Semantic Matching of Documents from Heterogeneous Collections: A Simple and Transparent Method for Practical Applications
Mark-Christoph Mueller · 2019
We present a very simple, unsupervised method for the pairwise matching of documents from heterogeneous collections.We demonstrate our method with the Concept-Project matching task, which is a binary classification task involving pairs of documents from heterogeneous collections.Although our method only employs standard resources without any domain-or task-specific modifications, it clearly outperforms the more complex system of the original authors.In addition, our method is transparent, because it provides explicit information about how a similarity score was computed, and efficient, because it is based on the aggregation of (pre-computable) word-level similarities.