A Hybrid Approach for Measuring Semantic Similarity between Documents and its Application in Mining the Knowledge Repositories
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 8
Abstract
This paper explains about similarity measure and the relationship between the knowledge repositories. This paper also describes the significance of document similarity measures, algorithms and to which type of text it can be applied Document similarity measures are of full text similarity, paragraph similarity, sentence similarity, semantic similarity, structural similarity and statistical measures. Two different frameworks had been proposed in this paper, one for measuring document to document similarity and the other model which measures similarity between documents to multiple documents. These two proposed models can use any one of the similarity measures in implementation aspect, which is been put forth for further research.
Authors and Affiliations
K. Sumathy, Chidambaram
Segmentation on the Dental Periapical X-Ray Images for Osteoporosis Screening
Segmentation on the trabecular of dental periapical X-Ray images is very important for osteoporosis screening. Existing methods do not perform well in segmenting the trabecular of dental periapical in X-Ray images due to...
Gait Identification using Neural Network
Biometric System has become more important in security and verification of any human, which is under surveillance. Identification from distance is also possible by this technology. Researchers are taking interest to find...
Unifying Modeling Language-Merise Integration Approach for Software Design
Software design is the most crucial step in the software development process that is why it must be given a good care. Software designers must go through many modeling steps to end up with a good design that will allow f...
An Effective Approach to Analyze Algorithms with Linear O(n) Worst-Case Asymptotic Complexity
A theoretical approach of asymptote analyzes the algorithms for approximate time complexity. The worst-case asymptotic complexity classifies an algorithm to a certain class. The asymptotic complexity for algorithms retur...
Clustering of Image Data Using K-Means and Fuzzy K-Means
Clustering is a major technique used for grouping of numerical and image data in data mining and image processing applications. Clustering makes the job of image retrieval easy by finding the images as similar as given i...