Hussein Soori

VSB - Technical University of Ostrava, Department of computer science, Research Assistant

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Address: Czech Republic

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Mark W. Post

The University of Sydney

Guy Denhiere

Centre National de la Recherche Scientifique / French National Centre for Scientific Research

Eitan Grossman

The Hebrew University of Jerusalem

Paolo Divizia

Masaryk University

Vishal Goyal

Punjabi University

Lev Manovich

Graduate Center of the City University of New York

Matthias Gallé

XRCE

Mark Beumer

Charles University, Prague

Émilie Pagé-Perron

University of Oxford

Ritesh Kumar

Agra University

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Papers by Hussein Soori

Internet of Things: Overview, Sources, Applications and Challenges

Advances in intelligent systems and computing, 2016

Nowadays, Internet of Things (IoT) is growing rapidly. Billions of devices are expected to be ass... more Nowadays, Internet of Things (IoT) is growing rapidly. Billions of devices are expected to be associated in the coming future. Smart and sensing devices have impacted the Big Data area through huge data generation and gathering during the communication between new physical object. The challenges in this communication process can be seen in the necessity to handle huge amount of data that can serve different purposes in various fields such as, medical, social, commercial, industrial and scientific fields. This study aims at presenting some of the most recent advances in IoT. We divided the study into four main parts: short history, Big Data concept, IoT sources (hardware and software), and finally some challenges and future expectations. The objective of the study is to give readers an updated description of the IoT and its impact on Big Data.

Evaluation of Google and Bing online translation of verb-noun collocations from English into Arabic

Journal of Modern Languages, Dec 31, 2015

This article aims to investigate and evaluate the translation of verb-noun collocation in English... more This article aims to investigate and evaluate the translation of verb-noun collocation in English into Arabic Google and Bing online translation engines. A number of sentences were used as a testing dataset to evaluate both engines. Human translations by three bilingual speakers were used as a gold standard. A simple evaluation metric was proposed to calculate the translation accuracy of verb-noun collocations. The results showed that Bing scored a verb-noun collocation value of 0.72 with a trend estimation ranging between 0.65 and 0.67. Google scored a verb-noun collocation value of 0.75 (3% higher than Bing) with a trend estimation ranging between 0.63 and 0.85. The results also showed that, in most cases, the Arabic translation output of both engines produced a one verb synonym which did not collocate with the different nouns in the testing data sentences. These results indicate that Google and Bing, so far, have not been able to resolve the verb-noun collocability problem in their Arabic output. This study and its results may shed some light on the problem and to develop new methods to improve Arabic verb noun collocability in the output translation of current machine translation engines.

Utilizing Text Similarity Measurement for Data Compression to Detect Plagiarism in Czech

Springer eBooks, 2015

ABSTRACT This paper attempts to apply data compression based similarity method for plagiarism det... more ABSTRACT This paper attempts to apply data compression based similarity method for plagiarism detection. The method has been used earlier for plagiarism detection for Arabic and English languages. In this paper we utilize this method for Czech language text from a local multi-domain Czech corpus with 50 original documents with non-plagiarized parts, and 100 suspicious documents. The documents were generated so that every document could have from 1 to 5 paragraphs. The suspicion rate in the documents was randomly chosen from 0.2 to 0.8. The findings of the study show that the similarity measurement based on Lempel-Ziv comparison algorithms is efficient for the plagiarized part of the Czech text documents with a success rate of 82.60%. Future studies may enhance the efficiency of the algorithms by including combined and more sophisticated methods.

Simple Stemming Rules for Arabic Language

Advances in intelligent systems and computing, Jul 17, 2012

ABSTRACT

Data Compression Approach for Plagiarism Detection

V nasi digitalni eře, je potřeba nastrojů pro detekci plagiatorstvi z důvodů obrovskeho poctu den... more V nasi digitalni eře, je potřeba nastrojů pro detekci plagiatorstvi z důvodů obrovskeho poctu denně rostoucich dokumentů ať již v akademicke sfeře ci mimo ni. Patři zde zpravy, ukoly studentů, bakalařske, magisterske ci disertacni prace. Zatimco někteři studenti použivaji metodu vyjmou a vložit, dalsi skupina studentů se uchyluje k různým způsobům plagiatorstvi, vcetně změn struktur vět, parafrazovani i nahrazeni slov jejich synonymem.Tato prace je zaměřena na vytvořeni nastroje pro detekci textoveho plagiatorstvi při odhalovani plagiatů v arabských a ceských textech, dale na provaděni pocatecnich casti kompresniho algoritmu s jejimi modifikacemi, kde podobnost textu může být měřena na zakladě podobnosti kompresnimi-metrik. Dale se tato prace zaměřuje na to, že zacleňuje tuto techniku v lexikonu ceských synonym a v ceskem stemmer, kde odhaluje semanticke plagiatorstvi vcetně parafrazovani a restrukturalizace ceských textů. Na druhe straně hledani kořenů slov a schopnost rozdělovani slov na slabiky je velmi důležite v oblastech vyhledavani informaci, dolovani dat a zpracovani jazyka. Vytvořeni kvalitnich pravidel pro rozklad na slabiky a hledani kořene slov je stěžejni. Jestě vyssi poptavka je u jazyků, jimiž hovoři sirsi populace, jako je napřiklad arabstina. Tato prace představuje novou metodu pro rozklad arabských slov na slabiky, založenou na arabských samohlaskach. Prace take představuje snadnou metodu pro hledani kořenů slov pro arabský jazyk. Pro doladěni výsledku teto metody, je nutne před použitim hledani kořenů slov, využit on-line syntetickeho analyzatoru. Ten se využiva pro lepsi kategorizaci různých slovni druhů. Po te, tyto výstupni slova je nutne porovnat pomoci elektronickeho slovniku.

