Results 61 to 70 of about 8,833 (199)

Mining frequent itemsets with convertible constraints [PDF]

Proceedings 17th International Conference on Data Engineering, 2002
Recent work has highlighted the importance of the constraint based mining paradigm in the context of frequent itemsets, associations, correlations, sequential patterns, and many other interesting patterns in large databases. The authors study constraints which cannot be handled with existing theory and techniques.
null Jian Pei, null Jiawei Han, L.V.S. Lakshmanan   +2 more
openaire   +1 more source

Data Mining of Infertility and Factors Influencing Its Development: A Finding From a Prospective Cohort Study of RaNCD in Iran

Health Science Reports, Volume 8, Issue 1, January 2025.
ABSTRACT Background and Aims Infertility, as defined by the World Health Organization, is the inability to conceive after 12 months of regular, unprotected intercourse. This study aimed to identify factors influencing infertility by applying data mining techniques, specifically rule‐mining methods, to analyze diverse patient data and uncover relevant ...
Hosna Heydarian, Masoumeh Abbasi, Farid Najafi, Mitra Darbandi   +3 more
wiley   +1 more source

Mining Frequent Itemsets Using Genetic Algorithm

, 2010
In general frequent itemsets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, Border algorithm etc., which take too much computer time to compute all the frequent ...
Biswas, Sushanta, Ghosh, Soumadip, Sarkar, Debasree, Sarkar, Partha Pratim   +3 more
core   +2 more sources

Efficiently mining maximal frequent itemsets

Proceedings 2001 IEEE International Conference on Data Mining, 2002
We present GenMax, a backtracking search based algorithm for mining maximal frequent itemsets. GenMax uses a number of optimizations to prune the search space. It uses a novel technique called progressive focusing to perform maximality checking, and diffset propagation to perform fast frequency computation.
K. Gouda, M.J. Zaki
openaire   +1 more source

Frequent-Itemset Mining Using Locality-Sensitive Hashing [PDF]

, 2016
The Apriori algorithm is a classical algorithm for the frequent itemset mining problem. A significant bottleneck in Apriori is the number of I/O operation involved, and the number of candidates it generates. We investigate the role of LSH techniques to overcome these problems, without adding much computational overhead. We propose randomized variations
Bera, Debajyoti, Pratap, Rameshwar
openaire   +2 more sources

A multi‐agent K‐means with case‐based reasoning for an automated quality assessment of software requirement specification

IET Communications, Volume 19, Issue 1, January/December 2025.
This paper proposed an Automated Quality Assessment of SRS (AQA‐SRS) framework by integrating four popular methods which are; NLP, K‐means, MAS, and CBR to assess the quality of SRS documents. The NLP utilize for feature extraction, K‐means for features clustering, MAS for interactive assessment and feature selection decision, and CBR for managing the ...
Mohammed Ahmed Jubair, Salama A. Mostafa, Aida Mustapha, Mohamad Aizi Salamat, Mustafa Hamid Hassan, Mazin Abed Mohammed, Fahad Taha AL‐Dhief   +6 more
wiley   +1 more source

An AI knowledge‐based system for police assistance in crime investigation

Expert Systems, Volume 42, Issue 1, January 2025.
Abstract The fight against crime is often an arduous task overall when huge amounts of data have to be inspected, as is currently the case when it comes for example in the detection of criminal activity on the dark web. This work presents and describes an artificial intelligence (AI) based system that combines various tools to assist police or law ...
Carlos Fernandez‐Basso, Karel Gutiérrez‐Batista, Juan Gómez‐Romero, M. Dolores Ruiz, Maria J. Martin‐Bautista   +4 more
wiley   +1 more source

Research on Risk Identification of Coal Mine Ventilation Systems Based on HFACS and Apriori Algorithm

Advances in Civil Engineering, Volume 2025, Issue 1, 2025.
The coal industry has always been a typically high‐risk industry with frequent accidents and extremely adverse impacts. Cases of accidents in coal mine ventilation systems serve as a concentrated demonstration of accident hazards and hold significant value for identifying key risk factors that may induce disasters in coal mine ventilation systems. This
Mingjia Jing, Guoxing Zhang, Dongjie Yang, Hongli Qin, Manoj Khandelwal   +4 more
wiley   +1 more source

Revisiting Numerical Pattern Mining with Formal Concept Analysis [PDF]

, 2011
In this paper, we investigate the problem of mining numerical data in the framework of Formal Concept Analysis. The usual way is to use a scaling procedure --transforming numerical attributes into binary ones-- leading either to a loss of information or ...
Kaytoue, Mehdi, Kuznetsov, Sergei O., Napoli, Amedeo   +2 more
core   +5 more sources

Unveiling Success Drivers in Gaming: A Machine Learning Study Across Steam, Twitch, and Metacritic

International Journal of Computer Games Technology, Volume 2025, Issue 1, 2025.
This study employs machine learning to assess the relative impact of major platforms—Steam, Twitch, and Metacritic—on video game revenue. Through an integrated analysis of three comprehensive datasets comprising commercially successful titles on Steam, key predictors of financial performance were identified.
Jiesi Ma, Michael J. Katchabaw
wiley   +1 more source