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        <title>Identifying Usage Expression Sentences in Consumer Product Reviews</title>
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        <namePart type="given">Shibamouli</namePart>
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    <name type="personal">
        <namePart type="given">V.G.Vinod</namePart>
        <namePart type="family">Vydiswaran</namePart>
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            <title>Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)</title>
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            <namePart type="given">Greg</namePart>
            <namePart type="family">Kondrak</namePart>
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    <abstract>In this paper we introduce the problem of identifying usage expression sentences in a consumer product review. We create a human-annotated gold standard dataset of 565 reviews spanning five distinct product categories. Our dataset consists of more than 3,000 annotated sentences. We further introduce a classification system to label sentences according to whether or not they describe some “usage”. The system combines lexical, syntactic, and semantic features in a product-agnostic fashion to yield good classification performance. We show the effectiveness of our approach using importance ranking of features, error analysis, and cross-product classification experiments.</abstract>
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%0 Conference Proceedings
%T Identifying Usage Expression Sentences in Consumer Product Reviews
%A Lahiri, Shibamouli
%A Vydiswaran, V.G.Vinod
%A Mihalcea, Rada
%Y Kondrak, Greg
%Y Watanabe, Taro
%S Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F lahiri-etal-2017-identifying
%X In this paper we introduce the problem of identifying usage expression sentences in a consumer product review. We create a human-annotated gold standard dataset of 565 reviews spanning five distinct product categories. Our dataset consists of more than 3,000 annotated sentences. We further introduce a classification system to label sentences according to whether or not they describe some “usage”. The system combines lexical, syntactic, and semantic features in a product-agnostic fashion to yield good classification performance. We show the effectiveness of our approach using importance ranking of features, error analysis, and cross-product classification experiments.
%U https://aclanthology.org/I17-1040
%P 394-403

Markdown (Informal)

[Identifying Usage Expression Sentences in Consumer Product Reviews](https://aclanthology.org/I17-1040) (Lahiri et al., IJCNLP 2017)

• Identifying Usage Expression Sentences in Consumer Product Reviews (Lahiri et al., IJCNLP 2017)

ACL

• Shibamouli Lahiri, V.G.Vinod Vydiswaran, and Rada Mihalcea. 2017. Identifying Usage Expression Sentences in Consumer Product Reviews. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 394–403, Taipei, Taiwan. Asian Federation of Natural Language Processing.