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Association rules mining using cuckoo search algorithm
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Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Modeling Social Networks using Data Mining Approaches-Review
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     Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti

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Publication Date
Wed Oct 31 2018
Journal Name
Iraqi Journal Of Science
Search Result Enhancement For Arabic Datasets Using Modified Chicken Swarm
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The need for information web-searching is needed by many users nowadays. They use the search engines to input their query or question and wait for the answer or best search results. As results to user query the search engines many times may be return irrelevant pages or not related to information need. This paper presents   a proposed model to provide the user with efficient and effective result through search engine, based on modified chicken swarm algorithm  and cosine similarity    to eliminate and delete irrelevant pages(outliers) from the ranked list results, and to improve the results of the user's query   . The proposed model is applied to Arabic dataset and use the ZAD corpus dataset for 27

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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solving Quadratic Assignment Problem by Using Meta-heuristic Search Method
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While analytical solutions to Quadratic Assignment Problems (QAP) have indeed been since a long time, the expanding use of Evolutionary Algorithms (EAs) for similar issues gives a framework for dealing with QAP with an extraordinarily broad scope. The study's key contribution is that it normalizes all of the criteria into a single scale, regardless of their measurement systems or the requirements of minimum or maximum, relieving the researchers of the exhaustively quantifying the quality criteria. A tabu search algorithm for quadratic assignment problems (TSQAP) is proposed, which combines the limitations of tabu search with a discrete assignment problem. The effectiveness of the proposed technique has been compared to well-established a

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Data Mining Methods for Extracting Rumors Using Social Analysis Tools
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       Rumors are typically described as remarks whose true value is unknown. A rumor on social media has the potential to spread erroneous information to a large group of individuals. Those false facts will influence decision-making in a variety of societies. In online social media, where enormous amounts of information are simply distributed over a large network of sources with unverified authority, detecting rumors is critical. This research proposes that rumor detection be done using Natural Language Processing (NLP) tools as well as six distinct Machine Learning (ML) methods (Nave Bayes (NB), random forest (RF), K-nearest neighbor (KNN), Logistic Regression (LR), Stochastic Gradient Descent (SGD) and Decision Tree (

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Publication Date
Wed Aug 11 2021
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Image Denoising Using Multiwavelet Transform with Different Filters and Rules
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<p class="0abstract">Image denoising is a technique for removing unwanted signals called the noise, which coupling with the original signal when transmitting them; to remove the noise from the original signal, many denoising methods are used. In this paper, the Multiwavelet Transform (MWT) is used to denoise the corrupted image by Choosing the HH coefficient for processing based on two different filters Tri-State Median filter and Switching Median filter. With each filter, various rules are used, such as Normal Shrink, Sure Shrink, Visu Shrink, and Bivariate Shrink. The proposed algorithm is applied Salt&amp; pepper noise with different levels for grayscale test images. The quality of the denoised image is evaluated by usi

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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Computer Science
Dropping down the Maximum Item Set: Improving the Stylometric Authorship Attribution Algorithm in the Text Mining for Authorship Investigation
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Publication Date
Wed Apr 01 2015
Journal Name
2015 Annual Ieee Systems Conference (syscon) Proceedings
Automatic generation of fuzzy classification rules using granulation-based adaptive clustering
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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The role of the legal rules to the reduction of public office Crimes(Search in the Office of the Inspector General of the Ministry of Environment)
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Abstract

The goal of the research is to diagnose some of the negative phenomena which was discovered through the period from (2010 to 2014) as determined by the national strategy to eliminate the corruption which was set out by the joint council of  the corruption elimination in Iraq. And to measure the gap in applying the legal rules by the administration, concerning the misconducts and felonies upon the state employments made by the state employee and how far they are applied in the studied sample and to show the nature of the rules and their importance and their role when they are applied in scientific and expertise manner. And to encourage the offices of the general supervisors to adhere to them which will lead t

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Data Mining Techniques for Iraqi Biochemical Dataset Analysis
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This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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