[go: up one dir, main page]

Markkandeyan et al., 2015 - Google Patents

Efficient machine learning technique for web page classification

Markkandeyan et al., 2015

Document ID
9804353603315084287
Author
Markkandeyan S
Indra Devi M
Publication year
Publication venue
Arabian Journal for Science and Engineering

External Links

Snippet

Web page classification plays a major role in information management and retrieval task. Feature selection is an important process for accurate classification of Web pages. Web pages contain several features, and more number of features reduce the classification …
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
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30634—Querying
    • G06F17/30657—Query processing
    • G06F17/30675—Query execution
    • G06F17/3069—Query execution using vector based model
    • 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
    • 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
    • G06F17/30707—Clustering or classification into predefined classes
    • 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
    • G06F17/30613—Indexing
    • G06F17/30619—Indexing indexing structures
    • 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
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G06K9/627—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches based on distances between the pattern to be recognised and training or reference patterns
    • 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
    • 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
    • G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
    • G06F17/30247—Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
    • 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
    • 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
    • G06K9/6267—Classification techniques
    • G06K9/6279—Classification techniques relating to the number of classes
    • 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

Similar Documents

Publication Publication Date Title
Harish et al. Representation and classification of text documents: A brief review
Yu et al. PEBL: Web page classification without negative examples
Tao et al. Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval
Jiang et al. A fuzzy self-constructing feature clustering algorithm for text classification
US7562060B2 (en) Large scale semi-supervised linear support vector machines
Chawla A novel approach of cluster based optimal ranking of clicked URLs using genetic algorithm for effective personalized web search
Liu et al. Clustering documents with labeled and unlabeled documents using fuzzy semi-Kmeans
CN111723179B (en) Feedback model information retrieval method, system and medium based on conceptual diagram
Zhang et al. Multi-label feature selection based on logistic regression and manifold learning
Li et al. Combination of multiple feature selection methods for text categorization by using combinatorial fusion analysis and rank-score characteristic
Markkandeyan et al. Efficient machine learning technique for web page classification
Zelaia et al. A multiclass/multilabel document categorization system: Combining multiple classifiers in a reduced dimension
Wang et al. A two-stage feature selection method for text categorization by using category correlation degree and latent semantic indexing
Srivastava et al. Learning-based text classifiers using the Mahalanobis distance for correlated datasets
Harrag et al. Improving Arabic Text Categorization Using Neural Network with SVD.
Zobeidi et al. Effective text classification using multi-level fuzzy neural network
Badawi et al. Termset weighting by adapting term weighting schemes to utilize cardinality statistics for binary text categorization
Roul Suitability and importance of deep learning feature space in the domain of text categorisation
Bounabi et al. Neural embedding & hybrid ml models for text classification
Zandieh et al. Clustering data text based on semantic
Silva et al. Towards expanding relevance vector machines to large scale datasets
Kuo et al. Ranking and selecting terms for text categorization via SVM discriminate boundary
Sailaja et al. New rough set-aided mechanism for text categorisation
Pandey et al. Hybrid Model with Word2vector in Information Retrieval Ranking
GHAREB et al. HYBRID STATISTICAL RULE-BASED CLASSIFIER FOR ARABIC TEXT MINING.