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Web Service Recommendation via Exploiting Location and QOS Information 
Web Service Recommendation via Exploiting Location and QOS 
Information 
Web services are integrated software components for the support of interoperable machine to 
machine interaction over a network. Web services have been widely employed for building 
service-oriented applications in both industry and academia in recent years. The number of 
publicly available Web services is steadily increasing on the Internet. However, this proliferation 
makes it hard for a user to select a proper Web service among a large amount of service 
candidates. An inappropriate service selection may cause many problems (e.g., ill-suited 
performance) to the resulting applications. In this paper, we propose a novel collaborative 
filtering-based Web service recommender system to help users select services with optimal 
Quality-of-Service (QoS) performance. Our recommender system employs the location 
information and QoS values to cluster users and services, and makes personalized service 
recommendation for users based on the clustering results. Compared with existing service 
recommendation methods, our approach achieves considerable improvement on the 
recommendation accuracy. Comprehensive experiments are conducted involving more than 1.5 
million QoS records of real-world Web services to demonstrate the effectiveness of our 
approach. 
When developing service-oriented applications, developers first design the business process 
according to requirements, and then try to find and reuse existing services to build the process. 
Currently, many developers search services through public sites like Google Developers 
(developers.google.com), Yahoo! Pipes (pipes.yahoo. com), programmable Web 
(programmableweb.com), etc. However, none of them provide location-based QoS information 
for users. Such information is quite important for software deployment especially when trade 
compliance is concerned. Some Web services are only available in EU, thus software employing 
these services cannot be shipped to other countries. Without knowledge of these things, 
deployment of service-oriented software can be at great risk. 
Contact: 9703109334, 9533694296 
ABSTRACT: 
EXISTING SYSTEM: 
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
Web Service Recommendation via Exploiting Location and QOS Information 
Contact: 9703109334, 9533694296 
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
Web Service Recommendation via Exploiting Location and QOS Information 
DISADVANTAGES OF EXISTING SYSTEM: 
1. Some developers choose to implement their own services instead of using publicly available 
ones, which incurs additional overhead in both time and resource. 
2. Effective approaches to service selection and recommendation are in an urgent need. 
This paper investigates personalized QoS value prediction for service users by employing the 
available past user experiences of Web services from different users. Our approach requires no 
additional Web service invocations. Based on the predicted QoS values of Web services, 
personalized QoS-aware Web service recommendations can be produced to help users select the 
optimal service among the functionally equivalent ones. From a large number of real-world 
service QoS data collected from different locations, we find that the user-observed Web service 
QoS performance has strong correlation to the locations of users. Google Transparency Report1 
has similar observation on Google services. To enhance the prediction accuracy, we propose a 
location-aware Web service recommender system (named LoRec), which employs both Web 
service QoS values and user locations for making personalized QoS prediction. 
ADVANTAGES OF PROPOSED SYSTEM: 
1. Improves the recommendation accuracy and time complexity compared with existing 
service recommendation algorithms. 
2. Comprehensive analysis on the impact of the algorithm parameters is also provided. 
Contact: 9703109334, 9533694296 
PROPOSED SYSTEM: 
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
Web Service Recommendation via Exploiting Location and QOS Information 
SYSTEM ARCHITECTURE: 
SYSTEM REQUIREMENTS: 
HARDWARE REQUIREMENTS: 
 System : Pentium IV 2.4 GHz. 
 Hard Disk : 40 GB. 
 Floppy Drive : 1.44 Mb. 
 Monitor : 15 VGA Colour. 
 Mouse : Logitech. 
 Ram : 512 Mb. 
SOFTWARE REQUIREMENTS: 
 Operating system : Windows XP/7. 
