Mashup Advisor: A Recommendation Tool for Mashup Development

Beijing(2008)

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摘要
Mashup editors, like Yahoo Pipes and IBM Lotus Mashup Maker, allow non-programmer end-users to ldquomash-uprdquo information sources and services to meet their information needs. However, with the increasing number of services, information sources and complex operations like filtering and joining, even an easy to use editor is not sufficient. MashupAdvisor aims to assist mashup creators to build higher quality mashups in less time. Based on the current state of a mashup, the MashupAdvisor quietly suggests outputs (goals) that the user might want to include in the final mashup. MashupAdvisor exploits a repository of mashups to estimate the popularity of specific outputs, and makes suggestions using the conditional probability that an output will be included, given the current state of the mashup. When a suggestion is accepted, MashupAdvisor uses a semantic matching algorithm and a metric planner to modify the mashup to produce the suggested output. Our prototype was implemented on top of IBM Lotus MashupMaker and our initial results show that it is effective.
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关键词
information source,final mashup,recommendation tool,mashup advisor,higher quality mashups,mashup editor,mashup development,ibm lotus mashupmaker,information need,ibm lotus mashup maker,conditional probability thatan output,current state,mashup creator,data mining,computer architecture,information services,mashups,conditional probability,web service,web services,probability
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