Journal Article10.1145/2431211.2431218
Sequential pattern mining -- approaches and algorithms
Carl Mooney,John F. Roddick +1 more
353
TL;DR: This article surveys the approaches and algorithms proposed to date in Sequential Pattern Mining, a subfield of data mining to focus on detecting and analyzing frequent subsequences in data.
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Abstract: Sequences of events, items, or tokens occurring in an ordered metric space appear often in data and the requirement to detect and analyze frequent subsequences is a common problem Sequential Pattern Mining arose as a subfield of data mining to focus on this field This article surveys the approaches and algorithms proposed to date
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Citations
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Data Mining: The Textbook
Charu C. Aggarwal
- 27 Apr 2015
TL;DR: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.
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A Survey of Parallel Sequential Pattern Mining
TL;DR: An in-depth survey of the current status of parallel SPM (PSPM) is investigated and provided, including detailed categorization of traditional serial SPM approaches, and state-of-the art PSPM.
A survey of itemset mining
Philippe Fournier-Viger,Jerry Chun-Wei Lin,Bay Vo,Bay Vo,Tin Truong Chi,Ji Zhang,Hoai Bac Le +6 more
TL;DR: An up‐to‐date survey of itemset mining problems and the relationship to other popular pattern mining problems, such as sequential pattern mining, episode mining, subgraph mining, and association rule mining are discussed.
256
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Fundamentals of Artificial Intelligence
K. R. Chowdhary
- 04 Apr 2020
TL;DR: This chapter presents the introduction to AI, its roots, sub-domains, Turing test to judge if the given program is intelligent, what are the goals of AI for Engineers and Scientists, what is the basic requirements for AI, symbol system, andWhat are the requirements for knowledge representation.
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A hybrid recommender system for e-learning based on context awareness and sequential pattern mining
John K. Tarus,John K. Tarus,Zhendong Niu,Zhendong Niu,Dorothy Kalui +4 more
- 01 Apr 2018
TL;DR: Evaluation of the proposed hybrid recommendation approach combining context awareness, sequential pattern mining (SPM) and CF algorithms for recommending learning resources to the learners indicated that it can outperform other recommendation methods in terms of quality and accuracy of recommendations.
162
References
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Fast Algorithms for Mining Association Rules in Large Databases
Rakesh Agrawal,Ramakrishnan Srikant +1 more
- 12 Sep 1994
TL;DR: Two new algorithms for solving thii problem that are fundamentally different from the known algorithms are presented and empirical evaluation shows that these algorithms outperform theknown algorithms by factors ranging from three for small problems to more than an order of magnitude for large problems.
•Proceedings Article
Fast algorithms for mining association rules
Rakesh Agrawal,Ramakrishnan Srikant +1 more
- 01 Jul 1998
TL;DR: Two new algorithms for solving thii problem that are fundamentally different from the known algorithms are presented and empirical evaluation shows that these algorithms outperform theknown algorithms by factors ranging from three for small problems to more than an order of magnitude for large problems.
•Journal Article
Maintaining knowledge about temporal intervals
TL;DR: An interval-based temporal logic is introduced, together with a computationally effective reasoning algorithm based on constraint propagation, which is notable in offering a delicate balance between space and time.
7.9K
Maintaining knowledge about temporal intervals
TL;DR: In this paper, an interval-based temporal logic is introduced, together with a computationally effective reasoning algorithm based on constraint propagation, which is notable in offering a delicate balance between time and space.