Measuring Word Relatedness Using Heterogeneous Vector Space Models

Text Relatedness Based on a Word Thesaurus

The computation of relatedness between two fragments of text in an automated manner requires taking into account a wide range of factors pertaining to the meaning the two fragments convey, and the pairwise relations betw…

Mined Semantic Analysis: A New Concept Space Model for Semantic Representation of Textual Data

Mined Semantic Analysis (MSA) is a novel concept space model which employs unsupervised learning to generate semantic representations of text. MSA represents textual structures (terms, phrases, documents) as a Bag of Con…

Duluth : Measuring Degrees of Relational Similarity with the Gloss Vector Measure of Semantic Relatedness

HG2Vec: Improved Word Embeddings from Dictionary and Thesaurus Based Heterogeneous Graph

Learning word embeddings is an essential topic in natural language processing. Most existing works use a vast corpus as a primary source while training, but this requires massive time and space for data pre-processing an…

Weight Initialization in Neural Language Models

Semantic Similarity is an important application which finds its use in many downstream NLP applications. Though the task is mathematically defined, semantic similarity's essence is to capture the notions of similarity im…