CAPRA: a comprehensive approach to product ranking using customer reviews

Najmi, Erfan; Hashmi, Khayyam; Malik, Zaki; Rezgui, Abdelmounaam; Khan, Habib Ullah

doi:10.1007/s00607-015-0439-8

Cited by 72 publications

(66 citation statements)

References 26 publications

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“…Najmi et al, 2015 [6] Springer, Journal CAPRA: a comprehensive approach to product ranking using customer reviews Propose a product ranking system that facilitates the online shopping experience by analyzing the reviews for sentiments, evaluating their usefulness, extracting and weighing different product features and aspects, ranking it among similar comparable products, and finally creating a unified rank for each product P20…”

Section: P19mentioning

confidence: 99%

“…It aims to serve appropriate product ranking to improve consumers experience and to expedite consumers purchase decision. It was done by various ranking approaches based on a custom algorithm or specific criteria in [2]- [6] employ product reviews (e.g., numeric rating, text reviews) using sentiment analysis to perform product ranking. Alengadan et al [3] using product aspects to perform product ranking to gear up faster decision-making.…”

Section: ) Product Rankingmentioning

confidence: 99%

“…Many studies perform product ranking using various approach and case studies. Huang [6] employ product reviews (e.g., numeric rating, text reviews) using sentiment analysis to perform product ranking. Alengadan et al [3] perform product ranking using product aspects to gear up faster decision-making.…”

Section: Introductionmentioning

confidence: 99%

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A Systematic Literature Review on the Product Ranking Methods

Najib

Rakhmawati

2019

khif

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The vast amount of online products data such as product properties, or product reviews plays an essential role in providing better information to the consumers to make a purchase decision. Thus, product ranking is a valuable research topic while many methods proposed by researchers in different approaches and case studies. This paper aims to develop a Systematic Literature Review (SLR) to summarise existing research and finding new gaps in product ranking research. We develop SLR by defining inclusion criteria, initiating preliminary findings, selecting primary studies and summarizing the outcome of results. We proposed three dimensions as research questions. It consists of ranking item types of product ranking, approaches of product ranking and dataset characteristics of each study. First, we found three ranking item types of product ranking that indicate what will be ranked in the studies. It consists of product ranking, aspect ranking, and review ranking. Second, there are four approaches, namely: collaborative filtering, content-based recommendation, hybrid-based and knowledge-based. Third, datasets characteristics summarise the information of datasets like the type of data and statistics. Also, we found new gaps by identifying each dimension to positioning for further research in the future.

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Section: P19mentioning

confidence: 99%

Section: ) Product Rankingmentioning

confidence: 99%

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A Systematic Literature Review on the Product Ranking Methods

Najib

Rakhmawati

2019

khif

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“…The general understanding about the Health Information System (HIS) can reveal it as an amalgamation of software, hardware, people and processes to cater to a range of services in a healthcare entity so as to ensure the collaborative work aimed to achieve the goals of the organization (Al-Gharbi et al, 2015;Silver et al, 1995;Khan, 2013a;Awan et al, 2012;Najmi et al, 2015;Heang and Khan, 2015;Ho et al, 2016;Smuts et al, 2017;. The active players in the working group would be the stake holders of the hospital belonging to a range of departments and centres.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Health Information System-A Case Study of Magrabi Hospitals, KSA

ELSaied¹,

Khan²

2017

Journal of Computer Science

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Today's healthcare market has created its niche by adopting emerging technologies and ensuring minimal rate of failures. Embracing integrated Health Information System (HIS) is one such venture that not only helps the organization to excel in the market but also caters to the needs of the public. The present research paper is a case study of HIS implementation of Magrabi hospitals and centres, in Saudi Arabia. Though implementing HIS is a herculean task, with respect to the efforts as well as investment, Magrabi could achieve this task with at most care. The system could promote service efficacy across all the centres and hospitals of Magrabi. The paper analyses the procedures and strategies followed in order to prepare the entity ready for transformation. That is, the method of actualizing the health system implementation is also detailed in this study. Overall, the case research tried to know the extent of improvement took place in all the streams of operations in Magrabi group after automation. To gather this information, data is collected from all the in-charges of respective departments as well as users, who are in managerial cadre. This data is tabulated against various cycles (revenue and payroll). From the opinion of the stakeholders it can be easily understood that HIS has brought a sea change in the service flows of Magrabi group. Apart from the benefits of HIS implementation, the lacunae of the study along with the future research prospects in these lines are suggested for the possible improvements.

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“…Chen et al visualized the market structure from different perspectives and formulated a Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS)-based product selection model [8]. Najmi et al presented a product ranking system that facilitates the online shopping experience according to online evaluations and description on the products [9]. Wu et al developed a two-stage consumer decision model from the risk perspective to understand the role of online reviews in the consumers' Willingness-To-Pay (WTP) [10].…”

Section: Introductionmentioning

confidence: 99%

Selecting Products Considering the Regret Behavior of Consumer: A Decision Support Model Based on Online Ratings

2018

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Abstract:With the remarkable promotion of e-commerce platforms, consumers increasingly prefer to purchase products online. Online ratings facilitate consumers to choose among products. Thus, to help consumers effectively select products, it is necessary to provide decision support methods for consumers to trade online. Considering the decision makers are bounded rational, this paper proposes a novel decision support model for product selection based on online ratings, in which the regret aversion behavior of consumers is formulated. Massive online ratings provided by experienced consumers for alternative products associated with several evaluation attributes are obtained by software finders. Then, the evaluations of alternative products in format of stochastic variables are conducted. To select a desirable alternative product, a novel method is introduced to calculate gain and loss degrees of each alternative over others. Considering the regret behavior of consumers in the product selection process, the regret and rejoice values of alternative products for consumer are computed to obtain the perceived utility values of alternative products. According to the prior order of the evaluation attributes provided by the consumer, the prior weights of attributes are determined based on the perceived utility values of alternative products. Furthermore, the overall perceived utility values of alternative products are obtained to generate a ranking result. Finally, a practical example from Zol.com.cn for tablet computer selection is used to demonstrate the feasibility and practically of the proposed model.

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CAPRA: a comprehensive approach to product ranking using customer reviews

Cited by 72 publications

References 26 publications

A Systematic Literature Review on the Product Ranking Methods

A Systematic Literature Review on the Product Ranking Methods

Implementation of Health Information System-A Case Study of Magrabi Hospitals, KSA

Selecting Products Considering the Regret Behavior of Consumer: A Decision Support Model Based on Online Ratings

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