A Linguistic Method into Stemming of Arabic for Data Compression

DATESO, 2013

Creating good stemming rules for the Arabic language comes from the importance of Arabic language... more Creating good stemming rules for the Arabic language comes from the importance of Arabic language as the sixth most used language in the word. Stemming is very important in information retrieval, data mining and language processing. With Arabic having complex morphology and grammatical properties, this poses a challenge for researchers in this field. In this paper, we try to use an online morphological parser to distinguish parts of speech (POS), and then set some extracting rules to produce stems, and finally, mismatch these stems with an electronic dictionary. As a pilot study for this method, in this paper we deal with three POS: nouns, verbs and adjectives.

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Advances in intelligent systems and computing, 2016

This paper aims at detecting semantic plagiarism in Czech texts. The paper integrates a similarit... more This paper aims at detecting semantic plagiarism in Czech texts. The paper integrates a similarity measure technique previously used for text compression along with a synonyms structured thesaurus and a stemming algorithm to detect rewording and restructuring of texts in Czech language. Out of a 100 GB corpus, we extracted 884 files of B.A., M.A., and Ph.D. students’ assignments, semester works and theses, from Computer Science major. The total size of the extracted testing data used was 1.98 GB of plain text for our initial experiment. The method is tested first on short texts. Then, the method is applied on longer texts of students’ assignments. Our results on short texts showed more accurate results to detect paraphrased texts of semantic similarity, but lower accuracy was detected in case of identical texts with rearranged paragraphs. Our results experiment conducted on the long texts corpus of students’ assignment and theses show a semantic plagiarism rate of 23.9 %. However, after manual scanning of documents, some noise results occur as a result of using the same technical terms and scientific definitions and references in bibliography lists in different documents. These results will be fine-tuned and optimized in the future by building a file—specific stop word list, additional exact match method and removing references and other standard text templates often used in certain parts of students’ assignment works and theses.

Metoda komprese dat pro detekci plagiátorství

Import 13/01/2017In our digital era, the need for plagiarism detection tools is growing with the ... more Import 13/01/2017In our digital era, the need for plagiarism detection tools is growing with the tremendous number of documents produced on daily basis in and outside academia in all fields of science. This includes, reports, students’ assignments, undergraduate and graduate theses and dissertations. While some students use cut and paste methods, some other students resort to different ways of plagiarism including, changing the sentence structure, paraphrasing and replacing words with their synonyms. This thesis focuses on creating textual plagiarism detection tools for detecting plagiarism of Arabic and Czech texts by implementing initial parts of a compression algorithm with its modifications where text similarity can be measured by compression-based similarity metrics. Next, it expands on this work by integrating this technique with a Czech synonyms thesaurus and a Czech stemmer to detect semantic plagiarism, including, paraphrasing and restructuring of Czech texts. On the other ...

Evaluation of Google and Bing online translation of verb-noun collocations from English into Arabic

Verb Noun Collocations in Arabic and Their Patterns in Lexicography

Jurnal Sultan Alauddin Sulaiman Shah (JSASS), Malaysia, Vol. 2, Issue 2, Pages: 14-27, 2016

This article is part of a study aiming to disambiguate Arabic verb-noun collocation in Machine Tr... more This article is part of a study aiming to disambiguate Arabic verb-noun collocation in Machine Translation (MT) and Natural Language Processing (NLP). This article investigates verb noun collocation in the Arabic language from a linguistic point of view. It reviews the main theoretical studies on collocation including early indications, concept, terminology and classification of collocation in the Arabic language. In addition to that, it also reviews contemporary collocation dictionaries and verb-noun collocation patterns and the possibility of using both traditional and current lexicography resources in sense disambiguation for NLP and MT. The final part of this article is dedicated to a suggested eclectic model of verb-noun collocation patterns in Arabic.

