Results 21 to 30 of about 4,248,745 (299)
Approximation of Probabilistic Maximal Frequent Itemset Mining Over Uncertain Sensed Data
IEEE Access, 2020 Event detection by discovering frequent itemsets is very popular in sensor network communities. However, the recorded data is often a probability rather than a determined value in a really productive environment as sensed data is often affected by noise.
Sheng Chen +4 more
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Parallel Incremental Mining of Regular-Frequent Patterns from WSNs Big Data [PDF]
Journal of Artificial Intelligence and Data Mining, 2023 Efficient regular-frequent pattern mining from sensors-produced data has become a challenge. The large volume of data leads to prolonged runtime, thus delaying vital predictions and decision makings which need an immediate response.
Sadegh Rahmani-Boldaji +2 more
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An N-List-Based Approach for Mining Frequent Inter-Transaction Patterns
IEEE Access, 2020 Mining frequent inter-transaction patterns (ITPs) from large databases is both useful and of interest. Since frequent inter-transaction patterns (FITPs) are discovered across transactions in a transaction database (TD), the number of patterns is very ...
Thanh-Ngo Nguyen +4 more
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An Optimization of Closed Frequent Subgraph Mining Algorithm
Cybernetics and Information Technologies, 2017 Graph mining isamajor area of interest within the field of data mining in recent years. Akey aspect of graph mining is frequent subgraph mining. Central to the entire discipline of frequent subgraph mining is the concept of subgraph isomorphism.
Demetrovics J. +3 more
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Seizure related injuries – Frequent injury patterns, hospitalization and therapeutic aspects
Chinese Journal of Traumatology, 2022 Purpose: Epileptic seizures frequently result in distinct physical injuries, fractures, traumatic brain injuries and minor trauma. The aim of this study was to retrospectively determine the frequent injury patterns due to seizure episode and to analyze ...
Nils Mühlenfeld +6 more
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A New Fast Vertical Method for Mining Frequent Patterns [PDF]
International Journal of Computational Intelligence Systems, 2010 Vertical mining methods are very effective for mining frequent patterns and usually outperform horizontal mining methods. However, the vertical methods become ineffective since the intersection time starts to be costly when the cardinality of tidset (tid-
Zhihong Deng, Zhonghui Wang
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Reducing the Frequent Pattern Set [PDF]
Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006 One of the major problems in frequent pattern mining is the explosion of the number of results, making it difficult to identify the interesting frequent patterns. In a recent paper [7] we have shown that an MDL-based approach gives a dramatic reduction of the number of frequent item sets to consider.
Bathoorn, R.W. +2 more
openaire +3 more sources
Representing Graphs as Bag of Vertices and Partitions for Graph Classification
Data Science and Engineering, 2018 Graph classification is a difficult task because finding a good feature representation for graphs is challenging. Existing methods use topological metrics or local subgraphs as features, but the time complexity for finding discriminatory subgraphs or ...
Mansurul Bhuiyan, Mohammad Al Hasan
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Discovering Self-reliant Periodic Frequent Patterns
, 2021 Periodic frequent pattern discovery is a non-trivial task for analysing databases to reveal the recurring shapes of patterns’ occurrences. Though significant strides have been made in their discovery for understanding large databases in decision-making ...
John Wondoh +7 more
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Graph-based discovery of ontology change patterns [PDF]
, 2011 Ontologies can support a variety of purposes, ranging from capturing conceptual knowledge to the organisation of digital content and information. However, information systems are always subject to change and ontology change management can pose challenges.
Abgaz, Yalemisew +3 more
core +2 more sources