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Creating domain dependent Turkish WordNet and SentiNet

Title	Creating domain dependent Turkish WordNet and SentiNet
Author	Arıcan, B. N., Özçelik, M., Aslan, D. B., Sarmış, E., Parlar, S., Yıldız, Olcay Taner
Publication Date:	2021
Publication Place	- Global WordNet Association
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	978-946402731-0
Record ID	a91df4d9-f2f9-4821-9149-126510249e88
Library Location	Computer Science
Date	2021
Sample Text	A WordNet is a thesaurus that has a structured list of words organized depending on their meanings. WordNet represents word senses, all meanings a single lemma may have, the relations between these senses, and their definitions. Another study within the domain of Natural Language Processing is sentiment analysis. With sentiment analysis, data sets can be scored according to the emotion they contain. In the sentiment analysis we did with the data we received on the Tourism WordNet, we performed a domain-specific sentiment analysis study by annotating the data. In this paper, we propose a method to facilitate Natural Language Processing tasks such as sentiment analysis performed in specific domains via creating a specific-domain subset of an original Turkish dictionary. As the preliminary study, we have created a WordNet for the tourism domain with 14,000 words and validated it on simple tasks.

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Özyeğin University

Creating domain dependent Turkish WordNet and SentiNet

Author Arıcan, B. N., Özçelik, M., Aslan, D. B., Sarmış, E., Parlar, S., Yıldız, Olcay Taner

Publication Date 2021

Publication Place - Global WordNet Association

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 978-946402731-0

Record ID a91df4d9-f2f9-4821-9149-126510249e88

Library Location Computer Science

Date 2021

Sample Text A WordNet is a thesaurus that has a structured list of words organized depending on their meanings. WordNet represents word senses, all meanings a single lemma may have, the relations between these senses, and their definitions. Another study within the domain of Natural Language Processing is sentiment analysis. With sentiment analysis, data sets can be scored according to the emotion they contain. In the sentiment analysis we did with the data we received on the Tourism WordNet, we performed a domain-specific sentiment analysis study by annotating the data. In this paper, we propose a method to facilitate Natural Language Processing tasks such as sentiment analysis performed in specific domains via creating a specific-domain subset of an original Turkish dictionary. As the preliminary study, we have created a WordNet for the tourism domain with 14,000 words and validated it on simple tasks.