Kernel Approach for Classification Using Conditional Random Field: Information Extraction

Pawar, Lokesh; Bajaj, Rohit

ISBN 10: 6204954598 / ISBN 13: 9786204954592

Edité par LAP LAMBERT Academic Publishing, 2022

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Titre : Kernel Approach for Classification Using ...

Éditeur : LAP LAMBERT Academic Publishing

Date d'édition : 2022

Reliure : Couverture souple

Etat : New

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Synopsis :

Extracting useful information from the pool of big data gives birth to new domain known as Information Extraction. The domain of Information Extraction has its genesis in Natural Language Processing (NLP). The fundamental drift in this field takes the birth from various competitions that are focused on the recognition and extraction of named entities such as names of people, organizations etc. As the world become more data oriented by advent of internet, new applications of processing of structured and unstructured data comes in light. Most of the interest is to extract and classify named entities like person, organization and location etc. that is a subtask of Information Extraction known as Entity Extraction and Classification.