtual world a more joyful environment to be connected at. ...
In this context, we present in this paper the results of a project that aims at understanding the mobility patterns of virtual world users in order to derive place recommenders for helping them to explore ...
To run the collaborative-filtering algorithms we have used the recommender systems library MyMediaLite [4] adopting the default settings for the collaborative-filtering recommenders. ...
doi:10.1145/2792838.2799674
dblp:conf/recsys/MarinhoTP15
fatcat:dd7mqs6prfe2rf7tr2kq76dwra
Introducing linked open data in graph-based recommender systems
2017
Information Processing & Management
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In this paper we compare several techniques to automatically feed a graph-based recommender system with features extracted from the Linked Open Data (LOD) cloud. ...
Specifically, we investigated whether the integration of LOD-based features can improve the e↵ectiveness of a graph-based recommender system and to what extent the choice of the features selection technique ...
We adopted the implementations available in MyMediaLite Recommender System library 5 . The overall highest F1 score for each metric is highlighted with (⇤)("). ...
doi:10.1016/j.ipm.2016.12.003
fatcat:mb2nwb2lpveizd5espxbv4ydka
Linked Open Data-enabled Strategies for Top-N Recommendations
2014
ACM Conference on Recommender Systems
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The huge amount of interlinked information referring to different domains, provided by the Linked Open Data (LOD) initiative, could be e↵ectively exploited by recommender systems to deal with the cold-start ...
that have been rated by a few users. ...
Acknowledgments This work fulfils the research objectives of the project "VIN-CENTE -A Virtual collective INtelligenCe ENvironment to develop sustainable Technology Entrepreneurship ecosystems" (PON 02 ...
dblp:conf/recsys/MustoBLGS14
fatcat:t562r2iwwvbdlor7m34deoh5bq
The million song dataset challenge
2012
Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion
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We introduce the Million Song Dataset Challenge: a largescale, personalized music recommendation challenge, where the goal is to predict the songs that a user will listen to, given both the user's listening ...
We explain the taste profile data, our goals and design choices in creating the challenge, and present baseline results using simple, off-the-shelf recommendation algorithms. ...
T.B.M. is supported in part by a NSERC scholarship. B.M. and G.R.G.L. further acknowledge support from Qualcomm, Inc., Yahoo!, Inc., the Hellman Fellowship Program, and the Sloan Foundation. ...
doi:10.1145/2187980.2188222
dblp:conf/www/McFeeBEL12
fatcat:xp7573b2tvhnpgimoczmw2ocsq
Assessing the Impact of a User-Item Collaborative Attack on Class of Users
[article]
2019
arXiv
pre-print
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Collaborative Filtering (CF) models lie at the core of most recommendation systems due to their state-of-the-art accuracy. ...
First, we investigate the effect of attack strategies crafted on a target user in order to push the recommendation of a low-ranking item to a higher position, referred to as user-item attack. ...
The computation of the CF comparative models has been done with the publicly available software library MyMediaLite http://www.mymedialite.net/. ...
arXiv:1908.07968v1
fatcat:qoymqrcg4jfgzgd2agzcbq5r4y
Towards a scalable social recommender engine for online marketplaces
2014
Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion
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server performance and the impact of model updates in a production system. ...
In addition, we evaluate our framework from two perspectives: (a) recommendation algorithms and data sources, and (b) system performance under server stress tests. ...
1 , Graphlab 2 , MyMediaLite 3 , among others [8] ), the deployment of a real-time recommender from scratch which considers a combination of algorithms and data sources, the effect of large volumes of ...
doi:10.1145/2567948.2579245
dblp:conf/www/LacicKPKT14
fatcat:i25nsjgchzctvo5pbvnbide4ra
ProfileRank
2013
Proceedings of the 7th Workshop on Social Network Mining and Analysis - SNAKDD '13
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systems, and viral marketing/advertising campaigns. ...
A convenient property of ProfileRank is that it can be adapted to provide personalized recommendations. ...
We consider a comprehensive set of collaborative filtering techniques implemented by the MyMediaLite 2 recommender system library as baselines. ...
doi:10.1145/2501025.2501033
dblp:conf/kdd/SilvaGMZ13
fatcat:ysuymrspyzd6fpi4l6u4quysje
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