Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor

Language: English

Published by GRIN Verlag, GRIN Verlag Feb 2018, 2018

3668642338 / 9783668642331

  • Softcover
  • New
See all details

Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

5-star seller

AbeBooks seller since January 23, 2017

Softcover

Condition: New

£ 41.17

£ 50.02 shipping 
Ships from Germany to U.S.A.

Quantity: 1 available

Add to basket
Free 30-day returns

Item description from seller

This item is printed on demand - Print on Demand Titel. Neuware -Scientific Study from the year 2018 in the subject Computer Sciences - Artificial Intelligence, grade: 1, Post Graduate Government College, language: English, abstract: Every natural language contains a large number of words. These words can have different senses in different context; such words with multiple senses are known as sense tagged words. Word sense reflects the basic concept of the word and the words with several meanings cause ambiguity in the sentence, and the process that decides which of the denotation is accurate in the sentence among several meanings of the word is known as Word Sense Disambiguation. Human beings are good at understanding the meaning of the word by reading the sentence but the same task is difficult for a machine: to understand and accurately sense the correct meaning of the word. Machines can easily understand the set of rules and it is a difficult task to create such rules that can easily disambiguate the word in the context. This task is complicated because every natural language has their own set of rules such as grammatical rules, part-of-speech, antonomy, and synonym. Therefore, a machine is trained by special algorithm so that it can tag the word with its correct sense. If the correct sense of the word is determined, that correct sense is helpful in retrieving the basic concepts of the word. As such this is very difficult task for a machine to retrieve the basic definition of word. In this proposed work, K-Nearest Neighbor (KNN) approach is used to disambiguate the sense tagged words. The KNN is based on supervised learning method. The proposed technique evaluates the performance on Hindi sense tagged words and these are obtained from Hindi Wordnet. The results show the effectiveness of the proposed technique in sense tagged words.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch.…

Seller Inventory # 9783668642331

Title
Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor
Author
Jagpreet Sidhu
Publisher
GRIN Verlag, GRIN Verlag Feb 2018
Publication year
2018
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3668642338
ISBN 13
9783668642331
Item weight
141 grams
Dimensions
210x148x7 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

5-star seller

AbeBooks seller since January 23, 2017

Shipping rates from Germany to U.S.A.

Item60 to 60 business days60 to 60 business days
First item£ 50.02£ 62.52
Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.

Payment methods

  • Visa
  • Mastercard
  • American Express
  • Apple Pay
  • Google Pay
  • Check
  • Paypal

Store description

Impressum Thorsten Retsch Buchversand Mimpf2000 Oberölschnitz 16 95517 Emtmannsberg Deutschland Telefon: 09209-2023188 Email: mimpf2000@online.de USt-ID-Nr.: DE 235096871 Wir führen gebrauchte Bücher aus allen Sparten der Literatur

Specialty

Modernes Antiquariat - Bücher von 1960 bis heute

Seller's business information

buchversandmimpf2000

Germany

Impressum

Gesetzliche Anbieterkennung:

Thorsten Retsch
Buchversand Mimpf2000
Oberölschnitz 16
95517 Emtmannsberg
Deutschland
Telefon: 092092023188
E-Mail: order@buchversandmimpf2000.de
USt-IdNr.: DE 235096871

Alternative Streitbeilegung:
Die Europäische Kommission stellt eine Plattform für die außergerichtliche Online-Streitbeilegung (OS-Plattform) bereit, aufrufbar unter http://ec.europa.eu/odr.