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You searched for subject:(relevance decision rule). Showing records 1 – 2 of 2 total matches.

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Queensland University of Technology

1. Zhang, Libiao. Modelling uncertain decision boundary for text classification.

Degree: 2016, Queensland University of Technology

Text classification is to classify documents into predefined categories by learned classifiers. Classic text classifiers cannot unambiguously describe decision boundary between relevant and irrelevant documents because of uncertainties caused by feature selection and knowledge learning. This research proposes a three-way decision model for dealing with uncertain decision boundary based on rough sets and centroid solution to improve classification performance. It partitions training samples into three regions by two main boundary vectors, and resolves the boundary region by two derived boundary vectors to generate decision rules for making 'two-way' decisions.

Subjects/Keywords: Text Classification; Decision Boundary; Uncertainty; Rough Set; Three-way Decision; Euclidean Distance; Decision Rule; Centroid Training; Centroid Optimization; Relevance Prediction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhang, L. (2016). Modelling uncertain decision boundary for text classification. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/102042/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zhang, Libiao. “Modelling uncertain decision boundary for text classification.” 2016. Thesis, Queensland University of Technology. Accessed September 21, 2020. https://eprints.qut.edu.au/102042/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zhang, Libiao. “Modelling uncertain decision boundary for text classification.” 2016. Web. 21 Sep 2020.

Vancouver:

Zhang L. Modelling uncertain decision boundary for text classification. [Internet] [Thesis]. Queensland University of Technology; 2016. [cited 2020 Sep 21]. Available from: https://eprints.qut.edu.au/102042/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhang L. Modelling uncertain decision boundary for text classification. [Thesis]. Queensland University of Technology; 2016. Available from: https://eprints.qut.edu.au/102042/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. YIN HAINAN. Personalized information retrieval based on novelty feeback.

Degree: 2005, National University of Singapore

Subjects/Keywords: Personalized information retrieval; relevance judgment; topicality; novelty; relevance decision rule; incomplete learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

HAINAN, Y. (2005). Personalized information retrieval based on novelty feeback. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/14774

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

HAINAN, YIN. “Personalized information retrieval based on novelty feeback.” 2005. Thesis, National University of Singapore. Accessed September 21, 2020. http://scholarbank.nus.edu.sg/handle/10635/14774.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

HAINAN, YIN. “Personalized information retrieval based on novelty feeback.” 2005. Web. 21 Sep 2020.

Vancouver:

HAINAN Y. Personalized information retrieval based on novelty feeback. [Internet] [Thesis]. National University of Singapore; 2005. [cited 2020 Sep 21]. Available from: http://scholarbank.nus.edu.sg/handle/10635/14774.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

HAINAN Y. Personalized information retrieval based on novelty feeback. [Thesis]. National University of Singapore; 2005. Available from: http://scholarbank.nus.edu.sg/handle/10635/14774

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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