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Research paper recommender system evaluation

Joeran Beel, Stefan Langer, Marcel Genzmehr, Bela Gipp, Corinna Breitinger, Andreas Nürnberger
2013 Proceedings of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation - RepSys '13  
Over 80 approaches for academic literature recommendation exist today. The approaches were introduced and evaluated in more than 170 research articles, as well as patents, presentations and blogs.  ...  Due to these and several other shortcomings described in this paper, we conclude that it is currently not possible to determine which recommendation approaches for academic literature are the most promising  ...  Discuss the suitability of offline evaluations for evaluating research paper recommender systems (we started this already with the preliminary conclusion that offline evaluations are unsuitable in many  ... 
doi:10.1145/2532508.2532512 dblp:conf/recsys/BeelLGGBN13 fatcat:fenaekxxszaixda3xrq52i7ray

Stream-Based Recommendations: Online and Offline Evaluation as a Service [chapter]

Benjamin Kille, Andreas Lommatzsch, Roberto Turrin, András Serény, Martha Larson, Torben Brodt, Jonas Seiler, Frank Hopfgartner
2015 Lecture Notes in Computer Science  
The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to evaluate and optimize news recommender algorithms online and offline.  ...  The framework makes possible the reproducible evaluation of recommender algorithms for stream data, taking into account recommender precision as well as the technical complexity of the recommender algorithms  ...  Further, the Idomaar framework for offline evaluation of stream recommendation is a powerful tool that allowing multi-dimensional evaluation of recommender systems "as a service".  ... 
doi:10.1007/978-3-319-24027-5_48 fatcat:vucqtwml3rgtjbmr3x4mwafmqa

Report on the workshop on reproducibility and replication in recommender systems evaluation (RepSys)

Alejandro Bellogín, Pablo Castells, Alan Said, Domonkos Tikk
2014 SIGIR Forum  
Experiment replication and reproduction are key requirements for empirical research methodology, and an important open issue in the field of Recommender Systems.  ...  While the problem of reproducibility and replication has been recognized in the Recommender Systems community, the need for a clear solution remains largely unmet, which motivates the main questions addressed  ...  Acknowledgements We would like to thank the organizers of ACM RecSys for providing a venue for this workshop.  ... 
doi:10.1145/2641383.2641389 fatcat:oizjlpkbkves3b5a2irwa53x2m

Adaptive User Modelling in AthosMail [chapter]

Kristiina Jokinen, Kari Kanto, Jyrki Rissanen
2004 Lecture Notes in Computer Science  
In this paper we discuss the adaptive User Model component of the AthosMail system, and describe especially the Cooperativity Model which produces recommendations for the appropriate explicitness of the  ...  The model consists of an offline and an online version, which use somewhat different input parameters, due to their different functionality in the system.  ...  We want to thank all the project participants for cooperation and discussions.  ... 
doi:10.1007/978-3-540-30111-0_12 fatcat:ygyinm5ehzg4ngl42hk4qskaom

A Comparison of Offline Evaluations, Online Evaluations, and User Studies in the Context of Research-Paper Recommender Systems [chapter]

Joeran Beel, Stefan Langer
2015 Lecture Notes in Computer Science  
The evaluation of recommender systems is key to the successful application of recommender systems in practice.  ...  However, although offline evaluations theoretically might have some inherent value, we conclude that in practice, offline evaluations are probably not suitable to evaluate recommender systems, particularly  ...  If one had trusted the offline evaluation, one had never considered stereotype and citation-based recommendations to be a worthwhile option.  ... 
doi:10.1007/978-3-319-24592-8_12 fatcat:l6aklaw7bzb6piwd6dp3ya6fja

The LKPY Package for Recommender Systems Experiments: Next-Generation Tools and Lessons Learned from the LensKit Project [article]

Michael D. Ekstrand
2018 arXiv   pre-print
In this paper, we reflect on the LensKit project, particularly on our experience using it for offline evaluation experiments, and describe the next-generation LKPY tools for enabling new offline evaluations  ...  Since 2010, we have built and maintained LensKit, an open-source toolkit for building, researching, and learning about recommender systems.  ...  stages of the offline recommender system evaluation lifecycle.  ... 
arXiv:1809.03125v1 fatcat:xejlk7zjcrgz5fchgfii6iwove

Revisiting offline evaluation for implicit-feedback recommender systems

Olivier Jeunen
2019 Proceedings of the 13th ACM Conference on Recommender Systems - RecSys '19  
Recommender systems are typically evaluated in an offline setting.  ...  CCS CONCEPTS • Information systemsRecommender systems; Evaluation of retrieval results.  ...  CONCLUSION In this paper, we have presented the key differences between onand offline evaluation methodologies for implicit feedback recommender systems.  ... 
doi:10.1145/3298689.3347069 dblp:conf/recsys/Jeunen19 fatcat:tlm64i2mbza6hequt4xyrhl4zu

Evaluation Infrastructures for Academic Shared Tasks

Johann Schaible, Timo Breuer, Narges Tavakolpoursaleh, Bernd Müller, Benjamin Wolff, Philipp Schaer
2020 Datenbank-Spektrum  
In addition, we introduce an evaluation infrastructure concept design aiming at reducing the shortcomings in shared tasks for search and recommender systems.  ...  Due to these requirements, small to mid-size academic search systems cannot evaluate their retrieval system in-house. Evaluation infrastructures for shared tasks alleviate this situation.  ...  Either the option for an online evaluation or the ability for reproducibility was not given, which poses a problem for validating user-centric experiment results.  ... 
doi:10.1007/s13222-020-00335-x fatcat:f7lj6fr4n5hazoqtywrulw7b4u

