Learning Element Weighting for Similarity Measures

摘要

Described is a technology for measuring the similarity between two objects (e.g., documents), via a framework that learns the term-weighting function from training data, e.g., labeled pairs of objects, to develop a learned model. A learning procedure tunes the model parameters by minimizing a defined loss function of the similarity score. Also described is using the learning procedure and learned model to detect near duplicate documents.