Authors:
Ashraf AbdelRaouf
1
;
Colin A. Higgins
1
;
Tony Pridmore
1
and
Mahmoud I. Khalil
2
Affiliations:
1
The University of Nottingham, United Kingdom
;
2
Ain Shams University, Egypt
Keyword(s):
Arabic Corpus, Optical Character Recognition, Data Retrieval, Morphological Analysis, Lexicon, Stemming Algorithm.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Computer Vision, Visualization and Computer Graphics
;
Data Engineering
;
Image Understanding
;
Information Retrieval
;
Information Retrieval and Learning
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Object Recognition
;
Ontologies and the Semantic Web
;
Pattern Recognition
;
Software Engineering
;
Symbolic Systems
;
Theory and Methods
Abstract:
Optical Character Recognition (OCR) is an important technology and has many advantages in storing information for both old and new documents. The Arabic language lacks both the variety of OCR systems and the depth of research relative to Roman scripts. An authoritative corpus is beneficial in the design and construction of any OCR system. Lexicon and stemming tools are essential in enhancing corpus retrieval and performance in an OCR context. A new lexicon/stemming algorithm is presented based on the Viterbi path method which uses a light stemmer approach. Lexicon and stemming lookup is combined to obtain a list of alternatives for uncertain words. This list removes affixes (prefixes or suffices) if there are any; otherwise affixes are added. Finally, every word in the list of alternatives is verified by searching the original corpus. The lexicon/stemming algorithm also assures the continuous updating of the contents of the corpus presented by (AbdelRaouf et al., 2010), which copes w
ith the innovative needs of Arabic OCR research.
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