Search Results - (( model evaluation styles algorithm ) OR ( problem representation matching algorithm ))
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Image matching using relational graph representation
Published 2005“…Feature-based matching algorithm cannot tackle the problem of matching ambiguities easily. …”
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Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function
Published 2012“…We resolve two non-trivial problems, i.e. semantic representation of text and the complexity of graph matching. …”
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Implementation of case-based reasoning in help desk system
Published 2019“…In my system, it consists of the following steps which are case representation and storage, case matching and retrieval. …”
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Undergraduates Project Papers -
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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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Conference or Workshop Item -
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Traditional schema theory does not support Lamatckian learning, i.e, forcing the genetic representation to match the solution found by the learning algorithm. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…For next, instead of k-means clustring, Fuzzy cmeans clustering is combined with Spatial Pyramid Matching image representation to improve the accuracy of classification results. …”
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Penilaian esei berbantukan komputer menggunakan teknik Bayesian dan pengunduran linear berganda
Published 2006“…MMB Technique only required a small size of training data. (3) Prediction process of writing style using Multiple Linear Regression (MLR) Algorithm. …”
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Effective query structuring with ranking using named entity categories for XML retrieval
Published 2016“…The systems focus on user query representation, user search intention identification and ranking algorithms to improve keyword search. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…The ADDIE model is applied in this study to develop products through the stages of analysis, design, development, implementation, and evaluation. …”
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Design of intelligent Qira’at identification algorithm
Published 2017“…To evaluate the algorithm, 350 samples for 10 types of Qira’at recitation are in used, and for justifying the best pattern classification, few algorithms are tested in the early preliminary evaluation with K-Nearest Neighbour, GMM and PPCA. …”
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A systematic review of face sketch recognition system / Nur Nabilah Bahrum, Samsul Setumin, Mohd Firdaus Abdullah, Mohd Ikmal Fitri Maruzuki and Adi Izhar Che Ani
Published 2023“…Even though the sketches contain all of the necessary information about the suspect face's spatial topology and geometric details, it is still difficult for manual face recognition to identify and match sketch representations to the corresponding photo. …”
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Using the line array representation as an alternative method for understanding whole number multiplication among primary students
Published 2015“…Problems that students had faced with using the array and dilemmas that researcher encountered throughout the study are discussed. …”
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Evolving fuzzy grammar for crime texts categorization
Published 2015“…Machine learning (ML) based methods are the popular solution for this problem. However, the developed models typically provide low expressivity and lacking in human-understandable representation. …”
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Summation Invariants Of Objects Under Projective Transformation Group With Application
Published 2016“…The role of invariants in computer vision has been advocated for various applications such as shape representation, shape matching, object recognition and robotic. …”
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A stylometry approach for blind linguistic steganalysis model against translation-based steganography
Published 2023“…This is because all translated in TBS text have an intrinsic structural styles that can be used to improve the performance of a blind steganalysis model. …”
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Computational stylometric model for oath and oath-like expressions in Quranic text
Published 2014“…Two, various experimental results from the proposed model are compared against expert evaluation. The results showed that the proposed stylometric model of oaths has scalability in detecting implicit oaths, obtains dissimilar generalization levels in discriminating oath takers, and better adding in oath expressions explanation.…”
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Isolated digit speech recognition in Malay language using Neuro-Fuzzy approach
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Conference or Workshop Item -
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Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki
Published 2024“…This is because CNN can automatically extract new image data from written material. The CNN model is trained and evaluated on a wide range of handwritten sample datasets. …”
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