... keyword-augmented nearestneighborsearch in time that is at the order of dozens of ...commercial search engine that applies massive parallelism, implying its immediate industrial ...
... Parallelism NearestNeighborSearch Algorithm The aim is reducing runtime for nearestneighborsearch algorithm using the technology of ...the nearestneighbor ...
... usual search engine indexing algorithms. A goal of a search engine presentation is optimize the speed of the ...1.1.2 Nearestneighborsearch (NNS) ...
... the nearest objects closest to a specified location that contains a ...keywords. Nearestneighbor queries that aims to find objects both a spatial predicate and predicate on their associated ...a ...
... In data mining, the k-means algorithm is among the most commonly and widely used method for solving clustering problems because of its simplicity and performance. However, one of the main drawback of this algorithm is ...
... the nearestneighbor or distance is obtained over these ...the nearestneighborsearch and cannot give the exact value of ...k nearest neighbors, the feature data is visited in ...
... Web Search Mechanism (AWSM) is established in order to improve the quality of various search services on the ...web search. We study privacy protection in web search applications that mainly ...
... k-expected nearestneighborsearch over objects represented by Gaussian ...we search D for top k objects having smallest distances with ...of nearest users for ...
... keyword search with reverse nearestneighbor query, hybrid indexing structure bR*-tree, efficient method to answer top-k spatial keyword query, computing the relevance between the documents of an ...
... In the paper ‘fast nearestneighborsearch with keywords’, there are methods like spatial index, inverted index, nearestneighborsearch. The first method spatial index is used ...
... a search engine that is able to efficiently support novel forms of spatial queries that are integrated with keyword ...keyword-augmented nearestneighborsearch in time that is at the order of ...
... This paper presents a new method for Bilingual Lexicon Induction (BLI), which we call Hub- less NearestNeighbor (HNN). BLI is the task of creating a lexicon of translation equivalents such as, bank:banc or ...
... We concentrate on taking care of the characterization issue over encoded information. Specifically, we propose a safe k-NN classifier over scrambled information in the cloud. The proposed convention ensures the ...
... We planned a new method for professional neighboring state look for in a set of high-dimensional point. Our method is based on the precipitation of the solution freedom of any chance „nearestneighbor ...
... the nearest objects closest to a specified location that contains ...keyword search would instead searches the keywords and shows the nearest hotels that having those ...In nearest ...
... of nearestneighborsearch falls in the fashionable topic of spatial keyword search, which has also given upward push to numerous opportunity ...totally nearestneighbor queries ...
... a search engine that is able to efficiently support novel forms of spatial queries that are integrated with keyword ...keyword-augmented nearestneighborsearch in time that is at the order of ...
... reverse nearestneighbor (RNN) search and coupling ...Reverse nearestneighborsearch retrieves all points in a given data set whose nearestneighbor is a given ...
... k- nearestneighborsearch can be categorized into two classes, the hypersphere- approaches and the ...its nearestneighbor distance and, thus, actually store hyperspheres rather than ...