Search Results - (( java implementation tree algorithm ) OR ( using string mining algorithm ))
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1
A new text-based w-distance metric to find the perfect match between words
Published 2020“…The k-NN algorithm is an instance-based learning algorithm which is widely used in the data mining applications. …”
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2
A Threshold-Based Combination of String and Semantic Similarity Measures for Record Linkage
Published 2011“…As experimental results indicate, the combined similarity measure which is based on the combination of string and semantic similarity measures outperforms the string and semantic similarity measures, which are used individually, with the F-measure of 99.1% in Restaurant dataset, and 88.3% in Cora dataset. …”
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3
A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining
Published 2009“…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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4
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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5
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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6
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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7
Random sampling method of large-scale graph data classification
Published 2024“…Finally, we classified the graphs of data blocks using the SVM algorithm. In experimental evaluation, our proposed method outperformed state-of-the-art graph kernels on graph classification datasets in terms of accuracy.…”
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