DINFRA: A One Stop Shop for Computing Multilingual Semantic Relatedness

TL;DR

DINFRA is a comprehensive platform that enables easy computation and comparison of multilingual semantic relatedness across twelve languages using multiple distributional semantic models, simplifying research and development tasks.

Contribution

The paper introduces DINFRA, a unified infrastructure that integrates various multilingual DSMs into a user-friendly webservice for large-scale semantic relatedness analysis.

Findings

Supports twelve languages with high accuracy

Provides easy access to multiple DSM configurations

Facilitates large-scale semantic experiments

Abstract

This demonstration presents an infrastructure for computing multilingual semantic relatedness and correlation for twelve natural languages by using three distributional semantic models (DSMs). Our demonsrator - DInfra (Distributional Infrastructure) provides researchers and developers with a highly useful platform for processing large-scale corpora and conducting experiments with distributional semantics. We integrate several multilingual DSMs in our webservice so the end user can obtain a result without worrying about the complexities involved in building DSMs. Our webservice allows the users to have easy access to a wide range of comparisons of DSMs with different parameters. In addition, users can configure and access DSM parameters using an easy to use API.