@conference {grycner:akbc2014, title = {A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases}, booktitle = {NeurIPS}, year = {2014}, abstract = {

The task of finding synonymous relational phrases is important in natural language understanding problems such as question answering and paraphrase detection. While this task has been addressed by many previous systems, each of these existing approaches is limited either in expressivity or in scalability. To address this challenge, we present a large-scale statistical relational method for clustering relational phrases using Probabilistic Soft Logic (PSL) [1]. To assess the quality of our approach, we evaluated it relative to a set of baseline methods. The proposed technique was found to outperform the baselines for both clustering and link prediction, and was shown to be scalable enough to be applied to 200,000relational phrases.

}, author = {Adam Grycner and Gerhard Weikum and Jay Pujara and James Foulds and Lise Getoor} }