Search Results - between ((((working algorithm) OR (mining algorithm))) OR (learning algorithm))
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…A comprehensive experimental analysis was conducted to evaluate the efficiency and effectiveness of the proposed algorithms (ONF-TRS, CC-TRS). The results shows that the algorithm ONF-TRS has low computational cost and high compression rate as compared with the existing works. …”
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Detection on ambiguous software requirements specification written in malay using machine learning
Published 2017“…Four (4) algorithms have been evaluated to find the suitable classification algorithm for this purpose. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…This research opens a wide range of future work to be considered, which includes applying the proposed method in other areas such as web mining, text mining or multimedia mining; and extending the proposed approach to work in parallel computing in data mining.…”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…Each respondent underwent two mathematical game sessions using a smartphone with a two-minute break in between each session. From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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8
A modified π rough k-means algorithm for web page recommendation system
Published 2018“…The results of the proposed modified algorithm for Web page recommendation system achieve an accuracy of 76-82% which is significantly outperforming than the previous work.…”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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A prototype for context identification of scientific papers via agent-based text mining
Published 2023Conference Paper -
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The experimental results demonstrate that the proposed algorithm is competitive compared to the state-of-the-art semi-supervised learning algorithms in terms of accuracy. …”
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A comprehensive analysis of blockchain-based cryptocurrency mining impact on energy consumption
Published 2022“…The Proof-of-Work (PoW) algorithm is used for mining ‘Bitcoin’ which is consumed enormous computational power. …”
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Dissimilarity algorithm on conceptual graphs to mine text outliers
Published 2009“…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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Mining dense data: Association rule discovery on benchmark case study
Published 2016“…In this article, we present comparison result between Apriori and FP-Growth algorithm in generating association rules based on a benchmark data from frequent itemset mining data repository. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis
Published 2022“…The existing approaches are based on traditional machine learning algorithms, such as support vector machine (SVM). …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…In particular, the proposed algorithm obtains satisfactory compromise between the number of cuts and classification accuracy.…”
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Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks
Published 2019“…Our proposed algorithm is capable of exploiting complementary information from different feature views in each task while exploring the shared knowledge between multiple related tasks in a joint framework when the labeled training data is sparse. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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