Learning distributed sentence representations for story segmentation

Traditional sentence representations such as bag-of-words (BOW) and term frequency-inverse document frequency (tf-idf) face the problem of data sparsity and may not generalize well. Neural network based representations such as word/sentence vectors are usually trained in an unsupervised way and lack...

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Main Authors: Yu, Jia, Xie, Lei, Xiao, Xiong, Chng, Eng Siong
格式: Article
語言:English
出版: 2020
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在線閱讀:https://hdl.handle.net/10356/141962
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機構: Nanyang Technological University
語言: English