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Revisiting Exact kNN Query Processing with Probabilistic Data Space Transformations [PDF]
, 2018 The state-of-the-art approaches for scalable kNN query processing utilise big data parallel/distributed platforms (e.g., Hadoop and Spark) and storage engines (e.g, HDFS, NoSQL, etc.), upon which they build (tree based) indexing methods for efficient ...
Christos Anagnostopoulos +7 more
core +1 more source
Batik Images Retrieval Using Pre-trained model and K-Nearest Neighbor
JOIV: International Journal on Informatics Visualization, 2023 Batik is an Indonesian cultural heritage that should be preserved. Over time, many batik motifs have sprung up, which can lead to mutual claims between craftsmen.
Agus Eko Minarno +2 more
doaj +1 more source
Efficient k-Nearest Neighbor Classification Over Semantically Secure Hybrid Encrypted Cloud Database
IEEE Access, 2018 Nowadays, individuals and companies increasingly tend to outsource their databases and further data operations to cloud service provides. However, utilizing the cost-saving advantages of cloud computing brings about the risk of violating database ...
Wei Wu +4 more
doaj +1 more source
CPRQ: Cost Prediction for Range Queries in Moving Object Databases
ISPRS International Journal of Geo-Information, 2021 Predicting query cost plays an important role in moving object databases. Accurate predictions help database administrators effectively schedule workloads and achieve optimal resource allocation strategies.
Shengnan Guo, Jianqiu Xu
doaj +1 more source
Sparse Coefficient-Based ${k}$ -Nearest Neighbor Classification
IEEE Access, 2017 K-nearest neighbor rule (KNN) and sparse representation (SR) are widely used algorithms in pattern classification. In this paper, we propose two new nearest neighbor classification methods, in which the novel weighted voting methods are developed for ...
Hongxing Ma +4 more
doaj +1 more source
Distributed Similarity Queries in Metric Spaces
Data Science and Engineering, 2019 Similarity queries, including range queries and k nearest neighbor (kNN) queries, in metric spaces have applications in many areas such as multimedia retrieval, computational biology and location-based services.
Keyu Yang +5 more
doaj +1 more source
A Bonferroni Mean Based Fuzzy K Nearest Centroid Neighbor Classifier
Jurnal Ilmu Komputer dan Informasi, 2021 K-nearest neighbor (KNN) is an effective nonparametric classifier that determines the neighbors of a point based only on distance proximity. The classification performance of KNN is disadvantaged by the presence of outliers in small sample size datasets ...
Arya Widyadhana +3 more
doaj +1 more source
QML: a hybrid spatial index structure
Tongxin xuebao, 2021 In order to enrich the functionalities of existing learned multidimensional indexes and improve the efficiency， the dynamic data segmentation algorithm DDSA was proposed， which could preserve the data distribution characteristics.A hybrid spatial index ...
Dong CUI +3 more
doaj +2 more sources
A multi-voter multi-commission nearest neighbor classifier
Journal of King Saud University: Computer and Information Sciences, 2022 Many improved versions of k-nearest neighbor (KNN) have been proposed by minimizing total distances of multi k nearest neighbors (multi-voter) in each class instead of the majority voting, such as a local mean-based pseudo nearest neighbor (LMPNN) that ...
Suyanto Suyanto +3 more
doaj +1 more source
Probabilistic CkNN Queries of Uncertain Data in Large Road Networks
IEEE Access, 2016 Continuous k-nearest neighbor (CkNN) query processing is an important issue in spatial temporal databases. In real-world scenarios, query clients and data objects may move with uncertain speeds on the road networks, which makes retrieving the exact CkNN ...
Yanhong Li +4 more
doaj +1 more source