 Coding Language : JAVA/J2EE 
 IDE : Netbeans 7.4 
 Database : MYSQL 
Contact: 9703109334, 9533694296 
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
Web Service Recommendation via Exploiting Location and QOS Information 
Xi Chen, Zibin Zheng, Qi Yu, and Michael R. Lyu, “Web Service Recommendation via 
Exploiting Location and QoS Information” IEEE TRANSACTIONS ON PARALLEL AND 
DISTRIBUTED SYSTEMS,VOL. 25,NO. 7, JULY 2014 
Contact: 9703109334, 9533694296 
REFERENCE: 
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in

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web service recommendation via exploiting location and qo s information

  • 1. Web Service Recommendation via Exploiting Location and QOS Information Web Service Recommendation via Exploiting Location and QOS Information Web services are integrated software components for the support of interoperable machine to machine interaction over a network. Web services have been widely employed for building service-oriented applications in both industry and academia in recent years. The number of publicly available Web services is steadily increasing on the Internet. However, this proliferation makes it hard for a user to select a proper Web service among a large amount of service candidates. An inappropriate service selection may cause many problems (e.g., ill-suited performance) to the resulting applications. In this paper, we propose a novel collaborative filtering-based Web service recommender system to help users select services with optimal Quality-of-Service (QoS) performance. Our recommender system employs the location information and QoS values to cluster users and services, and makes personalized service recommendation for users based on the clustering results. Compared with existing service recommendation methods, our approach achieves considerable improvement on the recommendation accuracy. Comprehensive experiments are conducted involving more than 1.5 million QoS records of real-world Web services to demonstrate the effectiveness of our approach. When developing service-oriented applications, developers first design the business process according to requirements, and then try to find and reuse existing services to build the process. Currently, many developers search services through public sites like Google Developers (developers.google.com), Yahoo! Pipes (pipes.yahoo. com), programmable Web (programmableweb.com), etc. However, none of them provide location-based QoS information for users. Such information is quite important for software deployment especially when trade compliance is concerned. Some Web services are only available in EU, thus software employing these services cannot be shipped to other countries. Without knowledge of these things, deployment of service-oriented software can be at great risk. Contact: 9703109334, 9533694296 ABSTRACT: EXISTING SYSTEM: Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
  • 2. Web Service Recommendation via Exploiting Location and QOS Information Contact: 9703109334, 9533694296 Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
  • 3. Web Service Recommendation via Exploiting Location and QOS Information DISADVANTAGES OF EXISTING SYSTEM: 1. Some developers choose to implement their own services instead of using publicly available ones, which incurs additional overhead in both time and resource. 2. Effective approaches to service selection and recommendation are in an urgent need. This paper investigates personalized QoS value prediction for service users by employing the available past user experiences of Web services from different users. Our approach requires no additional Web service invocations. Based on the predicted QoS values of Web services, personalized QoS-aware Web service recommendations can be produced to help users select the optimal service among the functionally equivalent ones. From a large number of real-world service QoS data collected from different locations, we find that the user-observed Web service QoS performance has strong correlation to the locations of users. Google Transparency Report1 has similar observation on Google services. To enhance the prediction accuracy, we propose a location-aware Web service recommender system (named LoRec), which employs both Web service QoS values and user locations for making personalized QoS prediction. ADVANTAGES OF PROPOSED SYSTEM: 1. Improves the recommendation accuracy and time complexity compared with existing service recommendation algorithms. 2. Comprehensive analysis on the impact of the algorithm parameters is also provided. Contact: 9703109334, 9533694296 PROPOSED SYSTEM: Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
  • 4. Web Service Recommendation via Exploiting Location and QOS Information SYSTEM ARCHITECTURE: SYSTEM REQUIREMENTS: HARDWARE REQUIREMENTS:  System : Pentium IV 2.4 GHz.  Hard Disk : 40 GB.  Floppy Drive : 1.44 Mb.  Monitor : 15 VGA Colour.  Mouse : Logitech.  Ram : 512 Mb. SOFTWARE REQUIREMENTS:  Operating system : Windows XP/7.  Coding Language : JAVA/J2EE  IDE : Netbeans 7.4  Database : MYSQL Contact: 9703109334, 9533694296 Email id: academicliveprojects@gmail.com, www.logicsystems.org.in
  • 5. Web Service Recommendation via Exploiting Location and QOS Information Xi Chen, Zibin Zheng, Qi Yu, and Michael R. Lyu, “Web Service Recommendation via Exploiting Location and QoS Information” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,VOL. 25,NO. 7, JULY 2014 Contact: 9703109334, 9533694296 REFERENCE: Email id: academicliveprojects@gmail.com, www.logicsystems.org.in