Time Expression and Named Entity Recognition (Hardcover, 1st ed. 2021)

This book presents a synthetic analysis about the characteristics of time expressions and named entities, and some proposed methods for leveraging these characteristics to recognize time expressions and named entities from unstructured text. For modeling these two kinds of entities, the authors propose a rule-based method that introduces an abstracted layer between the specific words and the rules, and two learning-based methods that define a new type of tagging scheme based on the constituents of the entities, different from conventional position-based tagging schemes that cause the problem of inconsistent tag assignment. The authors also find that the length-frequency of entities follows a family of power-law distributions. This finding opens a door, complementary to the rank-frequency of words, to understand our communicative system in terms of language use.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Socio-Affective Computing, 10
Release date:	August 2021
First published:	2021
Authors:	Xiaoshi Zhong • Erik Cambria
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	96
Edition:	1st ed. 2021
ISBN-13:	978-3-03-078960-2
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-03-078960-8
Barcode:	9783030789602

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!