Evaluation of Simple Distributional Compositional Operations on Longer Texts
17047Authors
nan
Abstract
AbstractDistributional semantic models have been effective at representing linguistic semantics at the word level, and more recently research has moved on to the construction of distributional representations for larger segments of text. However, it is not well understood how the composition operators that work well on short phrase-based models scale up to full-length sentences. In this paper we test several simple compositional methods on a sentence-length similarity task and discover that their performance peaks at fewer than ten operations. We also introduce a novel sentence segmentation method that reduces the number of compositional operations.
Keywords
Full Content
nan
Labeled Text
AbstractDistributional semantic models have been effective at representing linguistic semantics at the word level, and more recently research has moved on to the construction of distributional representations for larger segments of text. However, it is not well understood how the composition operators that work well on short phrase-based models scale up to full-length sentences. In this paper we test several simple compositional methods on a sentence-length similarity task and discover that their performance peaks at fewer than ten operations. We also introduce a novel sentence segmentation method that reduces the number of compositional operations.
Publication Details
- Paper ID:
- 17047
- Year:
- 2014
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan