English Morphological Analysis with Machine-learned Rules

نویسنده

  • Xuri Tang
چکیده

This paper expounds an algorithm for morphological analysis of English language. The algorithm consists of two closely related components: morphological rule learning and morphological analyzing. The morphological rules are obtained through statistical learning from wordlist, with particular morphological features of English language taken into consideration. The procedure of morphological analysis considers two types of ambiguities: intersectional ambiguity and combinatory ambiguity. The procedure also considers the order of wordform formation in the language. Experiment shows that the algorithm performs distinctively compared to other algorithms. Keyword: Morphological analysis; statistical learning; intersectional ambiguity; combinatory ambiguity; wordform formation order

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Automatic Learning of Morphological Variations for Handling Out-of-Vocabulary Terms in Urdu-English Machine Translation

We present an approach for online handling of Out-of-Vocabulary (OOV) terms in UrduEnglish MT. Since Urdu is morphologically richer than English, we expect a large portion of the OOV terms to be Urdu morphological variations that are irrelevant to English. We describe an approach to automatically learn English-irrelevant (targetirrelevant) Urdu (source) morphological variation rules from standa...

متن کامل

Learning Transfer Rules for Machine Translation with Limited Data

The transfer-based approach to machine translation (MT) captures structural transfers between the source language and the target language, with the goal of producing grammatical translations. The major drawback of the approach is the development bottleneck, requiring many human-years of rule development. On the other hand, data-driven approaches such as example-based and statistical MT achieve ...

متن کامل

Multi-agent System Technology for Morphological Analysis

Machine Translation involves multiple phases including morphological, syntax and semantic analysis of source and target languages. Despite there are numerous approaches to machine translations, handling of semantics has been an unsolved research challenge. We have been researching to exploit power of multiagent Systems technology for machine translation by extending our rule-based machine trans...

متن کامل

Automatic Rule Induction in Arabic to English Machine Translation Framework

This chapter addresses the exploitation of a supervised machine learning technique to automatically induce Arabic-to-English transfer rules from chunks of parallel aligned linguistic resources. The induced structural transfer rules encode the linguistic translation knowledge for converting an Arabic syntactic structure into a target English syntactic structure. These rules are going to be an in...

متن کامل

Morphological Analysis and Synthesis by Automated Discovery and Acquisition of Linguistic Rules

':[his paper describes a rule-based machine learning approach to morphological processing in the system called XMAS. XMAS discovers and acquires linguistic rules from examples of morphological combinations and accomplishes the morphological analysis and synthesis by applying the rules. This approach is independent of languages, saves time and effort for development and maintenance, and takes sm...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006