Earticle

초록

영어

Needs for the collection of data for text mining of the case with many protolanguages or emotional words distributed in SNS and following trends, and the treatment process method of purification of improved data in a previous step are raised. In data collection for mining, the online trend dictionary based on tag was referred and semi-structured data was effectively parsing processed based on tags of dictionaries according to domains of treating languages, and data for analysis was collected. Additionally, there were the cases to show inefficiency in the text processing of the general genre or the limitation of noun extraction, however, it can be suggested as an alternative on searching trend vocabularies which requires the timeliness or the class processing for corpus work of sentiment dictionary.

목차

Abstract
 1. Introduction
 2. Related Researches
  2.1. Definition of Big Data and their Utilizations
  2.2. Analysis of Big Data
 3. Analysis Design
  3.1. Definition of Corpus Trends Directory
  3.2. Trend Dictionary Reference
  3.3 Trend Word Extraction and Analysis
  3.4 Expanded Algorithm of Sentimental Corpus Dictionary
 4. Experiments and Evaluation
  4.1 Extraction Analysis
  4.2 Evaluation Method of Sentimental Words
 5. Conclusions
 References

키워드

저자

• Sungwook Yoon [ Dept. of Multimedia Engineering, Andong National University, Gyeongsangbuk-Do, Republic of Korea ]
• Hyenki Kim [ Dept. of Multimedia Engineering, Andong National University, Gyeongsangbuk-Do, Republic of Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605