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references.bib

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    @book{JuKa90,
       author = {Karlgren, Jussi},
       institution = {KTH, Computer and Systems Sciences, DSV},
       institution = {Stockholm University},
       publisher = {Department of Computer and Systems Sciences, Stockholm University},
       title = {An algebra for recommendations : Using reader data as a basis for measuring document proximity},
       series = {SYSLAB technical reports},
       number = {179},
       pages = {1--11},
       abstract = {A measure for proximity between documents is defined, based on data from readers. This proximity measure can be further investigated as a tool document retrieval, and as to provide data for concept formation experiments. },
       year = {1990}
    }
    @article{Rendle19,
      author    = {Steffen Rendle and
                   Li Zhang and
                   Yehuda Koren},
      title     = {On the Difficulty of Evaluating Baselines: {A} Study on Recommender
                   Systems},
      journal   = {CoRR},
      volume    = {abs/1905.01395},
      year      = {2019},
      url       = {http://arxiv.org/abs/1905.01395},
      archivePrefix = {arXiv},
      eprint    = {1905.01395},
      timestamp = {Mon, 27 May 2019 13:15:00 +0200},
      biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1905-01395},
      bibsource = {dblp computer science bibliography, https://dblp.org}
    }
    @inproceedings{DeKa11,
    author = {Christian Desrosiers and
                    George Karypis},
    year = {2011},
    month = {01},
    pages = {107--144},
    title = {A Comprehensive Survey of Neighborhood-Based Recommendation Methods},
    booktitle = {Recommender Systems Handbook},
    editor = {P.B. Kantor and F. Ricci and L. Rokach and B. Shapira},
    publisher={Springer},
    doi = {10.1007/978-0-387-85820-3_4}
    }
    @inproceedings{Lops11,
    author = {Pasquale Lops and 
    			   Marco de Gemmis and
    			   Giovanni Semeraro},
    year = {2011},
    month = {01},
    pages = {74--105},
    title = {Content-based Recommender Systems: State of the Art and Trends},
    booktitle = {Recommender Systems Handbook},
    editor = {P.B. Kantor and F. Ricci and L. Rokach and B. Shapira},
    publisher={Springer},
    doi = {10.1007/978-0-387-85820-3_4}
    }
    @article{Kor09,
    author = {Yehuda Koren and 
    			  Robert Bell and
    			  Chris Volinsky},
    year = {2009},
    month = {08},
    pages = {30-37},
    title = {Matrix factorization techniques for recommender systems},
    volume = {42},
    journal = {Computer}
    }
    @inproceedings{Kor08,
    author = {Koren, Yehuda},
    year = {2008},
    month = {08},
    pages = {426-434},
    title = {Factorization meets the neighborhood: A multifaceted collaborative filtering model},
    journal = {Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD'08).},
    doi = {10.1145/1401890.1401944}
    }
    @inproceedings{Kor11,
    author = {Yehuda Koren and Robert Bell},
    year = {2011},
    month = {01},
    pages = {145--186},
    title = {Advances in Collaborative Filtering},
    booktitle = {Recommender Systems Handbook},
    editor = {P.B. Kantor and F. Ricci and L. Rokach and B. Shapira},
    publisher={Springer},
    doi = {10.1007/978-0-387-85820-3_4}
    }
    @misc{Funk06,
      author = {Simon Funk},
      title = {Netflix Update: Try This at Home},
      howpublished = {\url{https://sifter.org/~simon/journal/20061211.html}},
      note = {Accessed: 2019-12-12},
      year = {2006},
      month = {12}
    }
    @inproceedings{Zh08,
    author = {Yunhong Zhou and Dennis Wilkinson and Robert Schreiber and Rong Pan},
    year = {2008},
    month = {06},
    pages = {337-348},
    title = {Large-Scale Parallel Collaborative Filtering for the Netflix Prize},
    doi = {10.1007/978-3-540-68880-8_32}
    }
    @inproceedings{Rus08,
    author = {Ruslan Salakhutdinov and Andriy Mnih},
    year = {2008},
    month = {01},
    pages = {880-887},
    title = {Bayesian probabilistic matrix factorization using Markov chain Monte Carlo},
    volume = {25},
    journal = {Proceedings of the 25th International Conference on Machine Learning},
    doi = {10.1145/1390156.1390267}
    }
    @misc{Koren,
      author = {Yehuda Koren},
      title = {Biography of Yehuda Koren},
      howpublished = {\url{https://ieeexplore.ieee.org/author/37414256700}},
      note = {Accessed: 2019-12-21},
    }
    @misc{Rendle,
      author = {Steffen Rendle},
      title = {Papers of Steffen Rendle},
      howpublished = {\url{https://dblp.org/pers/hd/r/Rendle:Steffen}},
      note = {Accessed: 2020-01-20},
    }
    @article{Kurucz07,
    author = {Miklós Kurucz and András Benczúr and Károly Csalogány},
    year = {2007},
    month = {01},
    pages = {},
    title = {Methods for large scale SVD with missing values},
    journal = {ACM KDDCup 2007}
    }
    @article{Koren09,
    author = {Yehuda Koren},
    year = {2009},
    month = {09},
    pages = {},
    title = {The BellKor solution to the Netflix Grand Prize}
    }
    @article{Harper15,
     author = {Harper, F. Maxwell and Konstan, Joseph A.},
     title = {The MovieLens Datasets: History and Context},
     journal = {ACM Trans. Interact. Intell. Syst.},
     issue_date = {January 2016},
     volume = {5},
     number = {4},
     month = dec,
     year = {2015},
     issn = {2160-6455},
     pages = {19:1--19:19},
     articleno = {19},
     numpages = {19},
