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Documents authored by Tintarev, Nava


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Diversity in News Recommendation (Dagstuhl Perspectives Workshop 19482)

Authors: Abraham Bernstein, Claes de Vreese, Natali Helberger, Wolfgang Schulz, Katharina Zweig, Christian Baden, Michael A. Beam, Marc P. Hauer, Lucien Heitz, Pascal Jürgens, Christian Katzenbach, Benjamin Kille, Beate Klimkiewicz, Wiebke Loosen, Judith Moeller, Goran Radanovic, Guy Shani, Nava Tintarev, Suzanne Tolmeijer, Wouter van Atteveldt, Sanne Vrijenhoek, and Theresa Zueger

Published in: Dagstuhl Manifestos, Volume 9, Issue 1 (2021)


Abstract
News diversity in the media has for a long time been a foundational and uncontested basis for ensuring that the communicative needs of individuals and society at large are met. Today, people increasingly rely on online content and recommender systems to consume information challenging the traditional concept of news diversity. In addition, the very concept of diversity, which differs between disciplines, will need to be re-evaluated requiring an interdisciplinary investigation, which requires a new level of mutual cooperation between computer scientists, social scientists, and legal scholars. Based on the outcome of a interdisciplinary workshop, we have the following recommendations, directed at researchers, funders, legislators, regulators, and the media industry: - Conduct interdisciplinary research on news recommenders and diversity. - Create a safe harbor for academic research with industry data. - Strengthen the role of public values in news recommenders. - Create a meaningful governance framework for news recommenders. - Fund a joint lab to spearhead the needed interdisciplinary research, boost practical innovation, develop reference solutions, and transfer insights into practice.

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Abraham Bernstein, Claes de Vreese, Natali Helberger, Wolfgang Schulz, Katharina Zweig, Christian Baden, Michael A. Beam, Marc P. Hauer, Lucien Heitz, Pascal Jürgens, Christian Katzenbach, Benjamin Kille, Beate Klimkiewicz, Wiebke Loosen, Judith Moeller, Goran Radanovic, Guy Shani, Nava Tintarev, Suzanne Tolmeijer, Wouter van Atteveldt, Sanne Vrijenhoek, and Theresa Zueger. Diversity in News Recommendation (Dagstuhl Perspectives Workshop 19482). In Dagstuhl Manifestos, Volume 9, Issue 1, pp. 43-61, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@Article{bernstein_et_al:DagMan.9.1.43,
  author =	{Bernstein, Abraham and de Vreese, Claes and Helberger, Natali and Schulz, Wolfgang and Zweig, Katharina and Baden, Christian and Beam, Michael A. and Hauer, Marc P. and Heitz, Lucien and J\"{u}rgens, Pascal and Katzenbach, Christian and Kille, Benjamin and Klimkiewicz, Beate and Loosen, Wiebke and Moeller, Judith and Radanovic, Goran and Shani, Guy and Tintarev, Nava and Tolmeijer, Suzanne and van Atteveldt, Wouter and Vrijenhoek, Sanne and Zueger, Theresa},
  title =	{{Diversity in News Recommendation (Dagstuhl Perspectives Workshop 19482)}},
  pages =	{43--61},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2021},
  volume =	{9},
  number =	{1},
  editor =	{Bernstein, Abraham and de Vreese, Claes and Helberger, Natali and Schulz, Wolfgang and Zweig, Katharina and Baden, Christian and Beam, Michael A. and Hauer, Marc P. and Heitz, Lucien and J\"{u}rgens, Pascal and Katzenbach, Christian and Kille, Benjamin and Klimkiewicz, Beate and Loosen, Wiebke and Moeller, Judith and Radanovic, Goran and Shani, Guy and Tintarev, Nava and Tolmeijer, Suzanne and van Atteveldt, Wouter and Vrijenhoek, Sanne and Zueger, Theresa},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.9.1.43},
  URN =		{urn:nbn:de:0030-drops-137456},
  doi =		{10.4230/DagMan.9.1.43},
  annote =	{Keywords: News, recommender systems, diversity}
}
Document
From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442)

Authors: Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, and Justin Zobel

Published in: Dagstuhl Manifestos, Volume 7, Issue 1 (2018)


Abstract
We describe the state-of-the-art in performance modeling and prediction for Information Retrieval (IR), Natural Language Processing (NLP) and Recommender Systems (RecSys) along with its shortcomings and strengths. We present a framework for further research, identifying five major problem areas: understanding measures, performance analysis, making underlying assumptions explicit, identifying application features determining performance, and the development of prediction models describing the relationship between assumptions, features and resulting performance.

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Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, and Justin Zobel. From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442). In Dagstuhl Manifestos, Volume 7, Issue 1, pp. 96-139, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@Article{ferro_et_al:DagMan.7.1.96,
  author =	{Ferro, Nicola and Fuhr, Norbert and Grefenstette, Gregory and Konstan, Joseph A. and Castells, Pablo and Daly, Elizabeth M. and Declerck, Thierry and Ekstrand, Michael D. and Geyer, Werner and Gonzalo, Julio and Kuflik, Tsvi and Lind\'{e}n, Krister and Magnini, Bernardo and Nie, Jian-Yun and Perego, Raffaele and Shapira, Bracha and Soboroff, Ian and Tintarev, Nava and Verspoor, Karin and Willemsen, Martijn C. and Zobel, Justin},
  title =	{{From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442)}},
  pages =	{96--139},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2018},
  volume =	{7},
  number =	{1},
  editor =	{Ferro, Nicola and Fuhr, Norbert and Grefenstette, Gregory and Konstan, Joseph A. and Castells, Pablo and Daly, Elizabeth M. and Declerck, Thierry and Ekstrand, Michael D. and Geyer, Werner and Gonzalo, Julio and Kuflik, Tsvi and Lind\'{e}n, Krister and Magnini, Bernardo and Nie, Jian-Yun and Perego, Raffaele and Shapira, Bracha and Soboroff, Ian and Tintarev, Nava and Verspoor, Karin and Willemsen, Martijn C. and Zobel, Justin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.7.1.96},
  URN =		{urn:nbn:de:0030-drops-98987},
  doi =		{10.4230/DagMan.7.1.96},
  annote =	{Keywords: Information Systems, Formal models, Evaluation, Simulation, User Interaction}
}