Results 121 to 130 of about 592,656 (330)

Implementasi Algoritma K-Nearest Neighbor untuk Melakukan Klasifikasi Produk dari beberapa E-marketplace

open access: yesJuTISI (Jurnal Teknik Informatika dan Sistem Informasi), 2019
E-marketplace has gained popularity with the Indonesian society resulting in the increment of products offered. Consequently, customers require more effort to search for products. In this study, we classified products from several e-marketplaces.
Danny Sebastian
doaj   +1 more source

Providing Diversity in K-Nearest Neighbor Query Results

open access: yes, 2003
Given a point query Q in multi-dimensional space, K-Nearest Neighbor (KNN) queries return the K closest answers according to given distance metric in the database with respect to Q.
Haritsa, Jayant R.   +2 more
core  

Impact of Asymptomatic Intracranial Hemorrhage on Outcome After Endovascular Stroke Treatment

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Endovascular treatment (EVT) achieves high rates of recanalization in acute large‐vessel occlusion (LVO) stroke, but functional recovery remains heterogeneous. While symptomatic intracranial hemorrhage (sICH) has been well studied, the prognostic impact of asymptomatic intracranial hemorrhage (aICH) after EVT is less certain ...
Shihai Yang   +22 more
wiley   +1 more source

Enhanced Weighted K-Nearest Neighbor Positioning

open access: yes2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring)
Peer ...
Li, Xinze   +3 more
openaire   +2 more sources

Data Recovery on Encrypted Databases with k-Nearest Neighbor Query Leakage

open access: yesIEEE Symposium on Security and Privacy, 2019
Recent works by Kellaris et al. (CCS’16) and Lacharite et al. (SP’18) demonstrated attacks of data recovery for encrypted databases that support rich queries such as range queries.
Evgenios M. Kornaropoulos   +2 more
semanticscholar   +1 more source

Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini   +28 more
wiley   +1 more source

ANALISIS PERFORMA METODE K-NEAREST NEIGHBOR UNTUK IDENTIFIKASI JENIS KACA

open access: yesIlkom Jurnal Ilmiah, 2019
Nowadays, the industry makes various types of goods that have glass-based materials, float car window panes, non-float building windows, lamps, jars, and tableware. These glasses have the same production material, the difference between one and the other
Mus Mulyadi Baharuddin   +2 more
semanticscholar   +1 more source

Location‐Specific Hematoma Volume Predicts Early Neurological Deterioration in Supratentorial ICH

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Early neurological deterioration (END) adversely affects outcomes in patients with intracerebral hemorrhage (ICH). This study aimed to determine the location‐specific hematoma volumes for END in supratentorial ICH patients. Methods We retrospectively analyzed supratentorial ICH patients presenting from two prospective cohorts.
Zuoqiao Li   +10 more
wiley   +1 more source

Angle-based Graph Neural Network Method for Anomaly Detection in High Dimensional Data [PDF]

open access: yesJisuanji gongcheng
In high-dimensional data spaces, most data are located at the edges of the high-dimensional space and distributed sparsely, resulting in the problem of "curse of dimensionality", which makes existing anomaly detection methods unable to ensure ...
Jun WANG, Huixia LAI, Yue WAN, Shi ZHANG
doaj   +1 more source

Fault Tolerant Clustering Revisited

open access: yes, 2013
In discrete k-center and k-median clustering, we are given a set of points P in a metric space M, and the task is to output a set C \subseteq ? P, |C| = k, such that the cost of clustering P using C is as small as possible.
Kumar, Nirman, Raichel, Benjamin
core  

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