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Examining Variations of Prominent Features in Genre Classification.

Kim, Dr Yunhyong and Ross, Prof Seamus (2007) Examining Variations of Prominent Features in Genre Classification.. In Proceedings Hawaiian International Conference on System Sciences.

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Abstract

This paper investigates the correlation between features of three types (visual, stylistic and topical types) and genre classes. The majority of previous studies in automated genre classification have created models based on an amalgamated representation of a document using a combination of features. In these models, the inseparable roles of different features make it difficult to determine a means of improving the classifier when it exhibits poor performance in detecting selected genres. In this paper we use classifiers independently modeled on three groups of features to examine six genre classes to show that the strongest features for making one classification is not necessarily the best features for carrying out another classification.

Item Type:Conference Paper
Keywords:information extraction, retrieval, genre classification, text classification, metadata, feature, automated classification, machine learning
Subjects:V Tools
M Resource Discovery
L Digital Repository, Digital Archive and Digital Library Models > LA Ingest
L Digital Repository, Digital Archive and Digital Library Models > LB Management
E Data Description, Documentation and Standards > EA Metadata
Document Language:English
ID Code:136
Deposited By:Kim, Dr Yunhyong
Deposited On:20 November 2007

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