Results 11 to 20 of about 310,714 (306)
Towards bounding sequential patterns [PDF]
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011 Given a sequence database, can we have a non-trivial upper bound on the number of sequential patterns? The problem of bounding sequential patterns is very challenging in theory due to the combinatorial complexity of sequences, even given some inspiring results on bounding itemsets in frequent itemset mining.
Chedy Raïssi, Jian Pei 0001
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Sequential Hierarchical Pattern Clustering [PDF]
, 2009 Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all pairwise distances between patterns must be computed in advance. This makes it computationally expensive and difficult to cope with large scale data used in several applications, such ...
Bassam Farran +2 more
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Frontiers in Computational Neuroscience, 2021 Sequential transitions between metastable states are ubiquitously observed in the neural system and underlying various cognitive functions such as perception and decision making.
Tomoki Kurikawa +2 more
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Mining Weighted Sequential Patterns Based on Prefix-Tree and Prism Encoding
Vietnam Journal of Computer Science, 2023 The purpose of mining sequential patterns problem with weighted constraints is to find high-valued patterns, including infrequent patterns but having items which appear in the pattern of high importance in the sequence database (SD).
Thi-Thiet Pham +4 more
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Mining Conjunctive Sequential Patterns [PDF]
Data Mining and Knowledge Discovery, 2008 In this paper we aim at extending the non-derivable condensed representation in frequent itemset mining to sequential pattern mining. We start by showing a negative example: in the context of frequent sequences, the notion of non-derivability is meaningless. Therefore, we extend our focus to the mining of conjunctions of sequences.
Chedy Raïssi +2 more
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Enhanced parallel mining algorithm for frequent sequential rules
Ain Shams Engineering Journal, 2022 Sequential rule mining is an important data mining technique that discovers relationships between occurrences of sequential patterns. The main challenge is to avoid time-consuming, especially in large search spaces.
Nesma Youssef +2 more
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Progressive CFM-Miner: An Algorithm to Mine CFM – Sequential Patterns from a Progressive Database [PDF]
International Journal of Computational Intelligence Systems, 2013 Sequential pattern mining is a vital data mining task to discover the frequently occurring patterns in sequence databases. As databases develop, the problem of maintaining sequential patterns over an extensively long period of time turn into essential ...
Bhawna Mallick +2 more
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IEEE Access, 2022 The field of data mining is progressing rapidly presenting researchers with many opportunities for research. Sequential pattern mining is a popular and long established technique in data mining which extracts data in the form of sequential patterns ...
Ritika, Sunil Kumar Gupta
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Sequential patterns for text categorization [PDF]
Intelligent Data Analysis, 2006 Text categorization is a well-known task based essentially on statistical approaches using neural networks, Support Vector Machines and other machine learning algorithms. Texts are generally considered as bags of words without any order. Although these approaches have proven to be efficient, they do not provide users with comprehensive and reusable ...
Jaillet, Simon +2 more
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An Efficient Method for Mining Top-
IEEE Access, 2020 The problem of exploiting Closed Sequential Patterns (CSPs) is an essential task in data mining, with many different applications. It is used to resolve the situations of huge databases or low minimum support (minsup) thresholds in mining sequential ...
Thi-Thiet Pham +4 more
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