Results 61 to 70 of about 719,228 (260)
Query Rewriting in Itemset Mining [PDF]
, 2004 In recent years, researchers have begun to study inductive databases, a new generation of databases for leveraging decision support applications. In this context, the user interacts with the DBMS using advanced, constraint-based languages for data mining where constraints have been specifically introduced to increase the relevance of the results and ...
Rosa Meo, Marco Botta, Roberto Esposito
openaire +1 more source
A New Algorithm for High Average-utility Itemset Mining [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold.
A. Soltani, M. Soltani
doaj +1 more source
Journal of Advanced Transportation, Volume 2026, Issue 1, 2026.The purpose of this study was to explore the risk factors for autonomous vehicle (AV) crashes and their interdependencies. A total of 659 AV crash data were collected between 2018 and July 2024 from AV crash reports published by the California Department of Motor Vehicles.
Tao Wang +4 more
wiley +1 more source
Frequent Itemset Mining for Big Data [PDF]
, 2017 Traditional data mining tools, developed to extract actionable knowledge from data, demonstrated to be inadequate to process the huge amount of data produced nowadays.
Pulvirenti, Fabio
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Identifying the Focus Word in Natural Language Questions Based on Association Rules
International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.Knowledge base‐based intelligent question‐answering systems have insufficient understanding of the questions. In the early stages of research, it is effective in most cases that the existing natural language question‐understanding methods can answer questions by connecting entities and relationships when ignoring the identification of focus words ...
Xin Hu +5 more
wiley +1 more source
Mining High-Efficiency Itemsets with Negative Utilities
MathematicsHigh-efficiency itemset mining has recently emerged as a new problem in itemset mining. An itemset is classified as a high-efficiency itemset if its utility-to-investment ratio meets or exceeds a specified efficiency threshold.
Irfan Yildirim
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Integrated Approach for Privacy Preserving Itemset Mining
, 2011 In this work, we propose an integrated itemset hiding algorithm that eliminates the need of pre-mining and post-mining and uses a simple heuristic in selecting the itemset and the item in itemset for distortion.
Belgin Ergenç +3 more
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Computational Intelligence, Volume 41, Issue 4, August 2025.ABSTRACT Machine learning techniques are increasingly used for high‐stakes decision‐making, such as college admissions, loan attribution, or recidivism prediction. Thus, it is crucial to ensure that the models learnt can be audited or understood by human users, do not create or reproduce discrimination or bias and do not leak sensitive information ...
Julien Ferry +4 more
wiley +1 more source
An Efficient Approach for Mining High Average-Utility Itemsets in Incremental Database
Engineering ProceedingsTraditional high-utility itemset (HUI) mining methods tend to overestimate utility for long itemsets, leading to biased results. High average-utility itemset (HAUI) mining addresses this problem by normalizing utility with itemset length.
Ye-In Chang +2 more
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Efficient Mining of Frequent Itemsets Using Only One Dynamic Prefix Tree
IEEE Access, 2020 Frequent itemset mining is a fundamental problem in data mining area because frequent itemsets have been extensively used in reasoning, classifying, clustering, and so on.
Jun-Feng Qu +5 more
doaj +1 more source