Continuous Top-k Monitoring on Document Streams

By | September 3, 2018

ABSTRACT:

The effective handling of document streams assumes an important role in numerous data filtering systems. Developing applications, for example, news refresh sifting and informal organization warnings, request giving end-clients the most important substance to their inclinations. In this work, client preferences are shown by an of keywords. A focal server screens the record stream and persistently reports to every client the top k archives that are most applicable to her passwords. Our goal is to help huge quantities of clients and high stream rates, while reviving the top  k results promptly. Our answer forsakes the customary recurrence requested ordering approach.

Rather, it takes after an identifier-requesting worldview that suits better the idea of the issue. At the point when supplemented with a novel, locally versatile procedure, our technique offers (I) demonstrated optimality w.r.t. the quantity of considered questions per stream occasion, and (ii) a request of greatness shorter response time (i.e., time to refresh the query results) than the current state of the art.

 

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