Finding Top-k Preferable Products
نویسندگان
چکیده
منابع مشابه
Finding top-k elements in data streams
Identifying the most frequent elements in a data stream is a well known and difficult problem. Identifying the most frequent elements for each individual, especially in very large populations, is even harder. The use of fast and small memory footprint algorithms is paramount when the number of individuals is very large. In many situations such analysis needs to be performed and kept up to date ...
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Identifying the top-k most frequent elements is one of the many problems associated with data streams analysis. It is a well-known and difficult problem, especially if the analysis is to be performed and maintained up to date in near real time. Analyzing data streams in time sliding window model is of particular interest as only the most recent, more relevant events are considered. Approximate ...
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We consider the problem of finding and ranking paths in semistructured data without necessarily knowing its full structure. The query language we adopt comprises conjunctions of regular path queries, allowing path variables to appear in the bodies and the heads of rules, so that paths can be returned to the user. We propose an approximate query matching semantics which adapts standard notions o...
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A RkNN (Reverse k Nearest Neighbor) set of a query q is known as the influence set of q that contains the top k influential points. This query has got a considerable amount of attention due to its importance in various applications involving decision support system, profile based marketing, location based services, etc. Although this query has been largely studied in Euclidean spaces but there ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Knowledge and Data Engineering
سال: 2012
ISSN: 1041-4347
DOI: 10.1109/tkde.2012.52