QoS-Based Web Service Ranking Model Considering Decision Making Methods

2017 ◽  
Author(s):  
G. Vadivelou ◽  
E. Ilavarasan
Keyword(s):  
Decision Making ◽  
Web Service ◽  
Ranking Model ◽  
Service Ranking

scholarly journals Personalized decision making for QOS-based web service selection

2021 ◽  
Author(s):  
Muhammad S Saleem
Keyword(s):  
Decision Making ◽  
Learning To Rank ◽  
Service Selection ◽  
Decision Strategy ◽  
The Past ◽  
Web Service Selection ◽  
Selection Systems ◽  
Ranking Model ◽  
Service Ranking ◽  
Multiple Qos

In order to choose from a list of functionally similar services, users often need to make their decisions based on multiple QoS criteria they require on the target service. In this process, different users may follow different decision making strategies, some are compensatory and some are non-compensatory. Most of the current QoS-based service selection systems do not consider these decision strategies in the ranking process, which we believe are crucial for generating accurate ranking results for individual users. In this thesis, we propose a decision strategy based service ranking model. Furthermore, considering that different users follow different strategies in different contexts at different times, we apply a learning to rank algorithm to learn a personalized ranking model for individual users based on how they select services in the past. Our experiment result shows the effectiveness of the proposed approach.

scholarly journals Personalized decision making for QOS-based web service selection

2021 ◽  
Author(s):  
Muhammad S Saleem
Keyword(s):  
Decision Making ◽  
Learning To Rank ◽  
Service Selection ◽  
Decision Strategy ◽  
The Past ◽  
Web Service Selection ◽  
Selection Systems ◽  
Ranking Model ◽  
Service Ranking ◽  
Multiple Qos

In order to choose from a list of functionally similar services, users often need to make their decisions based on multiple QoS criteria they require on the target service. In this process, different users may follow different decision making strategies, some are compensatory and some are non-compensatory. Most of the current QoS-based service selection systems do not consider these decision strategies in the ranking process, which we believe are crucial for generating accurate ranking results for individual users. In this thesis, we propose a decision strategy based service ranking model. Furthermore, considering that different users follow different strategies in different contexts at different times, we apply a learning to rank algorithm to learn a personalized ranking model for individual users based on how they select services in the past. Our experiment result shows the effectiveness of the proposed approach.

scholarly journals Modeling User's Non-Functional Preferences for Personalized Service Ranking

2021 ◽  
Author(s):  
Rozita Mirmotalebi
Keyword(s):  
Web Services ◽  
Web Service ◽  
Functional Properties ◽  
User Modeling ◽  
User Profiles ◽  
Different Types ◽  
The Right ◽  
Service Ranking ◽  
Implicit And Explicit ◽  
Flexible Model

As the number of web services is increasing on the web, selecting the proper web service is becoming a more and more difficult task. How to make the selection results from a list of services more customized towards users’ personal preferences and help users identify the right services for their personal needs becomes especially important under this context. In this thesis, we propose a novel User Modeling approach to generate user profiles on their non-functional preferences on web services, and then apply the generated profiles to the ranking process in order to make personalized selection results. The User Modeling system is based on both implicit and explicit information from the user. Also, this is a flexible model to include different types of non-functional properties. We performed experiments using a real web service dataset with values on various non-functional properties to show the accuracy of our system.

scholarly journals Performance Oriented Decision Making to Guide Web Service Lifecycle

2016 ◽  
pp. 113-122
Author(s):  
Tehreem Masood ◽  
Chantal Bonner Cherifi ◽  
Néjib Moalla ◽  
Muhammad Fahad
Keyword(s):  
Decision Making ◽  
Web Service

Exploring Marketing Theories to Model Business Web Service Procurement Behavior

2015 ◽  
pp. 1911-1940
Author(s):  
Kenneth David Strang
Keyword(s):  
Decision Making ◽  
Web Services ◽  
Web Service ◽  
Data Storage ◽  
Service Ontology ◽  
Grounded Theory Method ◽  
The Usa ◽  
Personal Context ◽  
Decision Making Behavior ◽  
Service Procurement

This chapter provides literature-grounded definitions of contemporary Web services and marketing theories, which can model business demand through procurement decision-making behavior. First, the literature was reviewed to identify contemporary Web 2.0 and Web service ontology alongside marketing theories, which can describe individual decision making in an organizational or personal context. The Web services included cloud computing, social networking, data storage, security, and hosted applications. Then selected models for assessing procurement decision-making behavior were discussed in more detail. The constructed grounded theory method was applied by interviewing Chief Information Officers (CIO) at large organizations across four industries in the USA: healthcare, higher education, energy creation, and banking. The purpose was to determine which marketing theories could effectively model their Web service procurement behavior. An empirical procurement decision-making model was developed and fitted with data collected from the participants. The results indicated that Web service procurement decision-making behavior in businesses could easily be modeled, and this was ratified by the CIOs. The chapter proposes a state-of-the-art ontology and model for continued empirical research about organizational procurement decision-making behavior for Web services or other products.

scholarly journals Promoting Geospatial Service from Information to Knowledge with Spatiotemporal Semantics

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Jing Geng ◽  
Shuliang Wang ◽  
Wenxia Gan ◽  
Hanning Yuan ◽  
Zeqiang Chen ◽  
...  
Keyword(s):  
Decision Making ◽  
Web Service ◽  
Quality Index ◽  
User Requirement ◽  
Geospatial Information ◽  
Related Services ◽  
Service Chain ◽  
Sensor Web ◽  
Spatial Decision Making ◽  
Novel Method

With the development of geoscience, users are eager to obtain preferred service from geospatial information intelligently and automatically. However, the information grows rapidly while the service gets more complicated, which makes it difficult to find out the targeted information for an exact service in geospatial issues. In this paper, a novel method is proposed to promote the geospatial service from information to knowledge with spatiotemporal semantics. Both prompted and professional knowledge are further refined to be published as a service. In terms of an exact task, numerous related services are recombined to a service chain under user requirement. Finally, the proposed method is applied to monitor the environment on the Air Quality Index (AQI) and soil moisture (SM) in the Sensor Web service platform, the results of which indicate geospatial knowledge service (GKS) is more efficient to support spatial decision-making.

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