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M-Cuckoo and SVM Classification Algorithm Based Opinion Mining
2021
Turkish Journal of Computer and Mathematics Education
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Therefore, this research paper proposes a hybrid feature selection which is a combination of cuckoo search and mRMR (Minimum Redundancy Maximum Relevance) algorithm. ...
In terms of better efficiency and less processing time, the Cuckoo algorithm performs various nature-inspired algorithms. ...
Cuckoo search uses Levi flight strategy based on Egg laying Radius in deriving the solution specific to problem. CS optimization algorithm increases the efficiency, accuracy, and convergence rate. ...
doi:10.17762/turcomat.v12i4.456
fatcat:xe3r7fe7xrandozdw3fyqj5hgi
Nature-Inspired Optimization Algorithms for Text Document Clustering—A Comprehensive Analysis
2020
Algorithms
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Text clustering is one of the efficient unsupervised learning techniques used to partition a huge number of text documents into a subset of clusters. ...
For improvement purposes, new modified versions of the tested algorithms can be proposed and tested to tackle the text clustering problems. ...
In Reference [55] , two approaches for web text document clustering are introduced based on the KHA algorithm. ...
doi:10.3390/a13120345
fatcat:5e4qcompgbdgpnt6o6iknmsauy
An Optimization of Multi-Class Document Classification with Computational Search Policy
2020
ECTI Transactions on Computer and Information Technology
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Traditional search policy for feature selection process is degrading with exhaustive search for complex feature in document classification. ...
The search policy of computational algorithm can provide the global optimal solution with random search approach on both exploitation and exploration process, and the selected search results of feature ...
ACKNOWLEDGEMENTS This work was supported by Thailand's Education Hub for ASEAN Countries (Grant No. TEH-AC 058/2016). ...
doi:10.37936/ecti-cit.2020142.227431
fatcat:mp3pxqecc5bxroye5gd7ouwbwq
Enhanced Cuckoo Search Optimization and Hybrid Firefly Artificial Neural Network Algorithm for Cyberbullying Detection on Twitter Dataset
2021
International Journal of Scientific Research in Science and Technology
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To avoid the above mentioned issues, in this work, Enhanced Cuckoo Search optimization (ECSO) and Hybrid Firefly Artificial Neural Network (HFANN) algorithm is proposed. ...
The pre-processed features are taken into feature selection process for obtaining more informative features from the Twitter dataset. ...
In [15], Emary et al (2015) used the system for feature selection based on firefly algorithm (FFA) optimization is proposed. ...
doi:10.32628/cseit217486
fatcat:3aa2gttkcreg3ggdqh5poadlka
Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering
2021
Electronics
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This paper reviews all of the relevant literature on meta-heuristic-based text clustering applications, including many variants, such as basic, modified, hybridized, and multi-objective methods. ...
This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on the text clustering applications and highlights its main procedures. ...
[96] proposed a new technique for solving the feature selection problem based on the HS algorithm to search for the best subset of informative features. ...
doi:10.3390/electronics10020101
fatcat:fb3sopje4fegphs5b6g673ipqa
A Comparative Study of Meta-Heuristic and Conventional Search in Optimization of Multi-Dimensional Feature Selection
2022
International Journal of Applied Metaheuristic Computing
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Algorithmic – based search approach is ineffective at addressing the problem of multi-dimensional feature selection for document categorization. ...
of meta-heuristic search for multi-dimensional feature selection problem in document categorization. ...
Nwabor for his assistance throughout the manuscript preparation phase. ...
doi:10.4018/ijamc.292517
fatcat:zkt2gzbvprfcza7a7hppiywfnu
A Survey on Sentiment Analysis using Swarm Intelligence
2016
Indian Journal of Science and Technology
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The statistical techniques of feature selection like document frequency thresholding produce sub optimal feature subset due to the Non Polynomial (NP) hard nature of the problem. ...
Swarm intelligence algorithms are extensively used in optimization problems. Optimization techniques could be applied to feature selection problem to produce Optimum feature set. ...
In PSO a collection of agents called particles which search for solution in search space based on its own experience and experience of its neighbors and based on this it decides where to move in the search ...
doi:10.17485/ijst/2016/v9i39/100766
fatcat:ta242dgr6jfdxkzxd2o74rzfyi
A Hyper Meta-Heuristic Cascaded Support Vector Machines for Big Data Cyber-Security
2019
International journal of recent technology and engineering
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Initially, the feature selection is done by using improved K-means clustering. Based on the selected features the intrusion detection and malware detection are performed using ESVM approach. ...
