scholarly journals Performance Analysis of a Clustering Model for QoS-Aware Service Recommendation

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 740
Author(s):  
Fei Ding ◽  
Tao Wen ◽  
Suju Ren ◽  
Jianmin Bao
Keyword(s):  
Web Services ◽  
Absolute Error ◽  
Personalized Recommendation ◽  
Service Recommendation ◽  
Service Computing ◽  
Service Invocation ◽  
Clustering Model ◽  
Similarity Algorithm ◽  
Service Clustering

The numbers of web services are growing rapidly in recent years. One of the most challenging issues in service computing is the personalized recommendation of Web services. Most of the current research recommends services based on Quality of Service (QoS)-aware data with few considerations of service-side factors, such as service functions. In this paper, a new QoS-aware Web service recommendation model based on user and service clustering (RMUSC) is proposed to gain an advance in recommended accuracy. Firstly, similar users are clustered together by a Top-N similarity algorithm through the user QoS records. Secondly, a K-means++ based filtering service cluster is established. Finally, a user and services collaborative scheme is exploited and obtains potential user QoS preferences to generate recommendations. The experimental results show that when the density of the service invocation matrix is 5%, 10% and 20%. the average absolute error (MAE) and root mean square error (RMSE) of RMUSC are lower than those of other methods.

Optimized Collaborative Filtering Recommendation Based on User’s Social Relationships

2014 ◽  
Vol 1044-1045 ◽  
pp. 1484-1488
Author(s):  
Yue Kun Fan ◽  
Xin Ye Li ◽  
Meng Meng Cao
Keyword(s):  
Collaborative Filtering ◽  
Social Relationships ◽  
Digital Libraries ◽  
Social Relationship ◽  
Nearest Neighbor ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Personalized Recommendation ◽  
Recommendation Algorithm

Currently collaborative filtering is widely used in e-commerce, digital libraries and other areas of personalized recommendation service system. Nearest-neighbor algorithm is the earliest proposed and the main collaborative filtering recommendation algorithm, but the data sparsity and cold-start problems seriously affect the recommendation quality. To solve these problems, A collaborative filtering recommendation algorithm based on users' social relationships is proposed. 0n the basis of traditional filtering recommendation technology, it combines with the interested objects of user's social relationship and takes the advantage of the tags to projects marked by users and their interested objects to improve the methods of recommendation. The experimental results of MAE ((Mean Absolute Error)) verify that this method can get better quality of recommendation.

scholarly journals An effective method for clustering-based web service recommendation

2022 ◽  
Vol 12 (2) ◽  
pp. 1571
Author(s):  
Ha Huy Cuong Nguyen ◽  
Bui Thanh Khiet ◽  
Van Loi Nguyen ◽  
Thanh Thuy Nguyen
Keyword(s):  
Web Services ◽  
Web Service ◽  
Performance Metrics ◽  
Research Problem ◽  
Quality Of Services ◽  
The Novel ◽  
Service Recommendation ◽  
Functional Relevance ◽  
Web Service Classification

Normally web services are classified by the quality of services; however, the term quality is not absolute and defined relatively. The quality of web services is measured or derived using various parameters like reliability, scalability, flexibility, and availability. The limitation of the methods employing these parameters is that sometimes they are producing similar web services in recommendation lists. To address this research problem, the novel improved clustering-based web service recommendation method is proposed in this paper. This approach is mainly dealing with producing diversity in the results of web service recommendations. In this method, functional interest, quality of service (QoS) preference, and diversity features are combined to produce a unique recommendation list of web services to end-users. To produce the unique recommendation results, we propose a varied web service classification order that is clustering-based on web services’ functional relevance such as non-useful pertinence, recorded client intrigue importance, and potential client intrigue significance. Additionally, to further improve the performance of this approach, we designed web service graph construction, an algorithm of various widths clustering. This approach serves to enhance the exceptional quality, that is, the accuracy of web service recommendation outcomes. The performance of this method was implemented and evaluated against existing systems for precision, and f-score performance metrics, using the research datasets.

