conference-paper Open access

Short Text Similarity with Word Embeddings

Research footprint

At a glance

Citations
444
References
43
Comments
0
Paper overview

Abstract

Determining semantic similarity between texts is important in many tasks in information retrieval such as search, query suggestion, automatic summarization and image finding. Many approaches have been suggested, based on lexical matching, handcrafted patterns, syntactic parse trees, external sources of structured semantic knowledge and distributional semantics. However, lexical features, like string matching, do not capture semantic similarity beyond a trivial level. Furthermore, handcrafted patterns and external sources of structured semantic knowledge cannot be assumed to be available in all circumstances and for all domains. Lastly, approaches depending on parse trees are restricted to syntactically well-formed texts, typically of one sentence in length.

Record transparency

Publication details

DOI
10.1145/2806416.2806475
OpenAlex
W2028742638
Document type
conference-paper
Language
EN
Last metadata update
Community

Comments

Log in to join the discussion.

  1. No comments yet. Start the discussion.