Search Results - (( pattern learning algorithms ) OR ((( patterns ant algorithm ) OR ( patterns graph algorithm ))))
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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Monograph -
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A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition
Published 2010“…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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Conference or Workshop Item -
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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A lightweight graph-based pattern recognition scheme in mobile ad hoc networks.
Published 2012“…Its one-cycle learning and divide and distribute recognition task approach allows DHGN to detect similar patterns in short of time. …”
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Book Section -
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Predicting energy consumption pattern based on top trending videos YouTube 2021 using machine learning techniques
Published 2022“…This project is about predicting energy consumption patterns based on trending videos on YouTube 2021 by using machine learning techniques. …”
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Final Year Project / Dissertation / Thesis -
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Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar
Published 2012“…Others have been looking beyond into the animal kingdom to learn how ants find their way to the food source.…”
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Research Reports -
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Distributed Multi-Feature Recognition Scheme for Greyscale Images
Published 2011“…Distributed Hierarchical Graph Neuron (DHGN) is a distributed single-cycle learning pattern recognition algorithm that can scale from coarse-grained to fine-grained networks and it has comparable accuracy to contemporary image recognition schemes. …”
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The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning
Published 2025“…These continuous updates makes the graph to be highly dynamic, where nodes/edges are added to or removed from the graph always. …”
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Proceeding Paper -
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Ontology enrichment with causation relations
Published 2014“…The proposed framework extracts initial semantic patterns for causation relation from the input samples, then filters these patterns using two novel algorithms, namely, the “Purpose Based Word Sense Disambiguation” which helps in determining the causation senses for input pair of words and the “Graph Based Semantics” which determines the existence of the causation relations in the sentence and to extract their cause-effect parts. …”
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CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning
Published 2023“…The novelty of our study lies in the Force Atlas 2 call graph development to capture malware behavior patterns. …”
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Conference or Workshop Item -
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…First, this study combines SPM with Sentence Scoring method as feature-based approach and Bellman-Ford algorithm as graph-based to validate the performance of SPM. …”
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Thesis -
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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Machine Learning Based Detection for Compromised Accounts on Social Media Networks
Published 2025“…Behavioral features include changes in posting frequency, interaction patterns, and location data. We employ machine learning algorithms to train models that can accurately classify accounts as compromised or legitimate based on these features. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Support Vector Machines are considered to be excellent patterns classification techniques.The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and may be done experimentally through time consuming human experience.To overcome this difficulty, an approach such as Ant Colony Optimization can tune Support Vector Machine parameters.Ant Colony Optimization originally deals with discrete optimization problems. …”
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Conference or Workshop Item -
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