Can Distributional Semantic Models identify substitutes and complements in shopping cart data?

Substitutive and Complementary relationships are natural attributes behind products and crucial to identify in order to understand a product’s functional value, in turn consumer needs. Recent research claimed that distributional semantic models can effectively identify and retrieve substitutes and c...

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Main Author: Gaur, Divya
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2018
Online Access:https://eprints.nottingham.ac.uk/54859/
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author Gaur, Divya
author_facet Gaur, Divya
author_sort Gaur, Divya
building Nottingham Research Data Repository
collection Online Access
description Substitutive and Complementary relationships are natural attributes behind products and crucial to identify in order to understand a product’s functional value, in turn consumer needs. Recent research claimed that distributional semantic models can effectively identify and retrieve substitutes and complements for any product in the shopping cart data, but falls short in providing any empirical evaluation. The aim of this dissertation was to test the validity of this hypothesis. Different types of DSMs were implemented and evaluated on shopping cart data for identifying substitutes. The results revealed unexpectedly poor performance of all the DSMs in retrieving appropriate substitutes and provided strong evidence of model’s incapability to capture these relations. Subjected to further evaluation, this study indicated a need for more intricate models to identify complex relationships of substitutes and complements.
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spelling nottingham-548592022-11-25T15:41:19Z https://eprints.nottingham.ac.uk/54859/ Can Distributional Semantic Models identify substitutes and complements in shopping cart data? Gaur, Divya Substitutive and Complementary relationships are natural attributes behind products and crucial to identify in order to understand a product’s functional value, in turn consumer needs. Recent research claimed that distributional semantic models can effectively identify and retrieve substitutes and complements for any product in the shopping cart data, but falls short in providing any empirical evaluation. The aim of this dissertation was to test the validity of this hypothesis. Different types of DSMs were implemented and evaluated on shopping cart data for identifying substitutes. The results revealed unexpectedly poor performance of all the DSMs in retrieving appropriate substitutes and provided strong evidence of model’s incapability to capture these relations. Subjected to further evaluation, this study indicated a need for more intricate models to identify complex relationships of substitutes and complements. 2018-12-01 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/54859/1/Final_Dissertation_DG.pdf Gaur, Divya (2018) Can Distributional Semantic Models identify substitutes and complements in shopping cart data? [Dissertation (University of Nottingham only)]
spellingShingle Gaur, Divya
Can Distributional Semantic Models identify substitutes and complements in shopping cart data?
title Can Distributional Semantic Models identify substitutes and complements in shopping cart data?
title_full Can Distributional Semantic Models identify substitutes and complements in shopping cart data?
title_fullStr Can Distributional Semantic Models identify substitutes and complements in shopping cart data?
title_full_unstemmed Can Distributional Semantic Models identify substitutes and complements in shopping cart data?
title_short Can Distributional Semantic Models identify substitutes and complements in shopping cart data?
title_sort can distributional semantic models identify substitutes and complements in shopping cart data?
url https://eprints.nottingham.ac.uk/54859/