This thesis represents a hybrid Arabic diacritizing system. The main objective of this thesis is ... more This thesis represents a hybrid Arabic diacritizing system. The main objective of this thesis is to build a system to diacritize Arabic text automatically using statistical model and morph-syntactical model. The first part of this system determines the most likely diacritics by choosing the full-form Arabic sub-sentence diacritization with the highest weight and probability estimation. The second part of the system factorizes and tokenizes each Arabic word into its possible morpho-syntactical constituent pattern, prefix, suffix, stem and root. After factorizing, the morpho-syntactical part selects the most likely diacritization sequence from different factorizations of the word. Most of the previous works on diacritization depend on tools such as Hidden Markov Model Toolkit (HTK) and/or higher linguistic knowledge such as morphology and syntax only, while this system uses statistical machine translation algorithm and ELXIRFM morphological analyzer. The accuracy rate of this hybrid s...
2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), 2015
This paper focuses on the effects of topic on the Arabic language used in Facebook, Twitter, news... more This paper focuses on the effects of topic on the Arabic language used in Facebook, Twitter, news sites, blogging sites, and mobile phone messaging. The results presented in this paper are based on a comprehensive study that was carried out using 8,538 text samples from these five forums. The sample topics are categorized into nine categories: political, social, economic, academic, religious, scientific, sports, arts, and others. The effect of topic is analyzed on several Arabic language aspects including the language whether Arabic, English, or mixed; the alphabet whether Arabic, English, or Arabizi; the dialect whether standard, colloquial, or mixed; the use of symbols; the style whether normal, metaphor, cynical, vulgar, or other; and the text cohesion level. This paper shows that there are large differences found in these six language aspects among the nine topic categories. Most notably, standard and refined language is common in serious topics such as religion and politics. Colloquial Arabic dialect and weak cohesion with Arabizi alphabet is common in casual topics such as social and academic topics.
This paper intends to present a large-scale dataset for Arabic morphology from a cognitive point ... more This paper intends to present a large-scale dataset for Arabic morphology from a cognitive point of view considering the uniqueness of the root-pattern phenomenon. The center of attention is focused on studying this singularity in terms of estimating associative relationships between roots as a higher level of abstraction for words meaning, and all their potential occurrences with multiple morpho-phonetic patterns. A major advantage of this approach resides in providing a novel balanced large-scale language resource, which can be viewed as an instantiated global root-pattern network consisting of roots, patterns, stems, and particles, estimated statistically for studying the morpho-phonetic level of cognition of Arabic. In this context, this paper asserts that balanced root-distribution is an additional significant key criterion for evaluating topic coverage in an Arabic corpus. Furthermore, some additional novel probabilistic morpho-phonetic measures and their distribution have been estimated in the form of root and pattern entropies besides bi-directional conditional probabilities of bi-grams of stems, roots, and particles. Around 29.2 million webpages of ClueWeb were extracted, filtered from non-Arabic texts, and converted into a large textual dataset containing around 11.5 billion word forms and 9.3 million associative relationships. As this dataset is predominantly considering the root-pattern phenomenon in Semitic languages, the acquired data might be significant support for researchers interested in studying phenomena of Arabic such as visual word cognition, morpho-phonetic perception, morphological analysis, and cognitively motivated query expansion, spell-checking, and information retrieval. Furthermore, based on data distribution and frequencies, constructing balanced corpora will be easier.
This paper is an attempt towards producing a utility to process documents over the Web in diversi... more This paper is an attempt towards producing a utility to process documents over the Web in diversified formats in a multilingual mode, and produce semi-translated documents from Arabic to English and the other way around, by using a term based approach. The process incorporates morphological analysis techniques of Arabic to handle the canonical forms of vocabularies in the terms stored
This paper addresses some issues involved in utilization of different levels of Arabic morphologi... more This paper addresses some issues involved in utilization of different levels of Arabic morphological knowledge in improving the search process in a search engine. The different levels of morphological knowledge can be considered as an incremental process considering the next sensitive word pattern in the context of enhancing the possibility of covering a higher recall and precision.
Abstract—The internet and smartphone penetrations continue to rising reaching large percentages o... more Abstract—The internet and smartphone penetrations continue to rising reaching large percentages of the world populations. Likewise, many Jordanians are actively communicating through the popular social networks and mobile phone messages. There are large questions and concerns related to the characteristics and quality of the language used in these forums and how to improve it. This study addresses these issues by collecting and analyzing a large sample of text from five sources: Facebook, Twitter, news sites, blogging sites, and mobile phone short messages. We analyzed the sample comprehensively including the sender, context, message, channel, and code. We present in this paper the results related to the used language, alphabet, dialect, text components, and style. The study concludes that the bilingualism problem is manifested in Twitter and Facebook with 24% and 14% of contributions in English, respectively. Moreover, 6.4% of the analyzed Arabic samples have English words and 13.2% are written in Arabizi (Arabic in English letters and numerals). The language dualism problem is manifested as 55.4% of the sample is in slang dialect, 36.4% in the formal Arabic, and 8.2% in formal with some slang words. Keywords—Arabic language; Jordan; social networks; Facebook; Twitter; blogging; electronic news sites; short messages
This thesis represents a hybrid Arabic diacritizing system. The main objective of this thesis is ... more This thesis represents a hybrid Arabic diacritizing system. The main objective of this thesis is to build a system to diacritize Arabic text automatically using statistical model and morph-syntactical model. The first part of this system determines the most likely diacritics by choosing the full-form Arabic sub-sentence diacritization with the highest weight and probability estimation. The second part of the system factorizes and tokenizes each Arabic word into its possible morpho-syntactical constituent pattern, prefix, suffix, stem and root. After factorizing, the morpho-syntactical part selects the most likely diacritization sequence from different factorizations of the word. Most of the previous works on diacritization depend on tools such as Hidden Markov Model Toolkit (HTK) and/or higher linguistic knowledge such as morphology and syntax only, while this system uses statistical machine translation algorithm and ELXIRFM morphological analyzer. The accuracy rate of this hybrid s...
