Items related to Natural Language Processing. A Machine Learning Approach...
Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor - Softcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
Buy New
View this item
£ 42.81
£ 9.53 shipping from Germany to United Kingdom
Destination, rates & speedsSearch results for Natural Language Processing. A Machine Learning Approach...
Seller Image
Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor
Print on DemandSeller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 88 pp. Englisch. Seller Inventory # 9783668642331
Quantity: 2 available
Seller Image
Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783668642331
Quantity: 1 available
Stock Image
Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor
Seller: California Books, Miami, FL, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # I-9783668642331
Quantity: Over 20 available
Seller Image
Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor
Published by
GRIN Verlag, GRIN Verlag Feb 2018, 2018
ISBN 10: 3668642338
ISBN 13: 9783668642331
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. 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.BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt 88 pp. Englisch. Seller Inventory # 9783668642331
Quantity: 2 available
Seller Image
Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor
Seller: preigu, Osnabrück, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor | Jagpreet Sidhu (u. a.) | Taschenbuch | 88 S. | Englisch | 2018 | GRIN Verlag | EAN 9783668642331 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 111533923
Quantity: 5 available
Stock Image
Natural Language Processing. A Machine Learning Approach to Sense Tagged Words using K-Nearest Neighbor
Seller: Mispah books, Redhill, SURRE, United Kingdom
Seller rating 4 out of 5 stars
paperback. Condition: New. New. book. Seller Inventory # ERICA82336686423386
Quantity: 1 available