Existing systems for big data cyber security problems are based on Online Support Vector Machines (OSVMs) framework. ...
The cuckoo search (cuckoo search CS) algorithm is a metaheuristic algorithm recommended in the latest years [22] ; Cuckoo Search (CS) is a new swarm intelligent optimization algorithm. ...
doi:10.35940/ijrte.d5330.118419
fatcat:yx4adfy4ondyzdazdsql76msby
Optimal Decision Tree Based Unsupervised Learning Method for Data Clustering
2017
International Journal of Intelligent Engineering and Systems
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In our proposed research, we introduce a binary cuckoo search based decision tree. In this tree based learning technique, extracting patterns from a given dataset. ...
Our investigation using a pattern based clustering on numerical data set; here, we are using a Parkinson and spam dataset. ...
In our research, we introduce an optimal decision tree technique for data clustering based on Binary Cuckoo Search Algorithm. ...
doi:10.22266/ijies2017.0430.14
fatcat:a4uc5oegrncmnbicx4pgoebg3e
Deep learning based Sequential model for malware analysis using Windows exe API Calls
2020
PeerJ Computer Science
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Another significant contribution of this research paper is the development of a new dataset for Windows operating systems based on API calls. ...
It is quite impossible for anti-virus applications using traditional signature-based methods to detect metamorphic malware, which makes it difficult to classify this type of malware accordingly. ...
We select the that we want to classify. 2. We process the dataset for the selected malware type. ...
doi:10.7717/peerj-cs.285
pmid:33816936
pmcid:PMC7924690
fatcat:euacesaw2zgutly7fhbxerbbo4
FRACTIONAL-EWA BASED DEEP CNN FOR PHISHING ATTACK DETECTION
2021
Indian Journal of Computer Science and Engineering
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The features are extracted using the term frequency and the feature is selected using the Levenshtein distance. The DCNN is trained by exploiting the proposed Fractional-EWA. ...
sensitivity, and maximum specificity of 0.744, 0.725, and 0.723, respectively for number of features. ...
These obtained outputs are employed as a text feature vector for further classification. The weights are similar to number of times that the features occur in a document for term frequency. ...
doi:10.21817/indjcse/2021/v12i5/211205014
fatcat:m6ibnxehkrdhbggcicc6vkg3km
A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications
2020
Applied Sciences
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The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering ...
We provide a comprehensive survey of the literature on HSA and its variants, analyze its strengths and weaknesses, and suggest future research directions. ...
Ayvaz in [71] HSA Text clustering New clustering methods are proposed based on using HSA for web document clustering purposes The obtained results reported that the hybrid HSA got better clusters using ...
doi:10.3390/app10113827
fatcat:okeokml755b2dcx6yjamnhtml4
A Review on Artificial Bee Colony Algorithms and Their Applications to Data Clustering
2017
Cybernetics and Information Technologies
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In the past, many swarm intelligence based techniques for clustering were introduced and proved their performance. ...
Artificial Bee Colony (ABC) algorithm is one of the popular swarm based algorithm inspired by intelligent foraging behaviour of honeybees that helps to minimize these shortcomings. ...
Coli bacteria foraging (see [12] ), Artificial Bee Colony, which is based on honey bee swarms [13] , Cat Swarm Optimization, which is based on behavior of cats [14] , Cuckoo Search Algorithm [15] , ...
doi:10.1515/cait-2017-0027
fatcat:evxefbetd5gv3enuc7fiulyewm
Artificial Intelligence in the Cyber Domain: Offense and Defense
2020
Symmetry
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However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. ...
In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. ...
[38] introduced an IDS based on SVM with the tabu-artificial bee colony for feature selection and parameter optimization simultaneously. ...
doi:10.3390/sym12030410
fatcat:7gyse3gaxjguhgkvfnbi7knkf4
An empirical study on the various stock market prediction methods
2022
Register: Jurnal Ilmiah Teknologi Sistem Informasi
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The reviewed articles are analyzed based on the use of prediction techniques, optimization algorithms, feature selection methods, datasets, toolset, evaluation matrices, and input parameters. ...
The techniques are further investigated to analyze relations of prediction methods with feature selection algorithm, datasets, feature selection methods, and input parameters. ...
The cuckoo search method based on the PSO approach was used for tuning the parameters of the SVM. The outcomes show that the cuckoo search SVM was attained more accuracy than the SVM. Das., et al. ...
doi:10.26594/register.v8i1.2533
fatcat:vtircrcxzzg3hinmpwszwrlkhu
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