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Journal article(2023)
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Christine Bauer, Ben Carterette, Nicola Ferro, Norbert Fuhr, Joeran Beel, Timo Breuer, Charles L. A. Clarke, Laura Dietz, Julián Urbano, More authors...
This report documents the program and the outcomes of Dagstuhl Seminar 23031 "Frontiers of Information Access Experimentation for Research and Education", which brought together 38 participants from 12 countries. The seminar addressed technology-enhanced information access (information retrieval, recommender systems, natural language processing) and specifically focused on developing more responsible experimental practices leading to more valid results, both for research as well as for scientific education.The seminar featured a series of long and short talks delivered by participants, who helped in setting a common ground and in letting emerge topics of interest to be explored as the main output of the seminar. This led to the definition of five groups which investigated challenges, opportunities, and next steps in the following areas: reality check, i.e. conducting real-world studies, human-machine-collaborative relevance judgment frameworks, overcoming methodological challenges in information retrieval and recommender systems through awareness and education, results-blind reviewing, and guidance for authors.Date: 15--20 January 2023.Website: https://www.dagstuhl.de/23031.
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This report documents the program and the outcomes of Dagstuhl Seminar 23031 "Frontiers of Information Access Experimentation for Research and Education", which brought together 38 participants from 12 countries. The seminar addressed technology-enhanced information access (information retrieval, recommender systems, natural language processing) and specifically focused on developing more responsible experimental practices leading to more valid results, both for research as well as for scientific education.The seminar featured a series of long and short talks delivered by participants, who helped in setting a common ground and in letting emerge topics of interest to be explored as the main output of the seminar. This led to the definition of five groups which investigated challenges, opportunities, and next steps in the following areas: reality check, i.e. conducting real-world studies, human-machine-collaborative relevance judgment frameworks, overcoming methodological challenges in information retrieval and recommender systems through awareness and education, results-blind reviewing, and guidance for authors.Date: 15--20 January 2023.Website: https://www.dagstuhl.de/23031.
Journal article(2019)
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Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Nava Tintarev, More authors...
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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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.
Conference paper(2019)
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Ryan Clancy, Nicola Ferro, Claudia Hauff, Jimmy Lin, Tetsuya Sakai, Ze Zhong Wu
The Open-Source IR Replicability Challenge (OSIRRC 2019), organized as a workshop at SIGIR 2019, aims to improve the replicability of ad hoc retrieval experiments in information retrieval by gathering a community of researchers to jointly develop a common Docker specification and build Docker images that encapsulate a diversity of systems and retrieval models. We articulate the goals of this workshop and describe the "jig" that encodes the Docker specification. In total, 13 teams from around the world submitted 17 images, most of which were designed to produce retrieval runs for the TREC 2004 Robust Track test collection. This exercise demonstrates the feasibility of orchestrating large, community-based replication experiments with Docker technology. We envision OSIRRC becoming an ongoing community-wide effort to ensure experimental replicability and sustained progress on standard test collections.
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The Open-Source IR Replicability Challenge (OSIRRC 2019), organized as a workshop at SIGIR 2019, aims to improve the replicability of ad hoc retrieval experiments in information retrieval by gathering a community of researchers to jointly develop a common Docker specification and build Docker images that encapsulate a diversity of systems and retrieval models. We articulate the goals of this workshop and describe the "jig" that encodes the Docker specification. In total, 13 teams from around the world submitted 17 images, most of which were designed to produce retrieval runs for the TREC 2004 Robust Track test collection. This exercise demonstrates the feasibility of orchestrating large, community-based replication experiments with Docker technology. We envision OSIRRC becoming an ongoing community-wide effort to ensure experimental replicability and sustained progress on standard test collections.
Journal article(2018)
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Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Nava Tintarev, More Authors...
This paper reports the findings of the Dagstuhl Perspectives Workshop 17442 on performance modeling and prediction in the domains of Information Retrieval, Natural language Processing and Recommender Systems. We present a framework for further research, which identifies 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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This paper reports the findings of the Dagstuhl Perspectives Workshop 17442 on performance modeling and prediction in the domains of Information Retrieval, Natural language Processing and Recommender Systems. We present a framework for further research, which identifies 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.
Journal article(2016)
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Nicola Ferro, Fabio Crestani, Stefano Mizzaro, Giorgio Maria Di Nunzio, Claudia Hauff, Omar Alonso, P Serdyukov, Gianmaria Silvello, Marie-Francine Moens, Josiane Mothe, Fabrizio Silvestri, Jaana Kekäläinen, Paolo Rosso, Paul Clough, Gabriella Pasi, Christina Lioma
The 38th European Conference on Information Retrieval took place from the 20th to the 23rd of March 2016 in Padua, Italy. This report summarizes the conference in terms of the presented keynotes, scientific and social programme, industry day, tutorials, workshops and student support.
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The 38th European Conference on Information Retrieval took place from the 20th to the 23rd of March 2016 in Padua, Italy. This report summarizes the conference in terms of the presented keynotes, scientific and social programme, industry day, tutorials, workshops and student support.