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Hits 1 – 20 of 33
1
JOKE RECOMMENDER SYSTEM USING HUMOR THEORY ...
Soumya Agrawal
. - : Purdue University Graduate School, 2020
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2
JOKE RECOMMENDER SYSTEM USING HUMOR THEORY ...
Soumya Agrawal
. - : Purdue University Graduate School, 2020
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3
Metadata record for: The Database of Cross-Linguistic Colexifications, reproducible analysis of cross-linguistic polysemies ...
Scientific Data Curation Team
. - : figshare, 2020
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4
Metadata record for: The Database of Cross-Linguistic Colexifications, reproducible analysis of cross-linguistic polysemies ...
Scientific Data Curation Team
. - : figshare, 2020
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5
Metadata record for: The Database of Cross-Linguistic Colexifications, reproducible analysis of cross-linguistic polysemies ...
Scientific Data Curation Team
. - : figshare, 2019
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6
Hard Synonyms MySQL dump 8.1 ...
Uban, Ana
. - : figshare, 2015
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7
Hard Synonyms MySQL dump 8.1 ...
Uban, Ana
. - : figshare, 2015
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8
Tracking Digitally Consumed News ...
Kleppe, Martijn
;
Meijer, Irene Costera
. - : figshare, 2015
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9
Tracking Digitally Consumed News ...
Kleppe, Martijn
;
Meijer, Irene Costera
. - : figshare, 2015
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10
Microblog-genre noise and impact on semantic annotation accuracy ...
Derczynski, Leon
. - : figshare, 2014
Abstract:
Using semantic technologies for mining and intelligent information access to microblogs is a challenging, emerging research area. Unlike carefully authored news text and other longer content, tweets pose a number of new challenges, due to their short, noisy, context-dependent, and dynamic nature. Semantic annotation of tweets is typically performed in a pipeline, comprising successive stages of language identification, tokenisation, part-of-speech tagging, named entity recognition and entity disambiguation (e.g. with respect to DBpedia). Consequently, errors are cumulative, and earlier-stage problems can severely reduce the performance of final stages. This paper presents a characterisation of genre-specific problems at each semantic annotation stage and the impact on subsequent stages. Critically, we evaluate impact on two high-level semantic annotation tasks: named entity detection and disambiguation. Our results demonstrate the importance of making approaches specific to the genre, and indicate a ...
Keyword:
Applied Computer Science
;
Artificial Intelligence and Image Processing
;
FOS Computer and information sciences
;
FOS Languages and literature
;
Linguistics
URL:
https://dx.doi.org/10.6084/m9.figshare.951943
https://figshare.com/articles/journal_contribution/Microblog_genre_noise_and_impact_on_semantic_annotation_accuracy/951943
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11
Microblog-genre noise and impact on semantic annotation accuracy ...
Derczynski, Leon
. - : figshare, 2014
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12
Temporal Signals Help Label Temporal Relations ...
Derczynski, Leon
. - : figshare, 2014
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13
Temporal Signals Help Label Temporal Relations ...
Derczynski, Leon
. - : figshare, 2014
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14
Analysis of disease mention annotation with mechanical turk ...
Good, Benjamin
. - : figshare, 2014
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15
TwitIE: An Open-Source Information Extraction Pipeline for Microblog Text: slides ...
Bontcheva, Kalina
;
Derczynski, Leon
. - : figshare, 2014
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16
Modeling expert memory search, knowledge access, and decision making: A model of crossword puzzle play ...
Mueller, Shane
;
Kejkaew Thanasuan
. - : figshare, 2014
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17
Disease Mention Annotation with Mechanical Turk ...
Good, Benjamin
. - : figshare, 2014
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18
Disease Mention Annotation with Mechanical Turk ...
Good, Benjamin
. - : figshare, 2014
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19
TwitIE: An Open-Source Information Extraction Pipeline for Microblog Text: slides ...
Bontcheva, Kalina
;
Derczynski, Leon
. - : figshare, 2014
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20
Disease mention annotations in pubtator format ...
Good, Benjamin
. - : figshare, 2014
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