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A new text-based w-distance metric to find the perfect match between words
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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 new function of stereo matching algorithm based on hybrid convolutional neural network
Published 2022“…This paper proposes a new hybrid method between the learning-based and handcrafted methods for a stereo matching algorithm. …”
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A prototype for context identification of scientific papers via agent-based text mining
Published 2023Conference Paper -
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AR oriented pose matching mechanism from motion capture data
Published 2023“…The experimental results show that the proposed algorithm outperforms the state of art techniques for successful identification and recognition of matched pose between the dance trainer and the expert of the pre-recorded video through the Kinect sensor. � 2018 Authors.…”
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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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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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A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining
Published 2009“…The longest common subsequence is a well-known string matching algorithm that we have utilized to find the most similar pattern between a set of navigation patterns and current user activities for creating the recommendations.…”
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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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Stereo matching algorithm using deep learning and edge-preserving filter for machine vision
Published 2024“…This paper proposes a hybrid method of a stereo matching algorithm with the goal of generating an accurate disparity map critical for applications such as 3D surface reconstruction and robot navigation to name a few. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Recognition of human motion from qualitative normalised templates
Published 2007“…In contrast to other human motion classification methods which usually include a human model, prior knowledge on human motion and a matching algorithm, we replace the matching algorithm (e.g. template matching) with the proposed QNTs. …”
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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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Improving named entity recognition accuracy of gene and protein in biomedical text
Published 2011“…The strength of our proposed approach for recognizing biomedical named entity is based on a Statistical Character-Based Syntax Similarity (SCSS) algorithm which measured similarity between all extracted candidates and the well-known biomedical named entities from a corpus. …”
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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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Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques
Published 2022“…This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. The goal of using a Decision Tree is to create a training model that can use to predict the class or value of the target variable by learning simple decision rules inferred from prior data. …”
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Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
Published 2011“…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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Predicting game-induced emotions using EEG, data mining and machine learning
Published 2024“…Thus, this paper is proposed to introduce the use of data mining techniques in investigating the relationships between the frequency changes of EEG signals and the human emotion elicited when playing diferent kinds of computer games. …”
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