     url = {http://doi.acm.org/10.1145/2827872},
     doi = {10.1145/2827872},
     acmid = {2827872},
     publisher = {ACM},
     address = {New York, NY, USA},
     keywords = {Datasets, MovieLens, ratings, recommendations},
    }
    @inproceedings{Rendle13,
    author = {Steffen Rendle},
    year = {2013},
    month = {03},
    pages = {337-348},
    title = {Scaling factorization machines to relational data},
    volume = {6},
    journal = {Proceedings of the VLDB Endowment},
    doi = {10.14778/2535573.2488340}
    }
    @article{Paterek07,
    author = {Arkadiusz Paterek},
    year = {2007},
    month = {01},
    pages = {},
    title = {Improving regularized singular value decomposition for collaborative filtering},
    journal = {Proceedings of KDD Cup and Workshop}
    }
    @article{Dacrema19,
      author    = {Dacrema, Maurizio Ferrari  and 
                    Cremonesi Paolo and Jannach Dietmar},
      title     = {Are We Really Making Much Progress? {A} Worrying Analysis of Recent
                   Neural Recommendation Approaches},
      journal   = {CoRR},
      volume    = {abs/1907.06902},
      year      = {2019},
      url       = {http://arxiv.org/abs/1907.06902},
      archivePrefix = {arXiv},
      eprint    = {1907.06902},
      timestamp = {Tue, 23 Jul 2019 10:54:22 +0200},
      biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1907-06902},
      bibsource = {dblp computer science bibliography, https://dblp.org}
    }
    @article{Dacrema2019,
      title={A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research},
      author={Maurizio Ferrari Dacrema and Simone Boglio and Paolo Cremonesi and Dietmar Jannach},
      journal={ArXiv},
      year={2019},
      volume={abs/1911.07698}
    }
    @inproceedings{Armstrong09,
    author = {Armstrong, Timothy and Moffat, Alistair and Webber, William and Zobel, Justin},
    year = {2009},
    month = {11},
    pages = {601-610},
    title = {Improvements that don’t add up: Ad-hoc retrieval results since},
    doi = {10.1145/1645953.1646031}
    }
    @article{Lin19,
    author = {Lin, Jimmy},
    title = {The Neural Hype and Comparisons Against Weak Baselines},
    year = {2019},
    issue_date = {January 2019},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    volume = {52},
    number = {2},
    issn = {0163-5840},
    url = {https://doi.org/10.1145/3308774.3308781},
    doi = {10.1145/3308774.3308781},
    journal = {SIGIR Forum},
    month = jan,
    pages = {40–51},
    numpages = {12}
    }
    @article{Ludewig18,
      author    = {Ludewig, Jannach},
      title     = {Evaluation of Session-based Recommendation Algorithms},
      journal   = {CoRR},
      volume    = {abs/1803.09587},
      year      = {2018},
      url       = {http://arxiv.org/abs/1803.09587},
      archivePrefix = {arXiv},
      eprint    = {1803.09587},
      timestamp = {Mon, 13 Aug 2018 16:46:25 +0200},
      biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1803-09587},
      bibsource = {dblp computer science bibliography, https://dblp.org}
    }
    @article{Rendle09,
    author = {Rendle, Steffen and Freudenthaler, Christoph and Gantner, Zeno and Schmidt-Thieme, Lars},
    year = {2012},
    month = {05},
    pages = {},
    title = {BPR: Bayesian Personalized Ranking from Implicit Feedback},
    journal = {Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009}
    }
    @inproceedings{Rendle10,
    author = {Rendle, Steffen and Freudenthaler, Christoph and Schmidt-Thieme, Lars},
    title = {Factorizing Personalized Markov Chains for Next-Basket Recommendation},
    year = {2010},
    isbn = {9781605587998},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/1772690.1772773},
    doi = {10.1145/1772690.1772773},
    booktitle = {Proceedings of the 19th International Conference on World Wide Web},
    pages = {811–820},
    numpages = {10},
    keywords = {basket recommendation, markov chain, matrix factorization},
    location = {Raleigh, North Carolina, USA},
    series = {WWW ’10}
    }
    @article{Sterling59,
     ISSN = {01621459},
     URL = {http://www.jstor.org/stable/2282137},
     abstract = {There is some evidence that in fields where statistical tests of significance are commonly used, research which yields nonsignificant results is not published. Such research being unknown to other investigators may be repeated independently until eventually by chance a significant result occurs-an "error of the first kind"-and is published. Significant results published in these fields are seldom verified by independent replication. The possibility thus arises that the literature of such a field consists in substantial part of false conclusions resulting from errors of the first kind in statistical tests of significance.},
     author = {Theodore D. Sterling},
     journal = {Journal of the American Statistical Association},
     number = {285},
     pages = {30--34},
     publisher = {[American Statistical Association, Taylor & Francis, Ltd.]},
     title = {Publication Decisions and Their Possible Effects on Inferences Drawn from Tests of Significance--Or Vice Versa},
     volume = {54},
     year = {1959}
    }
    @inproceedings{Rosenthal79,
      title={The file drawer problem and tolerance for null results.},
      author={Robert S. Rosenthal},
      year={1979}
    }
    @inproceedings{Sculley18,
      title={Winner's Curse? On Pace, Progress, and Empirical Rigor},
      author={D. Sculley and Jasper Snoek and Alexander B. Wiltschko and Ali Rahimi},
      booktitle={ICLR},
      year={2018}
    }