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المؤلفون: Tetsuya Sakai, Sijie Tao, Nuo Chen, Yujing Li, Maria Maistro, Zhumin Chu, Nicola Ferro
المصدر: ACM Transactions on Information Systems.
مصطلحات موضوعية: General Business, Management and Accounting, Computer Science Applications, Information Systems
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المؤلفون: Maria Maistro, Timo Breuer, Philipp Schaer, Nicola Ferro
مصطلحات موضوعية: Media Technology, Library and Information Sciences, Management Science and Operations Research, Computer Science Applications, Information Systems
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6836e01c9d3c77d61687eb012685b80
https://hdl.handle.net/11577/3471915 -
3
المؤلفون: Simone Borg Bruun, Kacper Kenji Leśniak, Mirko Biasini, Vittorio Carmignani, Panagiotis Filianos, Christina Lioma, Maria Maistro
المصدر: Lecture Notes in Computer Science ISBN: 9783031282430
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::e8e42c021ce042f626f68c6699091280
https://doi.org/10.1007/978-3-031-28244-7_12 -
4
المؤلفون: Nazli Goharian, Faegheh Hasibi, Maria Maistro, Suzan Verberne
المصدر: ACM SIGIR Forum. 56:1-2
مصطلحات موضوعية: Hardware and Architecture, Management Information Systems
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5
المؤلفون: K. Selçuk Candan, Guglielmo Faggioli, Nicola Ferro, Lorraine Goeuriot, Bogdan Ionescu, Alexis Joly, Birger Larsen, Maria Maistro, Henning Müller, Florina Piroi
المصدر: SIGIR Forum
مصطلحات موضوعية: Hardware and Architecture, Management Information Systems
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المؤلفون: Maria Maistro, Jakob Grue Simonsen, Lucas Chaves Lima, Christina Lioma
المصدر: Maistro, M, Lima, L C, Simonsen, J G & Lioma, C 2021, Principled Multi-Aspect Evaluation Measures of Rankings . in CIKM 2021-Proceedings of the 30th ACM International Conference on Information and Knowledge Management . Association for Computing Machinery, Inc, pp. 1232-1242, 30th ACM International Conference on Information and Knowledge Management, CIKM 2021, Virtual, Online, Australia, 01/11/2021 . https://doi.org/10.1145/3459637.3482287
Proceedings of the 30th ACM International Conference on Information & Knowledge Management
CIKMمصطلحات موضوعية: FOS: Computer and information sciences, Information retrieval, evaluation, Computer science, Computer Science - Information Retrieval, Single measure, Ranking, Discriminative model, ranking, Evaluation methods, Credibility, partial order, Multi aspect, Relevance (information retrieval), multiple aspects, Information Retrieval (cs.IR)
وصف الملف: application/pdf
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e694f717760c11271594837db624ab4
https://curis.ku.dk/portal/da/publications/principled-multiaspect-evaluation-measures-of-rankings(f8a7c7ac-fb92-457a-92b1-7c7394904737).html -
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المؤلفون: Timo Breuer, Nicola Ferro, Philipp Schaer, Maria Maistro
المساهمون: Hiemstra, Djoerd, Moens, Marie-Francine, Mothe, Josiane, Perego, Raffaele, Potthast, Martin, Sebastiani, Fabrizio
المصدر: Breuer, T, Ferro, N, Maistro, M & Schaer, P 2021, repro_eval : A Python Interface to Reproducibility Measures of System-Oriented IR Experiments . in D Hiemstra, M-F Moens, J Mothe, R Perego, M Potthast & F Sebastiani (eds), Advances in Information Retrieval-43rd European Conference on IR Research, ECIR 2021, Proceedings . Springer, Lecture Notes in Computer Science, vol. 12657 LNCS, pp. 481-486, 43rd European Conference on Information Retrieval, ECIR 2021, Virtual, Online, 28/03/2021 . https://doi.org/10.1007/978-3-030-72240-1_51
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Advances in Information Retrieval
Lecture Notes in Computer Science ISBN: 9783030722395
ECIR (2)مصطلحات موضوعية: FOS: Computer and information sciences, Reproducibility, Interface (Java), Programming language, Computer science, Python (programming language), computer.software_genre, eval, Computer Science - Information Retrieval, Replicability, Evaluation, computer, Information Retrieval (cs.IR), computer.programming_language
وصف الملف: application/pdf
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc29fc0a93cf3d4e004621bdfc734b39
http://hdl.handle.net/11577/3386940 -
8كتاب إلكتروني
المؤلفون: Jaap Kamps, Lorraine Goeuriot, Fabio Crestani, Maria Maistro, Hideo Joho, Brian Davis, Cathal Gurrin, Udo Kruschwitz, Annalina Caputo
نوع المادة: eBook.
