Sky line online calculation method based on user clustering

Abstract

The invention discloses a sky line online calculation method based on user clustering. The sky line online calculation method comprises the following steps of: (1) gathering users with similar QoS (Quality of Service) through user clustering, and substituting for personal characteristics of each user by using common characteristics of clustering to effectively reduce the data calculating volume, converting a mode of carrying out offline processing on all the users into a mode of carrying out offline processing on each cluster to improve the offline calculation efficiency, greatly reduce the storage space consumption and improve the enablement of a system; (2) dividing a calculation process into an offline module and an online module, carrying out a great quantity of complex calculations in the offline module to effectively improve the execution efficiency of an online algorithm; and (3) predicting an individual sky line by using a group characteristic sky line to obtain a prediction result, wherein on one hand, the prediction result is returned as a result when the requirement on precision is not high, and on the other handle, the prediction result can be corrected on the predicted sky line when an accurate sky line needs to be solved, and therefore the calculation process can be simplified.

Description

technical field [0001] The invention relates to a sky line computing discovery in service computing, in particular to an online sky line computing method that implements offline prediction based on user clustering. Background technique [0002] In recent years, the field of Web service computing has developed rapidly with the wide application of SOA technology, and several subfields such as service discovery, service composition, and service selection have been derived from it. With the wide application of SOA, the number of Web services (hereinafter referred to as services) on the Internet has increased sharply, making manual search, selection and invocation of services no longer able to meet the needs, so efficient discovery, selection and combination of service algorithms have become urgent research needs. How to find a service that meets this functional requirement in a large number of services according to the user's functional requirement description is the research c...

AI Technical Summary

Problems solved by technology

The completely offline method analyzes the global service QoS data set. The calculation results are accurate but difficult to meet the online sky line calculation requirements; the progressive online calculation method continuously adjusts and corrects the sky line online to gradually approach the final sky line result. Although the calculation process conforms to the online characteristics, the accurate results need to be gradually refined and completed completely online, and the overall calculation efficiency is low

It can be seen that there is no sky line calculation method that combines the globality of offline calculations and the real-time advantages of online calculations.

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