Semantics of Short Texts

A. Daveedu Raju

ISBN 10: 6200507481 / ISBN 13: 9786200507488

Verlag: LAP LAMBERT Academic Publishing Jan 2020, 2020

Beschreibung

This item is printed on demand - it takes 3-4 days longer - Neuware -Understanding short texts is crucial to many applications, but challenges abound. Here we focus on short texts which refer to texts with limited context. These short texts are produced, including Search queries, Tags, Keywords, Conversation or Social posts and containing limited context. Semantic knowledge is required in order to better understand short texts. First, short texts do not always observe the syntax of a written language. As a result, traditional natural language processing tools, ranging from part-of-speech tagging to dependency parsing, cannot be easily applied. Second, short texts usually do not contain sufficient statistical signals to support many state-of-the-art approaches for text mining such as topic modeling. Third, short texts are more ambiguous and noisier and are generated in an enormous volume, which further increases the difficulty to handle them. the book deals the knowledge-intensive approaches for discovering semantics of short texts. 100 pp. Englisch.

Bestandsnummer des Verkäufers 9786200507488

Bibliografische Details

• Titel: Semantics of Short Texts
• Verlag: LAP LAMBERT Academic Publishing Jan 2020
• Erscheinungsjahr: 2020
• Sprache: Englisch
• ISBN-10: 6200507481
• ISBN-13: 9786200507488
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

Understanding short texts is crucial to many applications, but challenges abound. Here we focus on short texts which refer to texts with limited context. These short texts are produced, including Search queries, Tags, Keywords, Conversation or Social posts and containing limited context. Semantic knowledge is required in order to better understand short texts. First, short texts do not always observe the syntax of a written language. As a result, traditional natural language processing tools, ranging from part-of-speech tagging to dependency parsing, cannot be easily applied. Second, short texts usually do not contain sufficient statistical signals to support many state-of-the-art approaches for text mining such as topic modeling. Third, short texts are more ambiguous and noisier and are generated in an enormous volume, which further increases the difficulty to handle them. the book deals the knowledge-intensive approaches for discovering semantics of short texts.