Comparison Latent Semantic and WordNet Approach for Semantic Similarity Calculation

TL;DR

This paper compares latent semantic analysis and WordNet-based methods for calculating semantic similarity across different domains, evaluating their effectiveness with expert-annotated references.

Contribution

It provides an evaluation of two semantic similarity approaches across multiple domains, aiding in concept mapping and interoperability.

Findings

Latent semantic analysis and WordNet show varying effectiveness depending on domain.

Evaluation results highlight strengths and limitations of each approach.

The study supports improved semantic mapping in heterogeneous information sources.

Abstract

Information exchange among many sources in Internet is more autonomous, dynamic and free. The situation drive difference view of concepts among sources. For example, word 'bank' has meaning as economic institution for economy domain, but for ecology domain it will be defined as slope of river or lake. In this aper, we will evaluate latent semantic and WordNet approach to calculate semantic similarity. The evaluation will be run for some concepts from different domain with reference by expert or human. Result of the evaluation can provide a contribution for mapping of concept, query rewriting, interoperability, etc.