Earticle

초록

영어

Until recently, it was expected that the web users’ tagging would be used in classification, recommendation, and information search. However, the users’ subjective decision or infrequent tags with high interrelationship have caused inaccurate results. This research proposes an algorithm to disregard users’ subjective tags and utilize infrequent tags with high semantic similarity using WordNet. Furthermore, to enhance the efficiency of the proposed algorithm, a weighted matrix is proposed. To evaluate the proposed algorithm, the current co-appearing frequency between tag-pairs method, tag-pair semantic similarity extraction algorithm, and tag-pair weight matrix method were analyzed and compared.

목차

Abstract
 1. Introduction
 2. Highly Related Tag-Pairs
  2.1. Tag-pair Weight Matrix Creation System
  2.2. Tag Frequency Extraction
  2.3. Tag-Pair Semantic Similarity using WordNet
  2.4. TSSE Algorithm
  2.5. Tag-Pair Weight Matrix
 3. Experiment and Analysis
  3.1. Extraction of Tag-Pair Co-Appearing Frequency
  3.2. Adaptation of TSSE
  3.3. TWM Matrix with Weight
 4. Conclusion
 Acknowledgements
 References

키워드

저자

• DaeHoon Hwang [ Dept. of Computer Engineering, Gachon University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605