الموضوعات: Information storage and retrieval systems, Machine learning, Natural language processing (Computer science), Education—Data processing, Social sciences—Data processing
تصنيفات: COMPUTERS / System Administration / Storage & Retrieval, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Business & Productivity Software / General, COMPUTERS / Speech & Audio Processing, EDUCATION / Computers & Technology, MATHEMATICS / Probability & Statistics / General
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المؤلفون: Nicola Ferro, Claudio Lucchese, Raffaele Perego, Maria Maistro
المصدر: Information retrieval (Boston) 23 (2019): 528–554. doi:10.1007/s10791-019-09366-9
info:cnr-pdr/source/autori:Ferro N.; Lucchese C.; Maistro M.; Perego R./titolo:Boosting learning to rank with user dynamics and continuation methods/doi:10.1007%2Fs10791-019-09366-9/rivista:Information retrieval (Boston)/anno:2019/pagina_da:528/pagina_a:554/intervallo_pagine:528–554/volume:23
Ferro, N, Lucchese, C, Maistro, M & Perego, R 2020, ' Boosting learning to rank with user dynamics and continuation methods ', Information Retrieval Journal, vol. 23, pp. 528–554 . https://doi.org/10.1007/s10791-019-09366-9مصطلحات موضوعية: Iterative and incremental development, Discounting, Boosting (machine learning), Exploit, Settore INF/01 - Informatica, business.industry, Computer science, Library and Information Sciences, Machine learning, computer.software_genre, Continuation methods, Learning to rank, User dynamics, Continuation, Leverage (statistics), Artificial intelligence, Explicit knowledge, business, Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni, computer, Information Systems
وصف الملف: application/pdf
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62c33a6e9aa00a5e530078c1c6a86c41
http://hdl.handle.net/11577/3367833 -
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المؤلفون: Norbert Fuhr, Philipp Schaer, Tetsuya Sakai, Maria Maistro, Timo Breuer, Nicola Ferro, Ian Soboroff
المصدر: Breuer, T, Ferro, N, Fuhr, N, Maistro, M, Sakai, T, Schaer, P & Soboroff, I 2020, How to Measure the Reproducibility of System-oriented IR Experiments . in SIGIR '20 : Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval . Association for Computing Machinery, pp. 349-358, 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China, 25/07/2020 . https://doi.org/10.1145/3397271.3401036
مصطلحات موضوعية: FOS: Computer and information sciences, Reproducibility, Measure (data warehouse), Computer science, 02 engineering and technology, measure, computer.software_genre, 01 natural sciences, Field (computer science), Computer Science - Information Retrieval, Informatik, 010104 statistics & probability, replicability, reproducibility, 020204 information systems, Face (geometry), 0202 electrical engineering, electronic engineering, information engineering, Data mining, Granularity, 0101 mathematics, computer, Information Retrieval (cs.IR)
وصف الملف: application/pdf
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c94b5aeb3014fd1077b6a1f76e241900
https://curis.ku.dk/ws/files/287763015/2010.13447.pdf
