Thesis (Ph. D.)--University of Florida, 1980. / Includes bibliographical references (leaves 176-179).

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Mode of access: World Wide Web. / Thesis (Ph. D.)--University of Hawaii at Manoa, 2005. / Includes bibliographical references (leaves 237-249). / Electronic reproduction. / Also available by subscription via World Wide Web / xv, 249 leaves, bound ill., maps (1 col.) 29 cm

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This work springs from the subjective need for limiting the translation bias. It has been noticed that a considerable amount of translation is allowed to be published and read mainly due to the importance of its readability in the target language and often overlooking the goal(s) of the source text. This seems to derive from two common presumptions: (1) That a text goal is the result of an irretrievable and indescribable intentionality and (2) That target text readability and the preservation of the source text goal are two incompatible goals of translation. And this is in turn the result of the long lived dichotomy of translation studies into literal and free or text-based and reader oriented approaches. This work attempts to show that both (I) and (2) are misconceptions. Given a reasonable characterisation, intentionality is retrievable from the text itself and revealing of the text goal, the preservation of which does not exclude the readability of the TT and vice versa. Based on pragmatic insights drawn mainly from the Gricean Maxims and Cooperative Principle, Speech Act theory and the Text Linguistic model, this work proceeds to argue the case by analysing three Arabic texts and their twenty-two translations (each text is translated seven to eight times by different translators). These are of three most common types of prose: the expository, the argumentative and the instructive types. The analysis revolves around the identification of the text goal in the SL and its preservation in the TL. During this process a number of models and theories that constitute a controversial view of intentionality are outlined and discussed with a view to breaking the polarity they form and finding a medium path that is apt for charting more plausibly the context, the text and the process of translation. It is hoped that the implications of such work will help improve the quality of translation, provide a more explicit and plausible contribution to the account for the process and to further the effort towards standardising the theory.

As yet, few explicit, practical and easy to implement marking scales for evaluating the quality of translations have been proposed. The purpose of this study is to introduce a new marking guide for making quantitative assessments of the quality of non-literary translations, and to test its practicality through a case study using the Arabic language. On the basis of the results, some generalizations about translation and translation quality assessment are made. Early treatments which dealt with the evaluation of translations are discussed, showing their merits and defects. The new marking guide is then described, including classification of errors and examples of each type of error. Guidelines are presented for the holistic subjective assessment, the guidelines are evaluated and the outcome discussed / Master of Arts (Hons)

Arabic is a major international language, spoken in more than 23 countries, and the lingua franca of the Islamic world. The number of Arabic-speaking Internet users has grown over nine-fold in the Middle East between the year 2000 and 2007, yet research in Arabic Information Retrieval (AIR) has not advanced as in other languages such as English. In this thesis, we explore techniques that improve the performance of AIR systems. Stemming is considered one of the most important factors to improve retrieval effectiveness of AIR systems. Most current stemmers remove affixes without checking whether the removed letters are actually affixes. We propose lexicon-based improvements to light stemming that distinguish core letters from proper Arabic affixes. We devise rules to stem most affixes and show their effects on retrieval effectiveness. Using the TREC 2001 test collection, we show that applying relevance feedback with our rules produces significantly better results than light stemming. Techniques for Arabic information retrieval have been studied in depth on clean collections of newswire dispatches. However, the effectiveness of such techniques is not known on other noisy collections in which text is generated using automatic speech recognition (ASR) systems and queries are generated using machine translations (MT). Using noisy collections, we show that normalisation, stopping and light stemming improve results as in normal text collections but that n-grams and root stemming decrease performance. Most recent AIR research has been undertaken using collections that are far smaller than the collections used for English text retrieval; consequently, the significance of some published results is debatable. Using the LDC Arabic GigaWord collection that contains more than 1 500 000 documents, we create a test collection of~90 topics with their relevance judgements. Using this test collection, we show empirically that for a large collection, root stemming is not competitive. Of the approaches we have studied, lexicon-based stemming approaches perform better than light stemming approaches alone. Arabic text commonly includes foreign words transliterated into Arabic characters. Several transliterated forms may be in common use for a single foreign word, but users rarely use more than one variant during search tasks. We test the effectiveness of lexicons, Arabic patterns, and n-grams in distinguishing foreign words from native Arabic words. We introduce rules that help filter foreign words and improve the n-gram approach used in language identification. Our combined n-grams and lexicon approach successfully identifies 80% of all foreign words with a precision of 93%. To find variants of a specific foreign word, we apply phonetic and string similarity techniques and introduce novel algorithms to normalise them in Arabic text. We modify phonetic techniques used for English to suit the Arabic language, and compare several techniques to determine their effectiveness in finding foreign word variants. We show that our algorithms significantly improve recall. We also show that expanding queries using variants identified by our Soutex4 phonetic algorithm results in a significant improvement in precision and recall. Together, the approaches described in this thesis represent an important step towards realising highly effective retrieval of Arabic text.

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Using information retrieval systems to gain access to documents in languages other than English is becoming an increasingly significant problem. Rules, theories, algorithms, and retrieval methods designed and developed for English and other morphologically similar languages may or may not apply in the linguistic environments of other languages. The problem is particularly acute in languages that differ radically from English on account of morphological rules. This thesis compares the effects of two indexing and retrieval techniques (stemming and root retrieval) on information retrieval in Arabic through an exploratory study of the handling of Arabic words by an English search engine. It also investigates how best to adapt existing English-language information retrieval systems for use with Arabic-language texts, and specifically to process words and their morphological variations. Search experiments, using 2000 Arabic documents and 40 Arabic search terms (nouns), were conducted with a Web search engine developed for English, AltaVista, to compare the performances of stemming and root retrieval and to investigate the possibility of adapting this engine for use with Arabic text. The results of the experiments show that more effective retrieval can be accomplished through stemming, and that it is possible to adapt the engine for use with Arabic without the need to develop root-retrieval features.

In this dissertation, I investigate the structural representation of mood in a Minimalist framework. This investigation is based on the study of mood particles in Modern Standard Arabic and the way they interact with (i) the verb and (ii) negation. Arabic subjunctive particles are compared to subjunctive Balkan particles. / The main suggestion is that Arabic clause structure involves an inflectional projection Modal Phrase (ModP) that hosts the subjunctive particle ?an as well as other mood particles all of which check verbal mood morphology through the operation Agree. / The subjunctive particle ?an is compared to Balkan subjunctive particles and is argued to be an inflectional element rather than a lower complementizer in the sense of Rizzi (1997). In particular, it is suggested that Arabic and Balkan subjunctive particles fall into two types: (i) Type 1 inflectional particles that check a mood feature with the verb and that may occur in clauses lacking the CP layer. These include Arabic ?an and Romanian sǎ, and (ii) Type 2 lower Comp particles that do not check any verbal feature and that require the projection of the CP layer. These include Greek na and Bulgarian da. / As far as the interaction of mood particles with negation, it is suggested that some mood particles including subjunctive ?an may select NegP and check verbal mood across negation. Other particles, however, may not select NegP and are incompatible with negation.