Paper: Multi-Relational Latent Semantic Analysis

ACL ID D13-1167
Title Multi-Relational Latent Semantic Analysis
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013

We present Multi-Relational Latent Seman- tic Analysis (MRLSA) which generalizes La- tent Semantic Analysis (LSA). MRLSA pro- vides an elegant approach to combining mul- tiple relations between words by construct- ing a 3-way tensor. Similar to LSA, a low- rank approximation of the tensor is derived using a tensor decomposition. Each word in the vocabulary is thus represented by a vec- tor in the latent semantic space and each re- lation is captured by a latent square matrix. The degree of two words having a specific relation can then be measured through sim- ple linear algebraic operations. We demon- strate that by integrating multiple relations from both homogeneous and heterogeneous information sources, MRLSA achieves state- of-the-art performance on existing benchmark datasets for two ...