2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), 2015
This paper focuses on the effects of topic on the Arabic language used in Facebook, Twitter, news... more This paper focuses on the effects of topic on the Arabic language used in Facebook, Twitter, news sites, blogging sites, and mobile phone messaging. The results presented in this paper are based on a comprehensive study that was carried out using 8,538 text samples from these five forums. The sample topics are categorized into nine categories: political, social, economic, academic, religious, scientific, sports, arts, and others. The effect of topic is analyzed on several Arabic language aspects including the language whether Arabic, English, or mixed; the alphabet whether Arabic, English, or Arabizi; the dialect whether standard, colloquial, or mixed; the use of symbols; the style whether normal, metaphor, cynical, vulgar, or other; and the text cohesion level. This paper shows that there are large differences found in these six language aspects among the nine topic categories. Most notably, standard and refined language is common in serious topics such as religion and politics. Colloquial Arabic dialect and weak cohesion with Arabizi alphabet is common in casual topics such as social and academic topics.
This paper intends to present a large-scale dataset for Arabic morphology from a cognitive point ... more This paper intends to present a large-scale dataset for Arabic morphology from a cognitive point of view considering the uniqueness of the root-pattern phenomenon. The center of attention is focused on studying this singularity in terms of estimating associative relationships between roots as a higher level of abstraction for words meaning, and all their potential occurrences with multiple morpho-phonetic patterns. A major advantage of this approach resides in providing a novel balanced large-scale language resource, which can be viewed as an instantiated global root-pattern network consisting of roots, patterns, stems, and particles, estimated statistically for studying the morpho-phonetic level of cognition of Arabic. In this context, this paper asserts that balanced root-distribution is an additional significant key criterion for evaluating topic coverage in an Arabic corpus. Furthermore, some additional novel probabilistic morpho-phonetic measures and their distribution have been estimated in the form of root and pattern entropies besides bi-directional conditional probabilities of bi-grams of stems, roots, and particles. Around 29.2 million webpages of ClueWeb were extracted, filtered from non-Arabic texts, and converted into a large textual dataset containing around 11.5 billion word forms and 9.3 million associative relationships. As this dataset is predominantly considering the root-pattern phenomenon in Semitic languages, the acquired data might be significant support for researchers interested in studying phenomena of Arabic such as visual word cognition, morpho-phonetic perception, morphological analysis, and cognitively motivated query expansion, spell-checking, and information retrieval. Furthermore, based on data distribution and frequencies, constructing balanced corpora will be easier.
This paper is an attempt towards producing a utility to process documents over the Web in diversi... more This paper is an attempt towards producing a utility to process documents over the Web in diversified formats in a multilingual mode, and produce semi-translated documents from Arabic to English and the other way around, by using a term based approach. The process incorporates morphological analysis techniques of Arabic to handle the canonical forms of vocabularies in the terms stored
This paper addresses some issues involved in utilization of different levels of Arabic morphologi... more This paper addresses some issues involved in utilization of different levels of Arabic morphological knowledge in improving the search process in a search engine. The different levels of morphological knowledge can be considered as an incremental process considering the next sensitive word pattern in the context of enhancing the possibility of covering a higher recall and precision.
Abstract—The internet and smartphone penetrations continue to rising reaching large percentages o... more Abstract—The internet and smartphone penetrations continue to rising reaching large percentages of the world populations. Likewise, many Jordanians are actively communicating through the popular social networks and mobile phone messages. There are large questions and concerns related to the characteristics and quality of the language used in these forums and how to improve it. This study addresses these issues by collecting and analyzing a large sample of text from five sources: Facebook, Twitter, news sites, blogging sites, and mobile phone short messages. We analyzed the sample comprehensively including the sender, context, message, channel, and code. We present in this paper the results related to the used language, alphabet, dialect, text components, and style. The study concludes that the bilingualism problem is manifested in Twitter and Facebook with 24% and 14% of contributions in English, respectively. Moreover, 6.4% of the analyzed Arabic samples have English words and 13.2% are written in Arabizi (Arabic in English letters and numerals). The language dualism problem is manifested as 55.4% of the sample is in slang dialect, 36.4% in the formal Arabic, and 8.2% in formal with some slang words. Keywords—Arabic language; Jordan; social networks; Facebook; Twitter; blogging; electronic news sites; short messages
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Papers by Mamoun Hattab
Keywords—Arabic language; Jordan; social networks; Facebook; Twitter; blogging; electronic news sites; short messages
Keywords—Arabic language; Jordan; social networks; Facebook; Twitter; blogging; electronic news sites; short messages