Scalability Issues of NER using Multi-Class Support Vector Machines

Language: English

Published by LAP LAMBERT Academic Publishing, 2016

365986045X / 9783659860454

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nach der Bestellung gedruckt Neuware - Printed after ordering - Named Entity Recognition (NER) is designed to extract and to categorize rigid designators in written text such as proper names, scientific species, and temporary expressions. There has been increasing interest in this area of research since the early 90's. In this book, we present a pattern shifting away from handcrafted rules, and towards machine learning techniques. Still, latest machine learning techniques have a problem with annotated data accessibility, which is a serious drawback in building and keeping large-scale Named Entity Recognition systems. In this book, we present a new model called as Multi class Support Vector Machine for workflow scheduling in cloud. This workflow scheduling provides a framework for scheduling the entity identification with multiclass Support Vector Machine classifier. The algorithm for the scheduling of resources in cloud called as improved allocation, which continuously and vigorously reallocates multiple types of named entities to the cloud resources to fulfill the cost and performance requirements. This book shows how to create a Multi Class SVM classifier for NER system in environment of cloud.

Seller Inventory # 9783659860454

Title
Scalability Issues of NER using Multi-Class Support Vector Machines
Author
Jyothi Bellary
Publisher
LAP LAMBERT Academic Publishing
Publication year
2016
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
365986045X
ISBN 13
9783659860454
Item weight
203 grams
Dimensions
220x150x8 mm

AHA-BUCH GmbH

Einbeck, Germany

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