Time-aware trustworthiness ranking prediction for cloud services using interval neutrosophic set and ELECTRE

Ma, Hua; Zhu, Haibin; Hu, Zhigang; Li, Keqin; Tang, Wensheng

doi:10.1016/j.knosys.2017.09.027

Cited by 46 publications

(17 citation statements)

References 41 publications

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“…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%

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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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Section: Related Workmentioning

confidence: 99%

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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“…The obtained results with this type of methods are clear and intuitive but unable to reflect the comparability relation between two alternatives. The latter is based on pairwise comparisons, such as the ELECTRE (ELimination Et Choix Traduisant la REalité -ELimination and Choice Expressing the Reality) method [23]…”

Section: Introductionmentioning

confidence: 99%

A continuous interval-valued linguistic ORESTE method for multi-criteria group decision making

Liao

Liang

et al. 2018

Knowledge-Based Systems

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Considering that the uncertain linguistic variable (or interval linguistic term) has some limitations in calculation, we extend it to the continuous interval-valued linguistic term set (CIVLTS), which is equivalent to the virtual term set but has its own semantics. It has the advantages of both the uncertain linguistic variable and the virtual term set but overcomes their defenses. It not only can interpret more complex assessments by continuous terms, but also is effective in aggregating the group opinions. We propose some methods to aggregate the individual decision matrices represented by CIVLTSs to the collective matrix. The extended Gaussian-distribution-based weighting method is proposed to derive the weights for aggregating the large group opinions. Furthermore, the general ranking method ORESTE, is extended to the CIVL environment and is named as the CIVL-ORESTE method. The proposed method is excellent by no requirements of crisp criterion weights and the objective thresholds. A case study of selecting the optimal innovative sharing bike design for the "Mobike" sharing bikes is operated to show the practicability of the CIVL-ORESTE method. Finally, we compare the CIVL-ORESTE method with other ranking methods to illustrate the reliability of our method and its advantages.

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“…So, some stretched form of NS was proposed for solving MAGDM, such as single-valued neutrosophic sets (SVNSs) [31], interval neutrosophic sets (INSs) [32], simplified neutrosophic sets (SNSs) [33], and so on. Meanwhile, they have attracted a lot of research, especially related to MAGDM [34][35][36][37][38][39][40][41]. Due to the characteristic of SNSs that use three crisp numbers of the interval [0,1] to depict truth-membership, indeterminacy-membership, and false-membership, motivated by the narrow scope of the LIFN, Fang and Ye [29] put forward the concept of linguistic neutrosophic numbers (LNNs) by combining linguistic terms and a simplified neutrosophic number (SNN).…”

Section: Introductionmentioning

confidence: 99%

Linguistic Neutrosophic Generalized Partitioned Bonferroni Mean Operators and Their Application to Multi-Attribute Group Decision Making

Wang

Лю

2018

Symmetry

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To solve the problems related to inhomogeneous connections among the attributes, we introduce a novel multiple attribute group decision-making (MAGDM) method based on the introduced linguistic neutrosophic generalized weighted partitioned Bonferroni mean operator (LNGWPBM) for linguistic neutrosophic numbers (LNNs). First of all, inspired by the merits of the generalized partitioned Bonferroni mean (GPBM) operator and LNNs, we combine the GPBM operator and LNNs to propose the linguistic neutrosophic GPBM (LNGPBM) operator, which supposes that the relationships are heterogeneous among the attributes in MAGDM. Then, we discuss its desirable properties and some special cases. In addition, aimed at the different importance of each attribute, the weighted form of the LNGPBM operator is investigated, which we call the LNGWPBM operator. Then, we discuss some of its desirable properties and special examples accordingly. In the end, we propose a novel MAGDM method on the basis of the introduced LNGWPBM operator, and illustrate its validity and merit by comparing it with the existing methods.

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Time-aware trustworthiness ranking prediction for cloud services using interval neutrosophic set and ELECTRE

Cited by 46 publications

References 41 publications

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

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

A continuous interval-valued linguistic ORESTE method for multi-criteria group decision making

Linguistic Neutrosophic Generalized Partitioned Bonferroni Mean Operators and Their Application to Multi-Attribute Group Decision Making

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