Search Results - ((((mining algorithm) OR (matching algorithm))) OR (((bees algorithm) OR (_ algorithm))))

Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman by Azman, Muhammad Izzat Azri

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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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A new text-based w-distance metric to find the perfect match between words by Ali, M., Jung, L.T., Hosam, O., Wagan, A.A., Shah, R.A., Khayyat, M.

“…The k-NN algorithm is an instance-based learning algorithm which is widely used in the data mining applications. …”
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A prototype for context identification of scientific papers via agent-based text mining by Mahmoud M.A., Ahmad M.S.

Dissimilarity algorithm on conceptual graphs to mine text outliers by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

“…The graphical text representation method such as Conceptual Graphs (CGs) attempts to capture the structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the dissimilarity (or similarity) between knowledge represented in the CGs.In this paper, we would like to present a dissimilarity algorithm to detect outliers from a collection of text represented with Conceptual Graph Interchange Format (CGIF).In order to avoid the NP-complete problem of graph matching algorithm, we introduce the use of a standard CG in the dissimilarity computation.We evaluate our method in the context of analyzing real world financial statements for identifying outlying performance indicators.For evaluation purposes, we compare the proposed dissimilarity function with a dice-coefficient similarity function used in a related previous work.Experimental results indicate that our method outperforms the existing method and correlates better to human judgements. …”
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Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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Context identification of scientific papers via agent-based model for text mining (ABM-TM) by Mahmoud M.A., Ahmad M.S., Yusoff M.Z.M., Mustapha A.

“…In this paper, we propose an agent-based text mining algorithm to extract potential context of papers published in the WWW. …”

Position score weighting technique for mining web content outliers. by Mustapha, Norwati, Mustapha, Aida

“…The existing mining web content outlier methods used stemming algorithm to preprocess the web documents and leave the domain dictionary in their root words. …”
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Improving sentiment reviews classification performance using support vector machine-fuzzy matching algorithm by Nurcahyawati, Vivine, Mustaffa, Zuriani

“…Many of these dimensionalities have a major impact on the complexity and performance of the algorithms used for classification. Various challenges were encountered, including how to determine the optimal combination of pre-processing techniques, how to clean the dataset, and determine the best classification algorithm. …”
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Bee foraging behaviour techniques for grid scheduling problem by Alyaseri, Sana, Ku-Mahamud, Ku Ruhana

“…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.These resources are collected together to make a huge computing power.Job scheduling problem is one of the key issues in grid computing and failing to look into grid scheduling results in uncompleted view of the grid computing.Achieving optimized performance of grid system, and matching application requirements with available computing resources, are the objectives of grid job scheduling.Bee colony approaches are more adaptive to grid scheduling due to high heterogeneous and dynamic nature of resources and applications in grid.These algorithms have shown encouraging results in terms of time and cost.This paper presents some resent research activities inspired by bee foraging behavior for grid job scheduling especially ABC and BCO approaches.Different original studies related to this area are briefly described along with their comparisons against them and results.The review summary of their derived algorithms and research efforts is done.…”
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Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data by Laxmi Lydia E., Sharmili N., Nguyen P.T., Hashim W., Maseleno A.

“…Automatic indexing; Big data; Cluster analysis; Extraction; Factorization; Indexing (of information); Information retrieval; K-means clustering; Natural language processing systems; Open source software; Open systems; Pattern matching; Software quality; Software testing; Text mining; Hadoop; Key phrase extractions; Map-reduce; Pattern-matching technique; Porters; Pre-processing algorithms; Software environments; Unlabeled; Matrix algebra…”

A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining by Jalali, Mehrdad

“…The approach in the offline phase is based on the new graph partitioning algorithm to model user navigation patterns for the navigation patterns mining. …”
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Pattern Discovery Using K-Means Algorithm by Ahmed, AM, Norwawi, NM, Ishak, WHW, Alkilany, A

“…The pattern extracted gave information on the previous matching process done by the university.…”

Travel place recommendation system using K-Nearest Neighbors algorithm / Nur Amirah Shahidan by Shahidan, Nur Amirah

“…The method has been proposed in the recommendation system is K-Nearest Neighbors algorithm. K-Nearest Neighbors algorithm is widely used among classification algorithm in recommendation system. …”
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Concept Based Lattice Mining (CBLM) using Formal Concept Analysis (FCA) for text mining by Mumtazimah, Mohamad, Hassan, H., Mohd Saman, M.Y, Abdullah, Z.

“…The deployment of FCA concept lattices ensures that the matching is done based on extracted concepts; not just mere keywords matching hence producing more relevant results. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Concept Based Lattice Mining (CLBM) Using Formal Concept Analysis (FCA) for Text Mining by Hasni, Hassan, Mumtazimah, Mohamad, Md Yazid, Mohamad Saman

“…The deployment of FCA concept lattices ensures that the matching is done based on extracted concepts: not just mere keywords matching hence producing more relevant results. …”
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Pattern discovery using k-means algorithm by Mohammed Ahmed A., Wan Ishak W.H., Md Norwawi N., Alkilany A.

Hybridized Intelligent Neural Network Optimization Model for Forecasting Prices of Rubber in Malaysia by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali, K. G. Tay, K. G. Tay, Muraly Velavan, Muraly Velavan

“…These algorithms, including Grey Wolf Optimization Algorithm, Artificial Bee Colony Algorithm, and Particle Swarm Optimization Algorithm were utilized in the forecasting data analysis. …”
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Hybridized Intelligent Neural Network Optimization Model for Forecasting Prices of Rubber in Malaysia by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan, K. G. Tay, K. G. Tay, Muraly Velavan, Muraly Velavan

“…These algorithms, including Grey Wolf Optimization Algorithm, Artificial Bee Colony Algorithm, and Particle Swarm Optimization Algorithm were utilized in the forecasting data analysis. …”
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