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    Latent Customer Needs Elicitation by Use Case Analogical Reasoning From Sentiment Analysis of Online Product Reviews

    Source: Journal of Mechanical Design:;2015:;volume( 137 ):;issue: 007::page 71401
    Author:
    Zhou, Feng
    ,
    Jianxin Jiao, Roger
    ,
    Linsey, Julie S.
    DOI: 10.1115/1.4030159
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Different from explicit customer needs that can be identified directly by analyzing raw data from the customers, latent customer needs are often implied in the semantics of use cases underlying customer needs information. Due to difficulties in understanding semantic implications associated with use cases, typical text miningbased methods can hardly identify latent customer needs, as opposite to keywords mining for explicit customer needs. This paper proposes a twolayer model for latent customer needs elicitation through use case reasoning. The first layer emphasizes sentiment analysis, aiming to identify explicit customer needs based on the product attributes and ordinary use cases extracted from online product reviews. Fuzzy support vector machines (SVMs) are developed to build sentiment prediction models based on a list of affective lexicons. The second layer is geared toward use case analogical reasoning, to identify implicit characteristics of latent customer needs by reasoning the semantic similarities and differences analogically between the ordinary and extraordinary use cases. Casebased reasoning (CBR) is utilized to perform case retrieval and case adaptation. A case study of Kindle Fire HD 7 in. tablet is developed to illustrate the potential and feasibility of the proposed method.
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      Latent Customer Needs Elicitation by Use Case Analogical Reasoning From Sentiment Analysis of Online Product Reviews

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    http://yetl.yabesh.ir/yetl1/handle/yetl/158846
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    • Journal of Mechanical Design

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    contributor authorZhou, Feng
    contributor authorJianxin Jiao, Roger
    contributor authorLinsey, Julie S.
    date accessioned2017-05-09T01:20:58Z
    date available2017-05-09T01:20:58Z
    date issued2015
    identifier issn1050-0472
    identifier othermd_137_07_071401.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/158846
    description abstractDifferent from explicit customer needs that can be identified directly by analyzing raw data from the customers, latent customer needs are often implied in the semantics of use cases underlying customer needs information. Due to difficulties in understanding semantic implications associated with use cases, typical text miningbased methods can hardly identify latent customer needs, as opposite to keywords mining for explicit customer needs. This paper proposes a twolayer model for latent customer needs elicitation through use case reasoning. The first layer emphasizes sentiment analysis, aiming to identify explicit customer needs based on the product attributes and ordinary use cases extracted from online product reviews. Fuzzy support vector machines (SVMs) are developed to build sentiment prediction models based on a list of affective lexicons. The second layer is geared toward use case analogical reasoning, to identify implicit characteristics of latent customer needs by reasoning the semantic similarities and differences analogically between the ordinary and extraordinary use cases. Casebased reasoning (CBR) is utilized to perform case retrieval and case adaptation. A case study of Kindle Fire HD 7 in. tablet is developed to illustrate the potential and feasibility of the proposed method.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleLatent Customer Needs Elicitation by Use Case Analogical Reasoning From Sentiment Analysis of Online Product Reviews
    typeJournal Paper
    journal volume137
    journal issue7
    journal titleJournal of Mechanical Design
    identifier doi10.1115/1.4030159
    journal fristpage71401
    journal lastpage71401
    identifier eissn1528-9001
    treeJournal of Mechanical Design:;2015:;volume( 137 ):;issue: 007
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian