Nguyen et al., 2012 - Google Patents

Divide-and-conquer memetic algorithm for online multi-objective test paper generation

Nguyen et al., 2012

Document ID
14748958065972298256
Author
Nguyen M
Hui S
Fong A
Publication year
Publication venue
Memetic Computing

External Links

Snippet

Online test paper generation (Online-TPG) generates a test paper automatically online according to user specification based on multiple assessment criteria, and the generated test paper can then be attempted online by user. Online-TPG is challenging as it is a multi …
Continue reading at link.springer.com (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386—Retrieval requests
    • G06F17/30424—Query processing
    • G06F17/30533—Other types of queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/12—Computer systems based on biological models using genetic models
    • G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30587—Details of specialised database models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/28—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/02—Knowledge representation
    • G06N5/022—Knowledge engineering, knowledge acquisition
    • G06N5/025—Extracting rules from data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705—Clustering or classification
    • G06F17/3071—Clustering or classification including class or cluster creation or modification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computer systems based on specific mathematical models
    • G06N7/005—Probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation

Similar Documents

Publication Publication Date Title
Laumanns et al. On the effects of archiving, elitism, and density based selection in evolutionary multi-objective optimization
Liang et al. Evolutionary Monte Carlo: applications to C p model sampling and change point problem
Kaya Multi-objective genetic algorithm based approaches for mining optimized fuzzy association rules
De La Iglesia et al. Data mining rules using multi-objective evolutionary algorithms.
CN110008259A (en) The method and terminal device of visualized data analysis
Filatovas et al. A preference-based multi-objective evolutionary algorithm R-NSGA-II with stochastic local search
Bourdache et al. Incremental elicitation of rank-dependent aggregation functions based on Bayesian linear regression
Zhang et al. Reinforcement learning with actor-critic for knowledge graph reasoning
Xia et al. A reinforcement-learning-based evolutionary algorithm using solution space clustering for multimodal optimization problems
Rokh et al. A new evolutionary optimization based on multi-objective firefly algorithm for mining numerical association rules
de la Iglesia et al. The application and effectiveness of a multi-objective metaheuristic algorithm for partial classification
Nguyen et al. Divide-and-conquer memetic algorithm for online multi-objective test paper generation
Hammami et al. A multi-objective hybrid filter-wrapper evolutionary approach for feature construction on high-dimensional data
Peng et al. Multi‐Objective Service Composition Using Enhanced Multi‐Objective Differential Evolution Algorithm
Yonar et al. Evaluation and comparison of metaheuristic methods to estimate the parameters of gamma distribution
Akila et al. Test case prioritization using modified genetic algorithm and ant colony optimization for regression testing
Al-Shboul et al. Initializing genetic programming using fuzzy clustering and its application in churn prediction in the telecom industry
Qian et al. A micro-cloning dynamic multiobjective algorithm with an adaptive change reaction strategy
Kalkreuth An empirical study on insertion and deletion mutation in cartesian genetic programming
Hadjiivanov et al. Epigenetic evolution of deep convolutional models
Michelakos et al. A hybrid classification algorithm evaluated on medical data
Gonzalez-Alvarez et al. Convergence analysis of some multiobjective evolutionary algorithms when discovering motifs
Nguyen et al. An efficient multi-objective optimization approach for online test paper generation
Ulrich Exploring structural diversity in evolutionary algorithms
Hruschka et al. Missing values imputation for a clustering genetic algorithm