학술논문

Comparison between SSTC and LINGO Algorithms in Clustered Based Semantic Search for Browsing Scholarships
Document Type
Conference
Source
2015 13th International Conference on Frontiers of Information Technology (FIT) Frontiers of Information Technology (FIT), 2015 13th International Conference on. :53-58 Dec, 2015
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Clustering algorithms
Semantics
Crawlers
Scholarships
Databases
Web pages
Search engines
Web Crawler
Clustering
Lingo
Semantic Suffix Tree Clustering (SSTC)
label induction
tree pruning
Language
Abstract
Amount of information available on internet is growing constantly. To explore the vast information search engines are used massively. They usually provide more than the required information. It takes huge amount of our precious time to go through all the information to find the relevant one. To resolve the issue it is best to display information in the form of meaningful clusters. This paper focuses on two of the clustering algorithms, SSTC and LINGO. These algorithms clusters the web results based on the semantics of keyword. The analysis of both the algorithms is performed on browsing scholarships and shows that SSTC has better results than Lingo.