A Machine Translation Engine for Rendering Some English Verb Patterns into Arabic

This study attempts to find a solution to the problem of verb polysemantic ambiguity in current E... more This study attempts to find a solution to the problem of verb polysemantic ambiguity in current English–Arabic machine translation (MT) engines through the study of verb patterns. This problem shows up during the computational rendering of verb patterns, where most current engines would perform the rendition only syntactically while the verb lexical meaning would remain the same in different constructions in the SL. As a result of that, the TL equivalent would not change in the output translation of these engines, which would create verb polysemantic ambiguity. Part of this problem can be solved through the adoption of two merged models of verb patterns: Hornby&#39;s (1975) and Quirk et al.&#39;s (1985), the adoption of Quirk et al.&#39;s (1985) verb complementation classification, Quirk et al.&#39;s (ibid.) verb situation types and by adding semantic markers of the subject and object, such as: (+human), (-animate), etc., to the verb in an analytic model. This assumption is enhanced by two findings: lexically the verb determines the type of the complement construction and the selection of a verb to a certain construction depends on the semantic property of that verb. This study classifies polysemy of the verb in verb patterns into: (1) Polysemy of the verb in different verb patterns and (2) Polysemy of the verb in the same verb pattern. (2) is sub-classified into: (a) SL polysemy of the SL verb and (b) TL polysemy of the SL verb. The current study focuses on (1) and (2a). The results of this study have shown that by implementing an analytic model based on the syntactic and semantic features of the verb can work efficiently as selectional restrictions to identify the polysemous meaning of the verb during the computational rendering of verb patterns.

Simple Stemming Rules for Arabic Language

ABSTRACT

Utilizing Text Similarity Measurement for Data Compression to Detect Plagiarism in Czech

Advances in Intelligent Systems and Computing, 2015

Simple Rules for Syllabification of Arabic Texts

Communications in Computer and Information Science, 2011

ABSTRACT

Lecture Notes in Electrical Engineering, 2014

ABSTRACT With the huge amount of online and offline written data, plagiarism detection has become... more ABSTRACT With the huge amount of online and offline written data, plagiarism detection has become an eminent need for various fields of science and knowledge. Various context based plagiarism detection methods have been published in the literature. This paper, tries to develop a new plagiarism detection methods using text similarity for Arabic language text with 150 documents and 330 paragraphs (159 from the source document and 171 from Al-Khaleej corpus). The findings of the study show that the similarity measurement based on Lempel Ziv comparison algorithms is very efficient for the plagiarized part of the Arabic text documents with a successful rate of 71.42%. Future studies can improve the efficiency of the algorithms by combining more sophisticated computation, statistical and linguistics hybrid detection methods.

A Linguistic Method into Stemming of Arabic A Linguistic Method for Data into Compression Stemming of Arabic for Data Compression

Abstract. Creating good stemming rules for the Arabic language comes from the importance of Arabi... more Abstract. Creating good stemming rules for the Arabic language comes from the importance of Arabic language as the sixth most used language in the word. Stemming is very important in information retrieval, data mining and language processing. With Arabic having complex morphology and grammatical properties, this poses a challenge for researchers in this field. In this paper, we try to use an online morphological parser to distinguish parts of speech (POS), and then set some extracting rules to produce stems, and finally, mismatch these stems with an electronic dictionary. As a pilot study for this method, in this paper we deal with three POS: nouns, verbs and adjectives.

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VŠB - Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Data Compression Approach for Plagiarism Detection

In our digital era, the need for plagiarism detection tools is growing with the tremendous number... more In our digital era, the need for plagiarism detection tools is growing with the tremendous number of documents produced on daily basis in and outside academia in all fields of science. This includes, reports, students’ assignments, undergraduate and graduate theses and dissertations. While some students use cut and paste methods, some other students resort to different ways of plagiarism including, changing the sentence structure, paraphrasing and replacing words with their synonyms. This thesis focuses on creating textual plagiarism detection tools for detecting plagiarism of Arabic and Czech texts by implementing initial parts of a compression algorithm with its modifications where text similarity can be measured by compression-based similarity metrics. Next, it expands on this work by integrating this technique with a Czech synonyms thesaurus and a Czech stemmer to detect semantic plagiarism, including, paraphrasing and restructuring of Czech texts. On the other hand,

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An Mt Engine for Rendering Some English Verb Patterns into Arabic

An Mt Engine for Rendering Some English Verb Patterns into Arabic، للحصول على النص الكامل يرجى زي... more

Using verb-noun collocation for disambiguating verb polysemy in English-Arabic statistical machine translation / Hussein Khaled Hussein Soori

This thesis attempts to resolve the problem of verb-noun collocation in English-Arabic Machine Tr... more This thesis attempts to resolve the problem of verb-noun collocation in English-Arabic Machine Translation engines. This problem can be seen from the semantic ill-formed output produced by current machine translation systems when the wrong verb synonym is chosen for the Arabic translation. Initially, this problem starts when a given engine tries to select from a set of polysemous verbs in English to find the equivalent meaning of the verb in Arabic. Mostly, this selection depends on the syntactic environment and verb semantic features serving as selectional restrictions. These selectional restrictions can be very effective when it comes to solving verb polysemantic ambiguity, but lead to a dead end when trying to find the verb that collocates most with the noun in the output Arabic translation. To resolve this problem, this work uses a statistical method inspired by Church et al. (1991) in a prototype designed to retrieve verb-noun collocates in Arabic. The testing data sets for thi...