Search Results - (( text classification parallel algorithm ) OR ( java implementation phase algorithm ))

Search alternatives:

  • Showing 1 - 14 results of 14
Refine Results
  1. 1
    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network

    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

    Published 2014
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…All the algorithm for the engine has been developed by using Java script language. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    Text classification using Naive Bayes: An experiment to conference paper

    Text classification using Naive Bayes: An experiment to conference paper by Sainin, Mohd Shamrie

    Published 2005
    “…The basic text classification technique in forum application has been discussed in Sainin (2005a) and Sainin (2005b).The paper explains about the use of the basic naïve Bayes algorithm to classify forum text me ssages into two classes namely clean and bad. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  4. 4
    Design and analysis of management platform based on financial big data

    Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

    Published 2023
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  6. 6
    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  7. 7
    Development of a parallel clustering of bilingual corpora based on reduced terms

    Development of a parallel clustering of bilingual corpora based on reduced terms by Leow, Ching Leong

    Published 2015
    “…However, not many works conducted that are related to clustering bilingual documents found, especially for Malay text articles. The quality of clustering bilingual text documents is highly influenced by the quality of the bag-of-word presentation of Malay text articles presented to the clustering algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, Norshuhani, Oxley, Alan, Abu Bakar, Zainab

    Published 2012
    “…Named Entity Recognition (NER) is the identification of words in text that correspond to a pre-defined taxonomy such as person, organization, location, date, time, etc.This article focuses on the person (PER), organization (ORG) and location (LOC) entities for a Malay journalistic corpus of terrorism.A projection algorithm, using the Dice Coefficient function and bigram scoring method with domain-specific rules, is suggested to map the NE information from the English corpus to the Malay corpus of terrorism.The English corpus is the translated version of the Malay corpus.Hence, these two corpora are treated as parallel corpora. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  9. 9
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…Named Entity Recognition (NER) is the identification of words in text that correspond to a pre-defined taxonomy such as person, organization, location, date, time, etc. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…Named Entity Recognition (NER) is the identification of words in text that correspond to a pre-defined taxonomy such as person, organization, location, date, time, etc. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    Projecting named entity tags from a resource rich language to a resource poor language

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…Named Entity Recognition (NER) is the identification of words in text that correspond to a pre-defined taxonomy such as person, organization, location, date, time, etc. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    Hybrid harmony search-artificial intelligence models in credit scoring

    Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

    Published 2019
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    Get full text
    Get full text
    Book Section
    Save to List
    Saved in:
  14. 14
    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: