Results 21 to 30 of about 1,381,457 (160)
Top-K Collective Spatial Keyword Queries
IEEE Access, 2019 With the advent of a large number of spatial-textual data, collective spatial keyword queries have been widely studied in recent years. However, the collective spatial keyword query studied so far usually looks for only a set of objects. In addition, the
Danni Su +4 more
doaj +1 more source
Improved Top-k Query Algorithm in Distributed Networks [PDF]
Jisuanji gongcheng, 2017 Existing Top-k query algorithms are mainly applied in the centralized relational database.However,the algorithms will cause huge communication costs and low efficiency in the distributed networks.In order to solve these problems,an improved Top-k Query ...
YANG Hao,LIN Xijun,QU Haipeng
doaj +1 more source
One-Pot Isothermal LAMP-CRISPR-Based Assay for Klebsiella pneumoniae Detection
Microbiology Spectrum, 2022 Klebsiella pneumoniae (K. pneumoniae) is one of the most common pathogens causing nosocomial infection. A rapid, accurate, and convenient detection method is required for early diagnosis and directed therapy of K. pneumoniae infection. CRISPR-top (CRISPR-
Xiaotong Qiu +6 more
doaj +1 more source
Policy-Aware Unbiased Learning to Rank for Top-k Rankings [PDF]
, 2020 Counterfactual Learning to Rank (LTR) methods optimize ranking systems using logged user interactions that contain interaction biases. Existing methods are only unbiased if users are presented with all relevant items in every ranking.
de Rijke, Maarten, Oosterhuis, Harrie
core +2 more sources
Fast Top-K Graph Similarity Search Via Representative Matrices
IEEE Access, 2018 Graph similarity search is a crucial problem in many applications, such as cheminformatics, data mining, and pattern recognition. Top-k graph similarity search aims to find the most similar k graphs to a query graph in graph databases.
Zhigang Sun, Hongwei Huo, Xiaoyang Chen
doaj +1 more source
Video Popularity Prediction: An Autoencoder Approach With Clustering
IEEE Access, 2020 Autoencoders implemented by artificial neural networks (ANNs) are utilized to learn the latent space representation of data in an unsupervised manner, and they have been widely used in recommender systems.
Yu-Tai Lin +2 more
doaj +1 more source
Top-k Distance Queries on Large Time-Evolving Graphs
IEEE Access, 2023 Fast extraction of top- $k$ distances from graph data is a primitive of paramount importance in the fields of data mining, network analytics and machine learning, where ranked distances are exploited for several purposes (e.g., link prediction or ...
Andrea D'ascenzo, Mattia D'emidio
doaj +1 more source
Collaborative personalized top-k processing [PDF]
ACM Transactions on Database Systems, 2011 This article presents P4Q, a fully decentralized gossip-based protocol to personalize query processing in social tagging systems. P4Q dynamically associates each user with social acquaintances sharing similar tagging behaviors. Queries are gossiped among such acquaintances, computed on-the-fly in a collaborative, yet partitioned manner ...
Bai, Xiao +3 more
openaire +1 more source
Diversified Top-k Graph Pattern Matching [PDF]
, 2013 Graph pattern matching has been widely used in e.g., social data analysis. A number of matching algorithms have been developed that, given a graph pattern Q and a graph G , compute the set
Fan, Wenfei, Wang, Xin, Wu, Yinghui
core +1 more source
Sketch‐BF: A fast algorithm for finding top‐k flows
Electronics Letters, 2022 Finding top‐k flows plays an essential role for many network managements. Since the line rates keep increasing in networks, finding top‐k flows precisely and quickly becomes more challenging.
Jie Lu +4 more
doaj +1 more source