BUILDING SEMANTIC KERNEL FOR PERSIAN TEXT CLASSIFICATION WITH A SMALL AMOUNT OF TRAINING DATA

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JADIDINEJAD AMIR H.; MARZA VENUS

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Journal Paper

Paper Information

Journal: JOURNAL OF ADVANCES IN COMPUTER RESEARCH Year:2015 | Volume:6 | Issue:1 (19) Page(s): 125-136

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Information Journal Paper

Title

BUILDING SEMANTIC KERNEL FOR PERSIAN TEXT CLASSIFICATION WITH A SMALL AMOUNT OF TRAINING DATA

Author(s)

JADIDINEJAD AMIR H. | MARZA VENUS | Issue Writer Certificate

Keywords

SEMANTIC KERNEL

VECTOR SPACE KERNEL

SUPPORT VECTOR MACHINE

DIMENSIONALITY REDUCTION

TEXT CLASSIFICATION

Abstract

The original idea of SEMANTIC KERNELs is to use semantic features instead of terms appeared in the text document. In this article, the documents are transformed into a new k-dimensional feature space by applying Singular Value Decomposition on the Term-Document matrix and extracting k eigenvectors with higher energy. The suggested SEMANTIC KERNEL causes severe reduction of dimensions which leads to two main conclusions. First, the computational complexity of the classifier is severely reduced. Second, the trained classifier has less sensitivity on the input terms; therefore, it can classify documents effectively. Experiments on Persian documents indicate the absolute superiority of the suggested SEMANTIC KERNEL in comparison to well-known vector space (Bag-of-Words) kernel, especially under the circumstances in which external semantic resources are not available and the amount of available training data is not sufficient.

Cites

COMPUTING SEMANTIC SIMILARITY OF DOCUMENTS BASED ON SEMANTIC TENSORS

References

Cite

APA: Copy

JADIDINEJAD, AMIR H., & MARZA, VENUS. (2015). BUILDING SEMANTIC KERNEL FOR PERSIAN TEXT CLASSIFICATION WITH A SMALL AMOUNT OF TRAINING DATA. JOURNAL OF ADVANCES IN COMPUTER RESEARCH, 6(1 (19)), 125-136. SID. https://sid.ir/paper/328788/en

Vancouver: Copy

JADIDINEJAD AMIR H., MARZA VENUS. BUILDING SEMANTIC KERNEL FOR PERSIAN TEXT CLASSIFICATION WITH A SMALL AMOUNT OF TRAINING DATA. JOURNAL OF ADVANCES IN COMPUTER RESEARCH[Internet]. 2015;6(1 (19)):125-136. Available from: https://sid.ir/paper/328788/en

IEEE: Copy

AMIR H. JADIDINEJAD, and VENUS MARZA, “BUILDING SEMANTIC KERNEL FOR PERSIAN TEXT CLASSIFICATION WITH A SMALL AMOUNT OF TRAINING DATA,” JOURNAL OF ADVANCES IN COMPUTER RESEARCH, vol. 6, no. 1 (19), pp. 125–136, 2015, [Online]. Available: https://sid.ir/paper/328788/en

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