Template based affix stemmer for a morphologically rich language
نویسندگان
چکیده
Word stemming is one of the most significant factors that affect the performance of a Natural Language Processing (NLP) application such as Information Retrieval (IR) system, part of speech tagging, machine translation system and syntactic parsing. Urdu language raises several challenges to NLP largely due to its rich morphology. In Urdu language, stemming process is different as compared to that for other languages, as it not only depends on removing prefixes and suffixes but also on removing infixes. In this paper, we introduce a template based stemmer that eliminates all kinds of affixes i.e., prefixes, infixes and suffixes, depending on the morphological pattern of the word. The presented results are excellent and this stemmer can prove to be very affective for a morphologically rich language.
منابع مشابه
A Light Weight Stemmer for Urdu Language: A Scarce Resourced Language
Stemming is a procedure that conflates morphologically related terms into a single term without doing complete morphological analysis. Urdu language raises several challenges to Natural Language Processing (NLP) largely due to its rich morphology. The core tool of information retrieval (IR) is a Stemmer which reduces a word to its stem form. Due to the diverse nature of Urdu, developing its ste...
متن کاملStemming in Tamil for Affix Stripping
Stemming is the one of the most important step in many of the Natural Language processing tasks. Stemming reduces inflected words to a common stem/root word. Stemming process mainly carried out in English language because Tamil language is more complex in structure and more over it consists of critical grammatical rules. Tamil is a Dravidian language, mainly spoken by Tamil. Tamil words have mo...
متن کاملAn Affix Removal Stemmer for Natural Language
Stemming is the prerequisite step in Text Mining, Spelling Checker applications as well as a basic requirement for Natural Language Processing (NLP) tasks. Also it is very important in most of the Information Retrieval (IR) systems. This paper describes an affix stripping technique for finding out the stems from context free text in Nepali Language using lexical lookup based and rule based appr...
متن کاملUnsupervised Learning of Arabic Stemming Using a Parallel Corpus
This paper presents an unsupervised learning approach to building a non-English (Arabic) stemmer. The stemming model is based on statistical machine translation and it uses an English stemmer and a small (10K sentences) parallel corpus as its sole training resources. No parallel text is needed after the training phase. Monolingual, unannotated text can be used to further improve the stemmer by ...
متن کاملStemming Hausa text: using affix-stripping rules and reference look-up
Stemming is a process of reducing a derivational or inflectional word to its root or stem by stripping all its affixes. It is been used in applications such as information retrieval, machine translation, and text summarization, as their preprocessing step to increase efficiency. Currently, there are a few stemming algorithms which have been developed for languages such as English, Arabic, Turki...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Int. Arab J. Inf. Technol.
دوره 12 شماره
صفحات -
تاریخ انتشار 2015