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1
Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents
In: Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II ; https://hal.archives-ouvertes.fr/hal-03635971 ; Matthias Hagen; Suzan Verberne; Craig Macdonald; Christin Seifert; Krisztian Balog; Kjetil Nørvåg; Vinay Setty. Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II, 13186, Springer International Publishing, pp.347-354, 2022, Lecture Notes in Computer Science, 978-3-030-99738-0. ⟨10.1007/978-3-030-99739-7_44⟩ (2022)
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2
Text Representations for Patent Classification
In: http://wing.comp.nus.edu.sg/~antho/J/J13/J13-3009.pdf (2013)
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3
Constructing a broad coverage lexicon for text mining in the patent domain
In: http://www.lrec-conf.org/proceedings/lrec2010/pdf/378_Paper.pdf (2010)
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4
Constructing a broad-coverage lexicon for text mining in the patent domain
In: http://lands.let.kun.nl/literature/oostdijk.2010.4.pdf (2010)
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5
Quantifying the Challenges in Parsing Patent Claims
In: http://lands.let.kun.nl/literature/sverbern.2010.1.pdf (2010)
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6
Evaluating paragraph retrieval for why-QA
In: http://lands.let.kun.nl/literature/sverbern.2008.1.pdf (2008)
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7
Exploring the use of linguistic analysis for answering whyquestions
In: http://lands.let.kun.nl/literature/sverbern.2006.3.pdf
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8
Using skipgrams and PoS-based feature selection for patent classification
In: http://www.clinjournal.org/sites/default/files/4Dhondt2012_0.pdf
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9
Features for automatic discourse analysis of paragraphs
In: http://lands.let.kun.nl/literature/daphne.2009.1.pdf
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10
Patent classification experiments with the Linguistic Classification System LCS
In: http://clef2010.org/resources/proceedings/clef2010labs_submission_49.pdf
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11
How does the Library Searcher behave? A contrastive study of library search against ad-hoc search
In: http://clef2010.org/resources/proceedings/clef2010labs_submission_42.pdf
Abstract: Abstract. We investigated the search behaviour of the library searcher using the log data from The European Library (TEL). We were especially interested in how this behaviour compares to the search behaviour of ad-hoc searchers, represented by log data in the MSN search engine. At first sight, the two data sets mainly differ in the topics of the queries entered and their multi-lingual vs. mono-lingual content. When studying user behaviour, session information is very important: how does the user navigate through the engine’s interface? We visualized the TEL users ’ interactions with the system by creating a transition network for the users ’ intra-session actions. In general, we think that research into user behaviour on the basis of search engine logs can be very informative for the evaluation of search engine interfaces. 1
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.174.2974
http://clef2010.org/resources/proceedings/clef2010labs_submission_42.pdf
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12
Information Foraging Lab
In: http://ceur-ws.org/Vol-1177/CLEF2011wn-CLEF-IP-VerberneEt2011.pdf
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13
General Terms Design
In: http://lands.let.kun.nl/literature/sverbern.2007.1.pdf
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14
Noname manuscript No. (will be inserted by the editor) Learning to Rank for Why-Question Answering
In: http://lands.let.kun.nl/literature/sverbern.2011.1.pdf
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15
Phrase-based Document Categorization
In: http://www.cs.kun.nl/%7Ekees/home/papers/PBDC-chapter.pdf
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16
Retrieval-based Question Answering for Machine Reading Evaluation
In: http://ceur-ws.org/Vol-1177/CLEF2011wn-QA4MRE-Verberne2011.pdf
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17
Learning to Rank QA Data Evaluating Machine Learning Techniques for Ranking Answers to Why-Questions
In: http://lands.let.kun.nl/literature/sverbern.2009.6.pdf
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