Results 31 to 40 of about 15,278 (236)
A survey of consumer health question answering systems
AI Magazine, Volume 44, Issue 4, Page 482-507, Winter 2023., 2023 Abstract Consumers are increasingly using the web to find answers to their health‐related queries. Unfortunately, they often struggle with formulating the questions, further compounded by the burden of having to traverse long documents returned by the search engine to look for reliable answers. To ease these burdens for users, automated consumer health
Anuradha Welivita, Pearl Pu
wiley +1 more source
Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions - DEW '09, 2009 This paper presents the task "Coreference Resolution in Multiple Languages" to be run in SemEval-2010 (5th International Workshop on Semantic Evaluations). This task aims to evaluate and compare automatic coreference resolution systems for three different languages (Catalan, English, and Spanish) by means of two ...
Recasens Potau, Marta +4 more
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Integrated Environmental Assessment and Management, Volume 19, Issue 6, Page 1581-1599, November 2023., 2023 Abstract Synthetic pesticides are important agricultural tools that increase crop yield and help feed the world's growing population. These products are also highly regulated to balance benefits and potential environmental and human risks. Public perception of pesticide use, safety, and regulation is an important topic necessitating discussion across a
Inyoung Jun +5 more
wiley +1 more source
SemEval-2015 Task 10: Sentiment Analysis in Twitter [PDF]
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), 2015 Sentiment analysis, sentiment towards a topic, quantification, microblog sentiment analysis; Twitter opinion ...
Rosenthal, Sara +5 more
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SemEval-2023 Task 11: Learning with Disagreements (LeWiDi)
Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023), 2023 NLP datasets annotated with human judgments are rife with disagreements between the judges. This is especially true for tasks depending on subjective judgments such as sentiment analysis or offensive language detection. Particularly in these latter cases, the NLP community has come to realize that the approach of 'reconciling' these different ...
Leonardelli, Elisa +8 more
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Wisdom of crowds and commodity pricing
Journal of Futures Markets, Volume 43, Issue 8, Page 1040-1068, August 2023., 2023 Abstract We extract commodity‐level sentiment from the Twittersphere in 2009–2020. A long–short strategy based on sentiment shifts more than doubles the Sharpe ratio of extant commodity factors. Commodities with lower (higher) sentiment shifts tend to be overvalued (undervalued) when the aggregate market is in backwardation (contango).
John Hua Fan +2 more
wiley +1 more source
TakeLab at SemEval-2017 Task 6: #RankingHumorIn4Pages [PDF]
Proceedings of the 11th International Workshop on Semantic Evaluation
(SemEval-2017), 2017 This paper describes our system for humor ranking in tweets within the SemEval 2017 Task 6: #HashtagWars (6A and 6B). For both subtasks, we use an off-the-shelf gradient boosting model built on a rich set of features, handcrafted to provide the model with the external knowledge needed to better predict the humor in the text.
Ivan Mršić +5 more
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IET Communications, Volume 17, Issue 13, Page 1655-1664, August 2023., 2023 Abstract The above article from IET Communications, published online on 12 November 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Interim Editor‐in‐Chief, Jian Ren, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd.
Latika Jindal +5 more
wiley +1 more source
Applied Sciences, 2023 Relation extraction tasks aim to predict the type of relationship between two entities from a given text. However, many existing methods fail to fully utilize the semantic information and the probability distribution of the output of pre-trained language
Ping Feng +4 more
doaj +1 more source
Food insufficiency and Twitter emotions during a pandemic
Applied Economic Perspectives and Policy, Volume 45, Issue 2, Page 1189-1210, June 2023., 2023 Abstract The COVID‐19 pandemic initially caused worldwide concerns about food insecurity. Tweets analyzed in real‐time may help food assistance providers target food supplies to where they are most urgently needed. In this exploratory study, we use natural language processing to extract sentiments and emotions expressed in food security‐related tweets ...
Stephan J. Goetz +8 more
wiley +1 more source