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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Veröffentlicht in:	2016 49th Hawaii International Conference on System Sciences (HICSS) S. 1164 - 1173
Hauptverfasser:	Prollochs, Nicolas, Feuerriegel, Stefan, Neumann, Dirk
Format:	Tagungsbericht Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.01.2016
Schlagworte:	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
Online-Zugang:	Volltext
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