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        <title>Product Classification in E-Commerce using Distributional Semantics</title>
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        <namePart type="given">Vivek</namePart>
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    <name type="personal">
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    <name type="personal">
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            <namePart type="given">Yuji</namePart>
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            <namePart type="given">Rashmi</namePart>
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    <abstract>Product classification is the task of automatically predicting a taxonomy path for a product in a predefined taxonomy hierarchy given a textual product description or title. For efficient product classification we require a suitable representation for a document (the textual description of a product) feature vector and efficient and fast algorithms for prediction. To address the above challenges, we propose a new distributional semantics representation for document vector formation. We also develop a new two-level ensemble approach utilising (with respect to the taxonomy tree) path-wise, node-wise and depth-wise classifiers to reduce error in the final product classification task. Our experiments show the effectiveness of the distributional representation and the ensemble approach on data sets from a leading e-commerce platform and achieve improved results on various evaluation metrics compared to earlier approaches.</abstract>
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%0 Conference Proceedings
%T Product Classification in E-Commerce using Distributional Semantics
%A Gupta, Vivek
%A Karnick, Harish
%A Bansal, Ashendra
%A Jhala, Pradhuman
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F gupta-etal-2016-product
%X Product classification is the task of automatically predicting a taxonomy path for a product in a predefined taxonomy hierarchy given a textual product description or title. For efficient product classification we require a suitable representation for a document (the textual description of a product) feature vector and efficient and fast algorithms for prediction. To address the above challenges, we propose a new distributional semantics representation for document vector formation. We also develop a new two-level ensemble approach utilising (with respect to the taxonomy tree) path-wise, node-wise and depth-wise classifiers to reduce error in the final product classification task. Our experiments show the effectiveness of the distributional representation and the ensemble approach on data sets from a leading e-commerce platform and achieve improved results on various evaluation metrics compared to earlier approaches.
%U https://aclanthology.org/C16-1052
%P 536-546

Markdown (Informal)

[Product Classification in E-Commerce using Distributional Semantics](https://aclanthology.org/C16-1052) (Gupta et al., COLING 2016)

• Product Classification in E-Commerce using Distributional Semantics (Gupta et al., COLING 2016)

ACL

• Vivek Gupta, Harish Karnick, Ashendra Bansal, and Pradhuman Jhala. 2016. Product Classification in E-Commerce using Distributional Semantics. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 536–546, Osaka, Japan. The COLING 2016 Organizing Committee.