UMBC_EBIQUITY-CORE: Semantic Textual Similarity Systems
Year: 2013
Type: article
Abstract: We describe three semantic text similarity systems developed for the *SEM 2013 STS shared task and the results of the corresponding three runs. All of them used a word similarity feature that combined LSA word similarity and WordNet knowledge. The first run, which achieved the top mean score on the task of all the submissions, used a simple term alignment algorithm. The other two runs, ranked second and fourth, used SVM models to combine a larger sets of features.
DOI: 10.13016/m28w38626
Authors: Han, Lushan, Kashyap, Abhay L., Finin, Tim, Mayfield, James, Weese, Johnathan
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2251291469