Results 31 to 40 of about 1,381,457 (160)
Top-k Spatial Preference Queries [PDF]
2007 IEEE 23rd International Conference on Data Engineering, 2007 A spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, consider a real estate agency office that holds a database with available flats for lease. A customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other ...
Mamoulis, N, Vaitis, M, Dai, X, Yiu, ML
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Missing values imputation using Fuzzy K-Top Matching Value
Journal of King Saud University: Computer and Information Sciences, 2023 Missing data occurs when variables or observations are missing. Researchers exclude or impute influenced variables and data. This study proposes Fuzzy K-Top Matching Value (FKTM) for missing value imputation.
Azza Ali +3 more
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Top-k Average Utility Co-location Pattern Mining of Fuzzy Features [PDF]
Jisuanji kexue yu tansuo, 2022 The spatial co-location pattern refers to a subset of non-empty spatial features whose instances are frequently located together in a spatial neighborhood.
LI Jinhong, WANG Lizhen, ZHOU Lihua
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Efficient and Secure Top-k Queries With Top Order-Preserving Encryption
IEEE Access, 2018 Top-k queries can retrieve the most relevant tuples from massive datasets and have wide implementations, such as PageRank, healthcare analytics, and decision making.
Hanyu Quan +3 more
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Efficient Top-k Graph Similarity Search With GED Constraints
IEEE Access, 2022 It is essential to identify similarity between graphs for various tasks in data mining, machine learning and pattern recognition. Graph edit distance (GED) is the most popular graph similarity measure thanks to its flexibility and versatility.
Jongik Kim
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Distributed top-k aggregation queries at large [PDF]
, 2009 Top-k query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network.
A. Marian +16 more
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Real-time recommendation algorithms for crowdsourcing systems
Applied Computing and Informatics, 2017 Crowdsourcing has become a promising paradigm for solving tasks that are beyond the capabilities of machines alone via outsourcing tasks to online crowds of people.
Mejdl Safran, Dunren Che
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Enumerating Top-k Quasi-Cliques [PDF]
, 2018 Quasi-cliques are dense incomplete subgraphs of a graph that generalize the notion of cliques. Enumerating quasi-cliques from a graph is a robust way to detect densely connected structures with applications to bio-informatics and social network analysis.
Das, Apurba +3 more
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Proceedings of the International Conference on Automated Planning and Scheduling, 2022 In top-k planning, the objective is to determine a set of k cheapest plans that provide several good alternatives to choose from. Such a solution set often contains plans that visit at least one state more than once. Depending on the application, plans with such loops are of little importance because they are dominated by a loopless representative and ...
Tschammer, Julian von +2 more
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Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations [PDF]
, 2018 To help their users to discover important items at a particular time, major websites like Twitter, Yelp, TripAdvisor or NYTimes provide Top-K recommendations (e.g., 10 Trending Topics, Top 5 Hotels in Paris or 10 Most Viewed News Stories), which rely on ...
Chakraborty, Abhijnan +4 more
core +5 more sources