A Tool Chain for Constructing QoS-aware Web Services

2012 ◽  
pp. 189-211
Author(s):  
Bernhard Hollunder ◽  
Ahmed Al-Moayed ◽  
Alexander Wahl
Keyword(s):  
Web Services ◽  
Dominant Role ◽  
Distributed Applications ◽  
Service Oriented Architectures ◽  
Tool Chain ◽  
Service Computing ◽  
Service Oriented ◽  
Development Support ◽  
Standard Components

Web services play a dominant role in service computing and for realizing service-oriented architectures (SOA), which define the architectural foundation for various kinds of distributed applications. In many business domains, Web services must exhibit quality attributes such as robustness, security, dependability, performance, scalability and accounting. As a consequence, there is a high demand to develop, deploy and consume Web services equipped with well-defined quality of service (QoS) attributes – so-called QoS-aware Web services. Currently, there is only limited development support for the creation of QoS-aware Web services, though. In this work we present a tool chain that facilitates development, deployment and testing of QoS-aware Web services. The tool chain has following features: i) integration of standard components such as widely used IDEs, ii) usage of standards and specifications, and iii) support for various application servers and Web services infrastructures.

Classification of methods for generating pseudo-CT from MRI images for MRI-alone RT

2017 ◽  
Vol 1 (3) ◽  
pp. 54
Author(s):  
BOUKELLOUZ Wafa ◽  
MOUSSAOUI Abdelouahab
Keyword(s):  
Performance Metrics ◽  
Radiation Treatment ◽  
Hybrid Methods ◽  
Dose Calculation ◽  
Absolute Error ◽  
Ct Images ◽  
General Technique ◽  
Therapy Field ◽  
The Brain

Background: Since the last decades, research have been oriented towards an MRI-alone radiation treatment planning (RTP), where MRI is used as the primary modality for imaging, delineation and dose calculation by assigning to it the needed electron density (ED) information. The idea is to create a computed tomography (CT) image or so-called pseudo-CT from MRI data. In this paper, we review and classify methods for creating pseudo-CT images from MRI data. Each class of methods is explained and a group of works in the literature is presented in detail with statistical performance. We discuss the advantages, drawbacks and limitations of each class of methods. Methods: We classified most recent works in deriving a pseudo-CT from MR images into four classes: segmentation-based, intensity-based, atlas-based and hybrid methods. We based the classification on the general technique applied in the approach. Results: Most of research focused on the brain and the pelvis regions. The mean absolute error (MAE) ranged from 80 HU to 137 HU and from 36.4 HU to 74 HU for the brain and pelvis, respectively. In addition, an interest in the Dixon MR sequence is increasing since it has the advantage of producing multiple contrast images with a single acquisition. Conclusion: Radiation therapy field is emerging towards the generalization of MRI-only RT thanks to the advances in techniques for generation of pseudo-CT images. However, a benchmark is needed to set in common performance metrics to assess the quality of the generated pseudo-CT and judge on the efficiency of a certain method.

Quality-of-Service Support in Web Services Architecture

2004 ◽  
Vol 9 (5-6) ◽  
pp. 185-203 ◽  
Author(s):  
Amma Eleyan ◽  
Ludmil Mikhailov ◽  
Liping Zhao
Keyword(s):  
Quality Of Service ◽  
Web Services ◽  
Service Support

Web Services Architecture Model to Support Distributed Systems

2019 ◽  
Vol 54 (6) ◽  
Author(s):  
Sawsan Ali Hamid ◽  
Rana Alauldeen Abdalrahman ◽  
Inam Abdullah Lafta ◽  
Israa Al Barazanchi
Keyword(s):  
Web Services ◽  
Web Service ◽  
Distributed System ◽  
Modern Technology ◽  
Service Description ◽  
Architecture Model ◽  
Software Applications ◽  
Evolving Model ◽  
The Web

Recently, web services have presented a new and evolving model for constructing the distributed system. The meteoric growth of the Web over the last few years proves the efficacy of using simple protocols over the Internet as the basis for a large number of web services and applications. Web service is a modern technology of web, which can be defined as software applications with a programmatic interface based on Internet protocol. Web services became common in the applications of the web by the help of Universal, Description, Discovery and Integration; Web Service Description Language and Simple Object Access Protocol. The architecture of web services refers to a collection of conceptual components in which common sets of standard can be defined among interoperating components. Nevertheless, the existing Web service's architecture is not impervious to some challenges, such as security problems, and the quality of services. Against this backdrop, the present study will provide an overview of these issues. Therefore, it aims to propose web services architecture model to support distributed system in terms of application and issues.

