Text mining draw more and more attention recently, it has been applied on different domains including web mining, and sentiment analysis. Text preprocessing is an important stage in text mining. The main problems in text mining are structuring text data, and the very high dimensionality of text data. Natural language processing and morphological tools can be employed to reduce the dimensionality of text data. In addition, term weighting schemes can be used to enhance text representation as feature vector. Researches in the field of Arabic text mining are still fairly limited. The work of this book presents and compares the impact of text preprocessing on Arabic text classification using popular text classification algorithms. Text preprocessing includes applying different term weighting schemes, and Arabic morphological analysis (stemming and light stemming). Text Classification algorithms are applied on 7 Arabic corpora. Results show that Light stemming with term pruning is best feature reduction technique; Support Vector Machines and Naive Bayes variations outperform other algorithms; Weighting schemes impact the performance of distance based classifier."
Product Identifiers
Publisher
LAP Gmbh & Company KG
ISBN-10
3844319573
ISBN-13
9783844319576
eBay Product ID (ePID)
123249645
Product Key Features
Author
Motaz Saad
Publication Name
Arabic Text Classification
Format
Trade Paperback
Language
English
Publication Year
2011
Type
Language Course
Number of Pages
172 Pages
Dimensions
Item Length
9in
Item Height
0.4in
Item Width
6in
Item Weight
9.3 Oz
Additional Product Features
Topic
Arabic, Natural Language Processing, Information Technology