[PDF] Top 20 k-Expected Nearest Neighbor Search over Gaussian Objects
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k-Expected Nearest Neighbor Search over Gaussian Objects
... varying k in ...of objects accessed by PLUB will be pruned by upper bounds of candidate objects using their lower bounds and we only need to compute ESQEDs for a small part of ...when k is ... See full document
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Analysis on Fast Nearest Neighbor Search with Keywords
... Nearest neighbor search (NNS), also known as closest point search, similarity ...points. Nearest neighbor search which returns the nearest neighbor of a ... See full document
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Quick Search of the Nearest Neighbor with Words
... range search and nearest neighbor retrieval, involve only conditions on objects’ geometric ...find objects satisfying both a spatial predicate, and a predicate on their associated ...a ... See full document
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FAST NEAREST NEIGHBOR SEARCH WITH KEYWORDS
... vary search and nearest neighbor retrieval, involve solely conditions on objects’ geometric ...out objects satisfying both a spatial predicate, and a predicate on their associated ...a ... See full document
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Nearest Neighbor Search with Keywords in Spatial Databases
... to search for a location or place, it searches all the rows and return the ...many objects, causing expensive overhead as each loading necessitates a random ...if search is performed only in the used ... See full document
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Keyword Search for Quick Finding of Nearest Neighbor
... the nearest objects closest to a specified location that contains ...the objects with special word or predicates &predicates with their associated ...keyword search would instead searches ... See full document
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Fast Nearest Neighbor Search With Keywords
... Distance browsing is easy with R- trees. In fact, thebest-first algorithm is exactly designed to output data points in ascending order of their distances to q. However ,we must coordinate the execution of best-first on ... See full document
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Nearest Neighbor Search with Anytime Clustering Method
... actual k nearest neighbors is ...data objects into two approximately equal-sized groups and recursively maintains the minimum of each group ...the K nearest neighbors on large-scale ... See full document
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Züfle, Andreas (2013): Similarity search and mining in uncertain spatial and spatio-temporal databases. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... a k-nearest neighbor (kNN) query. In Application I, a k-nearest neighbor query may not make much sense, as the k friends of yours having the smallest distance to you may ... See full document
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A Survey on K-Nearest Neighbor Classification over Semantically Secure Encrypted Relational Data
... The search process of our DMRS scheme starts from the root node with a recursive procedure upon the tree in a special depth-first manner, which is called as “Greedy Depth first Traverse ...documents, search ... See full document
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Abnormal Moving Object Detection Using Sparse Based Graph K Nearest Neighbour(SGk-NN)
... of k-nearest neighbor (k-NN) queries over moving objects within a geographic ...the objects are fully predictable at query processing ...NN search in both on-demand ... See full document
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Secure K-Nearest Neighbor Search By Keywords
... spoken to as a cross section), as expected to assess general circuits. Sadly, our underlying plan is not exactly bootstrappable – i.e., the profundity that the plan can accurately evaluate can be logarithmic in ... See full document
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Fast Concept Mention Grouping for Concept Map based Multi Document Summarization
... Given the mapping h from vectors to their bit hashes, we can partition a set of vectors by hash identity. Every unique hash becomes a group con- sisting of all vectors mapped to that hash. Since the hashes reflect ... See full document
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Scalable Distributed Processing of K nearest Neighbour Queries over Moving Objects
... moving objects location in advance is very ...moving objects, thus increasing our ability to mine spatiotemporal data ...moving objects behavior and to predict their future locations. k ... See full document
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On the Behavior of Intrinsically High-Dimensional Spaces: Distances, Direct and Reverse Nearest Neighbors, and Hubness
... reverse nearest neighbors, in intrinsically high-dimensional ...the expected distance from a given point to its kth nearest neighbor, and for the expected size of the ap- proximate set ... See full document
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What Affects K Value Selection In K-Nearest Neighbor
... best k values in n-class data sets (Figure 5) but there is no such relationship in the case of 2-class data sets (Figure ...best k values but also the ones with categorical ...of k may have not ... See full document
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Performance Evaluation of SVM and K Nearest Neighbor Algorithm over Medical Data set
... The support vector machine has been chosen because it represents a framework both interesting from a machine learning perspective. A SVM is a linear or non-linear classifier, which is a mathematical function that can ... See full document
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Recommendation of online Products Using Microblogging Information in Social Media
... Most of the e-commerce websites use customer information to list out products as customer’s rate their experience and the viewed items gives their interests. Online store Amazon.com personalizes eh website based on ... See full document
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A Novel Weighted Voting for K-Nearest Neighbor Rule
... of k than the k-nearest neighbor rule, their classification results are still affected by the sensitivity of ...of k, owing to the existing outliers in the set of k ... See full document
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Hubless Nearest Neighbor Search for Bilingual Lexicon Induction
... This paper presents a new method for Bilingual Lexicon Induction (BLI), which we call Hub- less Nearest Neighbor (HNN). BLI is the task of creating a lexicon of translation equivalents such as, bank:banc or ... See full document
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