Needs-Centric Searching and Ranking Based on Customer Reviews

Lee, T.Y.; Li, S.; Wei, Ran

doi:10.1109/cecandeee.2008.95

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…내용 기반 분석은 목적에 따라 보다 구체적인 정보를 획득 하기 위하여 사용되었다. Thoreleuchter(2012)는 의견을 작성한 고객정보를 활용하여 잠재적인 미래의 고객을 예측하는 모델 을 제안하였고, Lee(2009), Lee et al(2008) , IPC코드와 텍스트 유사도를 사용한 융합 대상을 선정하는 연구 (Huang et al, 2015), 키워드 유사도를 기반으로 IPC별 인문․기술 융합 현 황을 파악하는 연구 (Kim and Lee, 2016 …”

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User Needs-Based Technology Opportunities in Heterogeneous Fields Using Opinion Mining and Patent Analysis

Jang¹,

Roh²,

Yoon³

2017

Journal of Korean Institute of Industrial Engineers

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In a digital economy, users actively express their needs in many ways. Thus, many researchers analyze what users need and whether they are satisfied or not through opinion mining. In addition, they begin to find technology opportunities in heterogeneous technology fields. But they did not connect users' opinion to technology development process, only focused on natural language processing or marketing or manufacturing area. Also, heterogeneous technology fields are focused on fusion technology. Thus, this study suggests a novel approach that is based on sentimental value and can be applied to exploring technology opportunities in heterogeneous fields. Sentimental value is calculated from users' opinion through sLDA. The heterogeneous technology opportunity is explored by patent analysis. This research contributes to suggesting a hybrid methodology through patent and users' opinion. In addition, it can provide managerial efficiency by suggesting base data onto decision making. †

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User Needs-Based Technology Opportunities in Heterogeneous Fields Using Opinion Mining and Patent Analysis

Jang¹,

Roh²,

Yoon³

2017

Journal of Korean Institute of Industrial Engineers

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On Deriving Indicators from Texts

Kimbrough

Lee

Oktem

2012

Modeling for Decision Support in Network-Based Services

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Abstract. This paper presents and explores the idea of deriving numerical indicators from texts, that is, converting text data to numerical data that has predictive or diagnostic value. One application of such a general capability is to the provisional identification of networks, or rather, of associations within networks. Conversely, given a network structure among entities that are associated with various texts, the network structure can itself contribute usefully to construction of indicators derived from texts. The focus of the paper is on basic concepts and methods for deriving indicators from texts. Much research remains to be done.

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Technology opportunity discovery by structuring user needs based on natural language processing and machine learning

et al. 2019

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Discovering technology opportunities from the opinion of users can promote successful technological development by satisfying the needs of users. However, although previous approaches using opinion mining only have classified various needs of users into positive or negative categories, they cannot derive the main reasons for their opinion. To solve this problem, this research proposes an approach to exploring technology opportunity by structuring user needs with a concept of opinion trigger of objects and functions of the technology-based products. To discover technology opportunity, first, an opinion trigger is identified from review data using Naïve Base classifier and natural language processing. Second, the opinion triggers and patent keywords that have a similar meaning in context are clustered to discover the needs of the user and need-related technology. Then, the sentimental values of needs are calculated through graph-based semi-supervised learning. Finally, the needs of the user are classified in resolving the problem of vacant technology to discover technology opportunity. Then, an R&D strategy of each opportunity is suggested based on opinion triggers, patent keywords, and their property. Based on the concept of opinion trigger-based methodology, a case study is conducted on automobile—related reviews, extracting the customer needs and presenting important R&D projects such as an extracted need (cargo transportation) and its R&D strategy (resolving contradiction). The proposed approach can analyze the needs of user at a functional level to discover new technology opportunities.

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Needs-Centric Searching and Ranking Based on Customer Reviews

Abstract: Online retailers have associated the introduction of user-generated product reviews with increased customer sales and decreased product returns.

Cited by 3 publications

References 26 publications

User Needs-Based Technology Opportunities in Heterogeneous Fields Using Opinion Mining and Patent Analysis

User Needs-Based Technology Opportunities in Heterogeneous Fields Using Opinion Mining and Patent Analysis

On Deriving Indicators from Texts

Technology opportunity discovery by structuring user needs based on natural language processing and machine learning

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