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ETD Abstract Container

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Document Classification using Characteristic Signatures

Mondal, Abhro Jyoti
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511793852923472

Abstract Details

2017, MS, University of Cincinnati, Engineering and Applied Science: Computer Science.
Supervised document classification technique, proposes a model that is trained with a training set with fixed number of labeled classes and can be effectively used to classify documents under one of these labels in the test set. The major objective of our research was to identify text documents from labels or topics which are not present in the training set, yet appeared in the test set. We devised a method to identify and eliminate documents from such labels/topics that do not occur in the training set. This technique brings together the idea of template matching and document classification by creating characteristic signatures that are unique to each label in the training set. Using these signatures any unknown label could be detected and ignored in the test data-set. Our results clearly show that, these techniques are useful in classification of documents into known categories or labels, as well as identifying labels that don’t match with the predefined labels in training set.
Raj Bhatnagar, Ph.D. (Committee Chair)
Ali Minai, Ph.D. (Committee Member)
Shomir Wilson, Ph.D. (Committee Member)
69 p.
Computer Science
Text classification; Template matching; Signatures; Information retrieval

Recommended Citations

Citations

  • Mondal, A. J. (2017). Document Classification using Characteristic Signatures [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511793852923472

    APA Style (7th edition)

  • Mondal, Abhro. Document Classification using Characteristic Signatures. 2017. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511793852923472.

    MLA Style (8th edition)

  • Mondal, Abhro. "Document Classification using Characteristic Signatures." Master's thesis, University of Cincinnati, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511793852923472

    Chicago Manual of Style (17th edition)

ucin1511793852923472
322
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This open access ETD is published by University of Cincinnati and OhioLINK.