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M-Cuckoo and SVM Classification Algorithm Based Opinion Mining

Malathi. M, Dr. Antony Selvadoss Thanamani
2021 Turkish Journal of Computer and Mathematics Education  
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

Laith Abualigah, Amir H. Gandomi, Mohamed Abd Elaziz, Abdelazim G. Hussien, Ahmad M. Khasawneh, Mohammad Alshinwan, Essam H. Houssein
2020 Algorithms  
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

KHIN SANDAR KYAW, Somchai - Limsiroratana
2020 ECTI Transactions on Computer and Information Technology  
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

Sherly T. T., Dr. B. Rosiline Jeetha
2021 International Journal of Scientific Research in Science and Technology  
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

Laith Abualigah, Amir H. Gandomi, Mohamed Abd Elaziz, Husam Al Hamad, Mahmoud Omari, Mohammad Alshinwan, Ahmad M. Khasawneh
2021 Electronics  
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  
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

Akshi Kumar, Renu Khorwal, Shweta Chaudhary
2016 Indian Journal of Science and Technology  
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  
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

Nagarjuna Seelam, Sai Seelam, Babu Mukkala
2017 International Journal of Intelligent Engineering and Systems  
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

Ferhat Ozgur Catak, Ahmet Faruk Yazı, Ogerta Elezaj, Javed Ahmed
2020 PeerJ Computer Science  
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


Arshey M, Dr. K.S Angel Viji
2021 Indian Journal of Computer Science and Engineering  
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

Laith Abualigah, Ali Diabat, Zong Woo Geem
2020 Applied Sciences  
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

Ajit Kumar, Dharmender Kumar, S. K. Jarial
2017 Cybernetics and Information Technologies  
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

Thanh Cong Truong, Quoc Bao Diep, Ivan Zelinka
2020 Symmetry  
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

Jaymit Bharatbhai Pandya, Udesang K. Jaliya
2022 Register: Jurnal Ilmiah Teknologi Sistem Informasi  
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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