9789811083952 - investigations in computational sarcasm (cognitive systems monographs, 37, band 37) von joshi, aditya; bhattacharyya, pushpak; carman, mark j. (3 Ergebnisse)
Sprache: Englisch
Verlag: Singapore, Springer. 2018
Serie: Cognitive Systems Monographs, Buch 23 von 31. Buch 23 von 31 - Cognitive Systems Monographs
- Hardcover
Anbieter: Universitätsbuchhandlung Herta Hold GmbH, Berlin, , DeutschlandUniversitätsbuchhandlung Herta Hold GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenZustand: Gebraucht
EUR 12,00
EUR 30,00 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
xii, 143 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.
Sprache: Englisch
Verlag: Springer Nature Singapore 2018
Serie: Cognitive Systems Monographs, Buch 23 von 31. Buch 23 von 31 - Cognitive Systems Monographs
- Hardcover
Anbieter: Buchpark, Trebbin, , DeutschlandBuchpark
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Sehr gut
EUR 20,82
EUR 105,00 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book describes the authors¿ investigations of computational sarcasm based on the notion of incongruity. In addition, it provides a holistic view of past work in computational sarcasm and the challenges and opportunities that lie ahead. Sarcastic… text is a peculiar form of sentiment expression and computational sarcasm refers to computational techniques that process sarcastic text. To first understand the phenomenon of sarcasm, three studies are conducted: (a) how is sarcasm annotation impacted when done by non-native annotators? (b) How is sarcasm annotation impacted when the task is to distinguish between sarcasm and irony? And (c) can targets of sarcasm be identified by humans and computers. Following these studies, the book proposes approaches for two research problems: sarcasm detection and sarcasm generation. To detect sarcasm, incongruity is captured in two ways: ¿intra-textual incongruity¿ where the authors look at incongruity within the text to be classified (i.e., target text) and ¿context incongruity¿ where the authors incorporate information outside the target text. These approaches use machine-learning techniques such as classifiers, topic models, sequence labelling, and word embeddings. These approaches operate at multiple levels: (a) sentiment incongruity (based on sentiment mixtures), (b) semantic incongruity (based on word embedding distance), (c) language model incongruity (based on unexpected language model), (d) author¿s historical context (based on past text by the author), and (e) conversational context (based on cues from the conversation). In the second part of the book, the authors present the first known technique for sarcasm generation, which uses a template-based approach to generate a sarcastic response to user input. This book will prove to be a valuable resource for researchers working on sentiment analysis, especially as applied to automation in social media.
Sprache: Englisch
Verlag: Springer, Springer 2018
Serie: Cognitive Systems Monographs, Buch 23 von 31. Buch 23 von 31 - Cognitive Systems Monographs
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 112,77
EUR 62,18 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes the authors' investigations of computational sarcasm based on the notion of incongruity. In addition, it provides a holistic view of past work in computational sarcasm and the challenges and opportunities that lie ahead. Sarcastic text i…s a peculiar form of sentiment expression and computational sarcasm refers to computational techniques that process sarcastic text. To first understand the phenomenon of sarcasm, three studies are conducted: (a) how is sarcasm annotation impacted when done by non-native annotators (b) How is sarcasm annotation impacted when the task is to distinguish between sarcasm and irony And (c) can targets of sarcasm be identified by humans and computers. Following these studies, the book proposes approaches for two research problems: sarcasm detection and sarcasm generation. To detect sarcasm, incongruity is captured in two ways: 'intra-textual incongruity' where the authors look at incongruity within the text to be classified (i.e., target text) and 'context incongruity' where the authors incorporate information outside the target text. These approaches use machine-learning techniques such as classifiers, topic models, sequence labelling, and word embeddings. These approaches operate at multiple levels: (a) sentiment incongruity (based on sentiment mixtures), (b) semantic incongruity (based on word embedding distance), (c) language model incongruity (based on unexpected language model), (d) author's historical context (based on past text by the author), and (e) conversational context (based on cues from the conversation). In the second part of the book, the authors present the first known technique for sarcasm generation, which uses a template-based approach to generate a sarcastic response to user input. This book will prove to be a valuable resource for researchers working on sentiment analysis, especially as applied to automation in social media.
