A time-aware hyperlink-induced topic search-based reputation evaluation method for optimal manufacturing service recommendation in distributed peer-to-peer networks

Zhang, Shuai; Xu, Song; Zhang, Wenyu; Yu, Dejian

doi:10.1177/1748301816665018

Cited by 4 publications

(6 citation statements)

References 22 publications

(55 reference statements)

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“…Feng et al proposed a hierarchical and configurable reputation evaluation method based on collaborative filtering (CF) for evaluating the service reputation of the cloud manufacturing enterprises on CMFG service platform [35]. Zhang et al proposed a novel and effective reputation evaluation method, which can calculate the global and dynamic reputation value of an enterprise by using a time-aware hyperlink-induced topic search algorithm [36]. Wang et al proposed a reputation measurement method for cloud services based on feedback levels [37].…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating Reputation of Internet Financial Platform: An Improved Fuzzy Evaluation Approach

You

Hao

Dagestani

et al. 2021

Discrete Dynamics in Nature and Society

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Recent frequent “thunderstorm incidents” of the internet financial platforms (IFPs) have caused the panic of investors. In order to measure and reduce the investment risk of IFPs, the focus of this study is to evaluate the reputation of IFPs regarding investment risk. First, the reputation evaluation indicator system of IFPs is constructed from two dimensions of direct and indirect reputations. Then, based on this system, an improved fuzzy evaluation approach (IFEA) integrating the method of fuzzy comprehensive evaluation (FCE), the analytic hierarchy process (AHP), and the factor analysis (FA) are proposed for evaluating the reputation of IFPs. Finally, a case study based on the data of 20 peer-to-peer (P2P) lending platforms from “Home of Online Loans” (HOL) in China is used to illustrate the IFEA. Results show that the IFEA can reduce uncertainty and randomness in the determination process of indicator weight and membership degree and therefore accurately obtain the reputation level of IFPs and help investors make better decisions. Meanwhile, the key factors in determining the reputation of IFPs are identified, thereby improving the reputation level of the IFPs.

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Section: Literature Reviewmentioning

confidence: 99%

Evaluating Reputation of Internet Financial Platform: An Improved Fuzzy Evaluation Approach

You

Hao

Dagestani

et al. 2021

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

show abstract

“…Trust‐based recommendation systems use only trust scores or combination of trust and similarity scores to recommend items to users . Using this information, we can make an idea on how reliable the user or the provider of the item is …”

Section: Related Workmentioning

confidence: 99%

“…Trust-based recommendation systems use only trust scores or combination of trust and similarity scores to recommend items to users. 46,47 Using this information, we can make an idea on how reliable the user or the provider of the item is. 15 Most of the existing algorithms, which treat time-aware and context-aware service recommendation, do not take into account the trustworthiness and the time-dependent QoS relationships among Web services.…”

Section: Trust-based Time-aware Recommender Systemsmentioning

confidence: 99%

Web service recommendation based on time‐aware users clustering and multi‐valued QoS prediction

Fayala¹,

Mezni

2019

Concurrency and Computation

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Summary With the growing number of functionally similar services over the Internet, recommendation techniques become a natural choice to cope with the challenging task of optimal service selection, and to help consumers satisfy their needs and preferences. However, most existing models on service recommendation are static, while in the real world, the perception and popularity of Web services may continually change. Time is becoming an increasingly important factor in recommender systems since time effects influence users' preferences to a large extent. In order to help users with this problem, we propose a time‐aware Web service recommendation system. First, we use K‐means clustering method in order to exclude the less similar users, which share few common Web services with the active user at different times. Slope One algorithm is also adopted in order to deal with data sparsity problem by predicting the missing ratings over time. Then, a recommendation algorithm is presented in order to recommend the top‐rated Web services. Experiments proved the accuracy of our approach compared to five existing solutions.

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“…To deal with the changing reputations of enterprises, Zhang et al propose a reputation evaluation method for optimal and trustworthy recommendation of manufacturing services in distributed P2P networks. The proposed method aims to compute the global and dynamic reputation values of each enterprise peer by employing a time‐aware hyperlink‐induced topic search algorithm adapted from Timed PageRank.…”

Section: Time‐aware Recommendation Approachesmentioning

confidence: 99%

Time‐aware service recommendation: Taxonomy, review, and challenges

Mezni

Fayala²

2018

Softw Pract Exp

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Summary Nowadays, a huge number of available Web services offer the same functionalities and a high quality of service, which makes the selection of suitable services a difficult task. In such situation, the services must be differentiated by additional criteria such as users' ratings. To meet this goal, recommendation techniques become a natural choice to cope with the challenging task of optimal service selection and to help consumers satisfy their needs and preferences. However, most existing models on service recommendation are static, whereas in the real world, the perception and popularity of Web services may continually change, and users' preferences and habits also shift frequently. Time is becoming an increasingly important factor in recommender systems, since time effects influence users' preferences to a large extent. In addition, quality‐of‐service performance of Web services is strongly linked to the service status and network environments, which are variable against time. Recently, a wide range of service recommendation approaches, dealing with the time dimension in user modeling and recommendation strategies, have been proposed. Thus, the purpose of this survey is to present a comprehensive study and analysis of the state‐of‐the‐art on time‐aware service recommendation. We identify the techniques used in recommender systems to provide the best services. Moreover, we present a classification of time‐aware recommender systems based on the target recommendation time, the type of relationship between users, and the type of feedback. Besides, we present a comparison between time‐aware recommendation approaches, and we discuss their advantages and disadvantages. Finally, challenges and requirements of time‐aware service recommendation as well as the future directions are identified according to the studied approaches.

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A time-aware hyperlink-induced topic search-based reputation evaluation method for optimal manufacturing service recommendation in distributed peer-to-peer networks

Cited by 4 publications

References 22 publications

Evaluating Reputation of Internet Financial Platform: An Improved Fuzzy Evaluation Approach

Evaluating Reputation of Internet Financial Platform: An Improved Fuzzy Evaluation Approach

Web service recommendation based on time‐aware users clustering and multi‐valued QoS prediction

Time‐aware service recommendation: Taxonomy, review, and challenges

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