Automatic personalization based on Web usage mining
Communications of the ACM
Personalized web search by mapping user queries to categories
Proceedings of the eleventh international conference on Information and knowledge management
An architecture to support scalable online personalization on the Web
The VLDB Journal — The International Journal on Very Large Data Bases
BRITE: An Approach to Universal Topology Generation
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
DIMES: let the internet measure itself
ACM SIGCOMM Computer Communication Review
Making mashups with marmite: towards end-user programming for the web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
MashMaker: mashups for the masses
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Damia: a data mashup fabric for intranet applications
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Wishful search: interactive composition of data mashups
Proceedings of the 17th international conference on World Wide Web
Proceedings of the 13th international conference on Intelligent user interfaces
ACM SIGMOD Record
Semantic-Based Mashup of Composite Applications
IEEE Transactions on Services Computing
Composing enterprise mashup components and services using architecture integration patterns
Journal of Systems and Software
Collaborative browsing system based on semantic mashup with open APIs
Expert Systems with Applications: An International Journal
An optimization strategy for mashups performance based on relational algebra
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
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Two of the icons of Web 2.0 applications are feed readers and mashup platforms. On one hand, feed readers provide end-users with updates of content of feeds they subscribe to. On the other hand, mashups are conceptually web services created by end-users and hosted by mashup platforms which empower end-users with a tool to query the web based on their personalised interests. In this paper, we combine the best of mashup readers and mashup platforms in order to design a novel Web 2.0 application called mashup reader. Mashup reader enables end-users to subscribe to their favourite mashups and obtain updates of the result of executing those mashups. In this paper, we introduce the design of mashup reader, provide ways to improve its efficiency, and evaluate its execution mechanism. Our experiments show that mashup reader is an efficient and scalable Web 2.0 platform which provides end-users with an effective web querying tool.