Using micro-documents for feature selection: The case of ordinal text classification
نویسندگان
چکیده
منابع مشابه
Using Micro-Documents for Feature Selection: The Case of Ordinal Text Classification
Most popular feature selection methods for text classification (TC) are based on binary information concerning the presence/absence of the feature in each training document. As such, these methods do not exploit term frequency information. In order to overcome this drawback we break down each training document of length k into k training “microdocuments”, each consisting of a single word occurr...
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متن کاملFeature Selection for Ordinal Text Classification
Ordinal classification (also known as ordinal regression) is a supervised learning task that consists of estimating the rating of a data item on a fixed, discrete rating scale. This problem is receiving increased attention from the sentiment analysis and opinion mining community due to the importance of automatically rating large amounts of product review data in digital form. As in other super...
متن کاملAn Improved K-Nearest Neighbor with Crow Search Algorithm for Feature Selection in Text Documents Classification
The Internet provides easy access to a kind of library resources. However, classification of documents from a large amount of data is still an issue and demands time and energy to find certain documents. Classification of similar documents in specific classes of data can reduce the time for searching the required data, particularly text documents. This is further facilitated by using Artificial...
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ژورنال
عنوان ژورنال: Expert Systems with Applications
سال: 2013
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2013.02.010