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View all- Chi AChen LChang YLee SChang J(2023)Learning to Paraphrase Sentences to Different Complexity LevelsTransactions of the Association for Computational Linguistics10.1162/tacl_a_0060611(1332-1354)Online publication date: 13-Nov-2023
Towards a Better Learning of Near-Synonyms: Automatically Suggesting Example Sentences via Fill in the Blank
Pages 293 - 302
Abstract
Language learners are confused by near-synonyms and often look for answers from the Web. However, there is little to aid them in sorting through the overwhelming load of information that is offered. In this paper, we propose a new research problem: suggesting example sentences for learning word distinctions. We focus on near-synonyms as the first step. Two kinds of one-class classifiers, the GMM and BiLSTM models, are used to solve fill-in-the-blank (FITB) questions and further to select example sentences which best differentiate groups of near-synonyms. Experiments are conducted on both an open benchmark and a private dataset for the FITB task. Experiments show that the proposed approach yields an accuracy of 73.05% and 83.59% respectively, comparable to state-of-the-art multi-class classifiers. Learner study further shows the results of the example sentence suggestion by the learning effectiveness and demonstrates the proposed model indeed is more effective in learning near-synonyms compared to the resource-based models.
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Index Terms
- Towards a Better Learning of Near-Synonyms: Automatically Suggesting Example Sentences via Fill in the Blank
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Published In
April 2017
1738 pages
ISBN:9781450349147
- General Chairs:
- Rick Barrett,
- Rick Cummings,
- Program Chairs:
- Eugene Agichtein,
- Evgeniy Gabrilovich
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- IW3C2: International World Wide Web Conference Committee
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International World Wide Web Conferences Steering Committee
Republic and Canton of Geneva, Switzerland
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Published: 03 April 2017
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View all- Chi AChen LChang YLee SChang J(2023)Learning to Paraphrase Sentences to Different Complexity LevelsTransactions of the Association for Computational Linguistics10.1162/tacl_a_0060611(1332-1354)Online publication date: 13-Nov-2023
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