Showing papers by "Aly A. Fahmy published in 2009"
06 Nov 2009
TL;DR: The proposed translation model (from Arabic to English) tackles the problem of building translation model by employing Inductive Logic Programming (ILP) to learn the language model from a set of example pairs acquired from parallel corpora and represent the languagemodel in a rule-based format that maps Arabic sentence pattern to English sentence pattern.
Abstract: Rule based machine translation systems face different challenges in building the translation model in a form of transfer rules. Some of these problems require enormous human effort to state rules and their consistency. This is where different human linguists make different rules for the same sentence. A human linguist states rules to be understood by human rather than machines. The proposed translation model (from Arabic to English) tackles the mentioned problem of building translation model. This model employs Inductive Logic Programming (ILP) to learn the language model from a set of example pairs acquired from parallel corpora and represent the language model in a rule-based format that maps Arabic sentence pattern to English sentence pattern. By testing the model on a small set of data, it generated translation rules with logarithmic growing rate and with word error rate 11%
10 citations
01 Jan 2009
TL;DR: The proposed model gives high accuracy in translating the Queries from English to Arabic solving the translation and transliteration ambiguities and with orthographic query expansion, it gave high degree of accuracy in handling OCR errors.
Abstract: In this paper, a novel for Query Translation and Expansion for enabling English/Arabic CLIR for both normal and OCR-Degraded Arabic Text model has been proposed, implemented, and tested. First, an English/Arabic Word Collocations Dictionary has been established plus reproducing three English/Arabic Single Words Dictionaries. Second, a modern Arabic Corpus has been built. Third, a model for simulating the Arabic OCR errors has been proposed. Forth, a comprehensive model for Query Translation and expansion is proposed. The model translates the Query from English to Arabic detecting and translating collocations, translating single words and transliterating names. It solves the replacement ambiguity then it expands the Arabic Query to handle the expected Arabic OCR errors. The proposed model gives high accuracy in translating the Queries from English to Arabic solving the translation and transliteration ambiguities and with orthographic query expansion, it gave high degree of accuracy in handling OCR errors.
6 citations
17 Feb 2009
TL;DR: A novel model for English/Arabic Query Translation to search Arabic text, and then expands the Arabic query to handle Arabic OCR-Degraded Text to give high degree of accuracy in handling OCR errors.
Abstract: This paper provides a novel model for English/Arabic Query Translation to search Arabic text, and then expands the Arabic query to handle Arabic OCR-Degraded Text. This includes detection and translation of word collocations, translating single words, transliterating names, and disambiguating translation and transliteration through different approaches. It also expands the query with the expected OCR-Errors that are generated from the Arabic OCR-Errors simulation model which proposed inside the paper. The query translation and expansion model has been supported by different libraries proposed in the paper like a Word Collocations Dictionary, Single Words Dictionaries, a Modern Arabic corpus, and other tools. The model gives high accuracy in translating the Queries from English to Arabic solving the translation and transliteration ambiguities and with orthographic query expansion; it gives high degree of accuracy in handling OCR errors.
3 citations