Adaptation and user expertise modelling in AthosMail

Kristiina Jokinen
2006 Universal Access in the Information Society  
The article also discusses methods for the evaluation of adaptive user models and presents results from the AthosMail evaluation.  ...  The User Model produces recommendations of the system's appropriate reaction depending on the user's observed competence level, monitored and computed on the basis of the user's interaction with the system  ...  The author would especially like to thank Kari Kanto for his contributions to the design and evaluation of the Cooperativity Model.  ... 
doi:10.1007/s10209-005-0002-z fatcat:bapmuihcrzczxafcuwgih25ujy

Online Application Guidance for Heterogeneous Memory Systems [article]

M. Ben Olson, Brandon Kammerdiener, Kshitij A. Doshi, Terry Jones, Michael R. Jantz
2021 arXiv   pre-print
Additionally, we show that this approach achieves similar performance as a comparable offline profiling-based approach after a short startup period, without requiring separate program execution or offline  ...  This work presents a toolset for addressing the limitations of existing approaches for managing complex memories.  ...  The offline configuration always uses the same program input for the profile and evaluation runs.  ... 
arXiv:2110.02150v1 fatcat:4aog3w6v3bd2zfhcll7m4npi2m

Accelerated learning from recommender systems using multi-armed bandit [article]

Meisam Hejazinia, Kyler Eastman, Shuqin Ye, Abbas Amirabadi, Ravi Divvela
2019 arXiv   pre-print
The gold standard for evaluating recommendation algorithms has been the A/B test since it is an unbiased way to estimate how well one or more algorithms compare in the real world.  ...  Evaluating recommender system algorithms is a hard task, given all the inherent bias in the data, and successful companies must be able to rapidly iterate on their solution to maintain their competitive  ...  ACKNOWLEDGMENTS The authors would like to thank Travis Brady, Pavlos Mitsoulis Ntompos, Ben Dundee, Kurt Smith, and John Meakin for their internal review of this paper and their helpful feedback.  ... 
arXiv:1908.06158v1 fatcat:7rp3l5ea25feliymdm6cyeuska

Personalized Re-ranking for Improving Diversity in Live Recommender Systems [article]

Yichao Wang, Xiangyu Zhang, Zhirong Liu, Zhenhua Dong, Xinhua Feng, Ruiming Tang, Xiuqiang He
2020 arXiv   pre-print
Therefore, we propose a personalized re-ranking model for improving diversity of the recommendation list in real recommender systems.  ...  Users of industrial recommender systems are normally suggesteda list of items at one time. Ideally, such list-wise recommendationshould provide diverse and relevant options to the users.  ...  Users in industrial recommender systems are normally recommended a list of items at one time. Ideally, such list-wise recommendation should provide diverse and relevant options to the users.  ... 
arXiv:2004.06390v2 fatcat:eos6mbwxpfbqjaz5kgeuldi4ka

Optimizing and Evaluating Stream-Based News Recommendation Algorithms [chapter]

Andreas Lommatzsch, Sebastian Werner
2015 Lecture Notes in Computer Science  
The evaluation shows that our approach allows us to find optimal recommender algorithms for a given hardware setting.  ...  We present an offline evaluating framework allowing us the efficient optimizing of recommender algorithms taking into account the available hardware resources.  ...  Instead of waiting hours for 10,000 recommendation request, an offline test can simulate and evaluate 10,000 requests within minutes.  ... 
doi:10.1007/978-3-319-24027-5_40 fatcat:xwfo5uh4szbq3ekybzk5jtavzq

Recommending Users: Whom to Follow on Federated Social Networks [article]

Jan Trienes, Andrés Torres Cano, Djoerd Hiemstra
2018 arXiv   pre-print
Due to their recent emergence, recommender systems do not exist for federated social networks, yet.  ...  We present an offline and online evaluation of two recommendation strategies: a collaborative filtering recommender based on BM25 and a topology-based recommender using personalized PageRank.  ...  We evaluate the systems in an offline and online scenario. For the offline evaluation, we collect an unbiased sample of the Mastodon user graph.  ... 
arXiv:1811.09292v1 fatcat:3pnplfmf3rb7zkerwpil7q3tpu

An Experiment to Discover Usability Guidelines for Designing Mobile Tourist Apps

Eva Garcia-Lopez, Antonio Garcia-Cabot, Luis de-Marcos, António Moreira-Teixeira, Miguel López-Benítez
2021 Wireless Communications and Mobile Computing  
a map, working offline, and showing a tourist's current location.  ...  This paper presents a research study with two objectives: analyzing the most common usability problems in mobile apps for tourism and proposing recommendations for improving the usability of those apps  ...  Acknowledgments We would like to acknowledge the support by the Junta de Comunidades de Castilla-La Mancha for funding the first author with a postdoctoral training grant for carrying out this work.  ... 
doi:10.1155/2021/2824632 fatcat:hdlmwrvu65bihn52sudkapfa2e
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