An interpretable mechanism for personalized recommendation based on cross feature

2021 ◽  
pp. 1-12
Author(s):  
Lv YE ◽  
Yue Yang ◽  
Jian-Xu Zeng
Keyword(s):  
Recommender System ◽  
Online Shopping ◽  
Side Information ◽  
Attention Mechanism ◽  
Personalized Recommendation ◽  
Model Based ◽  
Embedded Model ◽  
Feature Attention ◽  
Match Score

The existing recommender system provides personalized recommendation service for users in online shopping, entertainment, and other activities. In order to improve the probability of users accepting the system’s recommendation service, compared with the traditional recommender system, the interpretable recommender system will give the recommendation reasons and results at the same time. In this paper, an interpretable recommendation model based on XGBoost tree is proposed to obtain comprehensible and effective cross features from side information. The results are input into the embedded model based on attention mechanism to capture the invisible interaction among user IDs, item IDs and cross features. The captured interactions are used to predict the match score between the user and the recommended item. Cross-feature attention score is used to generate different recommendation reasons for different user-items.Experimental results show that the proposed algorithm can guarantee the quality of recommendation. The transparency and readability of the recommendation process has been improved by providing reference reasons. This method can help users better understand the recommendation behavior of the system and has certain enlightenment to help the recommender system become more personalized and intelligent.

Multi-criteria Web Services Selection: Balancing the Quality of Design and Quality of Service

2022 ◽  
Vol 22 (1) ◽  
pp. 1-31
Author(s):  
Marwa Daaji ◽  
Ali Ouni ◽  
Mohamed Mohsen Gammoudi ◽  
Salah Bouktif ◽  
Mohamed Wiem Mkaouer
Keyword(s):  
Quality Of Service ◽  
Web Services ◽  
Web Service ◽  
State Of The Art ◽  
Service Selection ◽  
Service Design ◽  
Design Quality ◽  
Trade Off ◽  
Selection Approach

Web service composition allows developers to create applications via reusing available services that are interoperable to each other. The process of selecting relevant Web services for a composite service satisfying the developer requirements is commonly acknowledged to be hard and challenging, especially with the exponentially increasing number of available Web services on the Internet. The majority of existing approaches on Web Services Selection are merely based on the Quality of Service (QoS) as a basic criterion to guide the selection process. However, existing approaches tend to ignore the service design quality, which plays a crucial role in discovering, understanding, and reusing service functionalities. Indeed, poorly designed Web service interfaces result in service anti-patterns, which are symptoms of bad design and implementation practices. The existence of anti-pattern instances in Web service interfaces typically complicates their reuse in real-world service-based systems and may lead to several maintenance and evolution problems. To address this issue, we introduce a new approach based on the Multi-Objective and Optimization on the basis of Ratio Analysis method (MOORA) as a multi-criteria decision making (MCDM) method to select Web services based on a combination of their (1) QoS attributes and (2) QoS design. The proposed approach aims to help developers to maintain the soundness and quality of their service composite development processes. We conduct a quantitative and qualitative empirical study to evaluate our approach on a Quality of Web Service dataset. We compare our MOORA-based approach against four commonly used MCDM methods as well as a recent state-of-the-art Web service selection approach. The obtained results show that our approach outperforms state-of-the-art approaches by significantly improving the service selection quality of top- k selected services while providing the best trade-off between both service design quality and desired QoS values. Furthermore, we conducted a qualitative evaluation with developers. The obtained results provide evidence that our approach generates a good trade-off for what developers need regarding both QoS and quality of design. Our selection approach was evaluated as “relevant” from developers point of view, in improving the service selection task with an average score of 3.93, compared to an average of 2.62 for the traditional QoS-based approach.

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