SemantiKLUE: Robust Semantic Similarity at Multiple Levels Using Maximum Weight Matching

Thomas Proisl, Stefan Evert, Paul Greiner, Besim Kabashi
2014 Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)  
Being able to quantify the semantic similarity between two texts is important for many practical applications. SemantiKLUE combines unsupervised and supervised techniques into a robust system for measuring semantic similarity. At the core of the system is a word-to-word alignment of two texts using a maximum weight matching algorithm. The system participated in three SemEval-2014 shared tasks and the competitive results are evidence for its usability in that broad field of application.
doi:10.3115/v1/s14-2093 dblp:conf/semeval/ProislEGK14 fatcat:zbzihwseqvh2dos55n6srihbpi