Detecting Negation Scopes for Financial News Sentiment Using Reinforcement Learning

Applying natural language processing to the domain of financial news requires robust methods that process all sentences correctly, including those that are negated. So far, related research commonly utilizes rule-based algorithms to detect negated sentence fragments, named negation scopes. Nonethele...

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Vydané v:	2016 49th Hawaii International Conference on System Sciences (HICSS) s. 1164 - 1173
Hlavní autori:	Prollochs, Nicolas, Feuerriegel, Stefan, Neumann, Dirk
Médium:	Konferenčný príspevok.. Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.01.2016
Predmet:	Conferences Flexible structures Hidden Markov models Learning Learning (artificial intelligence) Manuals Natural language processing News Pragmatics Raw materials Reinforcement Sentences Sentiment analysis Stock markets
ISSN:	1530-1605, 1530-1605
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