A Theoretical Analysis of Cross-lingual Semantic Relatedness in Vector Space Models

Semantic relatedness is essential for different text processing tasks, especially in the cross-lingual setting due to the vocabulary mismatch problem. Many concept-based solutions to semantic relatedness have been proposed, which vary in the notions of concept and document representation. In our contribution, we provide a unified model that generalizes over the existing approaches to cross-lingual semantic relatedness. It shows that the main existing solutions represent different ways for constructing the concept space, which result in different document representations and implications for semantic relatedness computation. In particular, it al- lows us to provide theoretical justifications of existing solutions. Through the experimental evaluation, we show that the results support our theoretical findings.