fast nearest-neighbor algorithm
DISTRIBUTED NEAREST NEIGHBOR MATCHING ALGORITHM FOR COMPUTER VISION
... approximately nearest neighbor ...A fast approximate similarity search method based on a neighborhood-graph ...k-nearest neighbor (k-DR) graph, from a given data set with a ...
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Survey of Efficient and Fast Nearest Neighbor Search For Spatial Query on Multidimensional Data
... Chandrashekhar [5] has presented some features of data mining like fast analysis, complex data set, etc., and also has briefly presented data mining applications, operations, techniques and algorithms. The author ...
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Evaluation Of The Performance Of K-Nearest Neighbor Algorithm In Determining Student Learning Styles
... is fast becoming popular due to its distinct features and applicability to different ...K-Nearest Neighbor (K-NN) supervised algorithm in determining students’ learning ...K-NN ...
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Scale-Invariant Feature Transform Algorithm with Fast Approximate Nearest Neighbor Ekhlas Khalaf Gbash | Suha Mohammed Saleh
... This algorithm is applied to bounder the keypoints (final keypoints) obtained from the SIFT and then from SIFT with approximate, the algorithm is worked by choosing points from specified image and generate ...
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Presentation of a Parallel Algorithm for Nearest Neighbor Search on GPU Using CUDA
... – Nearest Neighbor Search Algorithm has many applications in various sciences, for example KNN classification techniques are used often in industry and in many scientific ...in nearest ...
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A Modified Rsa Algorithm For Security Enhancement And Redundant Messages Elimination Using K-Nearest Neighbor Algorithm
... Symmetric algorithms are typically considered fast and they are suitable for processing large stream of data. Some of the famous and efficient symmetric algorithms include Twofish, Serpent, AES, Blowfish and IDEA ...
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Efficient Vector Quantization for Fast Approximate Nearest Neighbor Search
... As can be seen from the above, ICM considers one codebook at a time and tries to im- prove the quantization error, while keeping other 𝑀 − 1 assignments fixed. This solu- tion has a complexity of 𝑂(𝐿𝑀𝐾𝐷) for encoding a ...
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Analysis on Fast Nearest Neighbor Search with Keywords
... Second method is inverted index. The inverted index data structure is a central component of a typical search engine indexing algorithm. A goal of a search engine performance is to optimize the speed of the query: ...
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FAST NEAREST NEIGHBOR SEARCH WITH KEYWORDS
... k nearest neighbor (kNN) and range queries are fundamental query ...for nearest neighbor queries are designed in the context of spatial ...Dijkstra’s algorithm-based kNN solutions have ...
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Fast Nearest Neighbor Search With Keywords
... thebest-first algorithm is exactly designed to output data points in ascending order of their distances to ...This algorithm is expected to work well if the query keyword set Wq is ...sequential ...
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Video Inpainting using Nearest Neighbor Field Algorithm
... the fast randomized algorithm for approximating nearest neighbor correspondence between two ...a nearest- neighbor field (NNF) as a function f: A 7-> R2 of offsets, defined ...
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An Infectious Disease Prediction Method Based on K-Nearest Neighbor Improved Algorithm
... k-nearest neighbor improvement algorithm from the perspective of patient similarity ...K-nearest neighbor algorithm; based on the maximum entropy The K-nearest ...
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A Logarithmic Complexity Algorithm for Nearest Neighbor Classification Using Layered Range Trees
... the nearest neighbor(s) to the query ...finding algorithm would iterate through all of the dataset, measure the distance between the query instance and every other instance in the data set, and then ...
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Credit card fraud detection using anti-k nearest neighbor algorithm
... Banks have used early fraud warning systems for some years. Improved fraud detection thus has become essential to maintain the viability of the payment system. Outlier mining in data mining is an important functionality ...
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Provide Security of Ranked Multi keyword Search over Encrypted Data in cloud computing
... Abstract : Now a day’s mobile cloud computing is rapidly growth for searching outsource the mobile data to external cloud servers for scalable data storage. So that to provide security of that data is most important ...
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Analysis of Machine Learning Algorithms Performance for Real World Concept
... As it can be seen the result for K=1 is the best. We choose the K that does best in the leave-one-out experiment (breaking any ties by choosing the largest K). After tuning the K parameter, we did classification of the ...
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A recommender system based on collaborative filtering using ontology and dimensionality reduction techniques
... Lv, Hu, and Chen (2016) developed a recommendation system based on relational data using the relational data in the domain ontology. They used genetic algorithm for recommendation pro- cess. They used MovieLens ...
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William_Wiener_Biology_Honors_Thesis.pdf
... their nearest neighbors (Evangelista et. al, 2017). Nearest neighbor distance appeared to help predict whether swifts were cooperating, with the conclusion being that local interactions were ...
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Title: PERFORMANCE ANALYSIS OF HYBRID APPROACH OF K-NN ALGORITHM USING MULTIPLE-LEVEL LEARNING FOR TEXT CLASSIFICATION
... Abstract: -Dataset of each and every institute or organization is rapidly increasing. Due to this, it is going very complex for any user to find and access necessary data from whole dataset. To keep this problem in mind, ...
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Prediction of Student’s Performance based on Incremental Learning
... NNGE algorithm worked nicely in terms of accuracy and also took less ...NNGe algorithm for evaluating student’s performance like in datasets which has been used ...
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