Document Similarity

Research on document similarity has shown that complex representations are not more accurate than the simple bag-of- words. Term clustering, e.g. using latent semantic indexing, word co-occurrences or synonym relations …...

Many tasks in NLP and IR require ef- ficient document similarity computations. Beyond their common application to ex- ploratory data analysis, latent variable topic models have been used to represent …...

This paper addresses the question of how doc- ument classifiers can exploit implicit infor- mation about document similarity to improve document classifier accuracy. We infer doc- ument similarity using simple …...

AbstractThe prevalent way to estimate the similarity of two documents based on word embeddings is to apply the cosine similarity measure to the two centroids obtained from the embedding vectors …...

AbstractWe describe our methods for automatically grading the level of clinical evidence in medical papers, as part of the ALTA 2021 shared task. We use a combination of transfer learning …...

AbstractMeasuring document similarity plays an important role in natural language processing tasks. Most existing document similarity approaches suffer from the information gap caused by context and vocabulary mismatches when comparing …...

AbstractWe present a new scientific document similarity model based on matching fine-grained aspects of texts. To train our model, we exploit a naturally-occurring source of supervision: sentences in the full-text …...