Continuous Top-k Monitoring on Document Streams


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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