Stemmers for Tamil Language: Performance Analysis
نویسندگان
چکیده
Abstract— Stemming is the process of extracting root word from the given inflection word and also plays significant role in numerous application of Natural Language Processing (NLP). Tamil Language raises several challenges to NLP, since it has rich morphological patterns than other languages. The rule based approach light-stemmer is proposed in this paper, to find stem word for given inflection Tamil word. The performance of proposed approach is compared to a rule based suffix removal stemmer based on correctly and incorrectly predicted. The experimental result clearly show that the proposed approach light stemmer for Tamil language perform better than suffix removal stemmer and also more effective in Information Retrieval System (IRS). KeywordsTamil morphology, Tamil stemmer, Light stemmer, Rule-based stemmer, NLP, Natural Language Processing.
منابع مشابه
A Case Study of Using Domain Analysis for the Conflation Algorithms Domain
This paper documents the domain engineering process for much of the conflation algorithms domain. Empirical data on the process and products of domain engineering were collected. Six conflation algorithms of four different types: three affix removal, one successor variety, one table lookup, and one n-gram were analyzed. Products of the analysis include a generic architecture, reusable component...
متن کاملAlgorithmic stemmers or morphological analysis? An evaluation
It is important in information retrieval (IR), information extraction, or classification tasks that morphologically related forms are conflated under the same stem (using stemmer) or lemma (using morphological analyzer). To achieve this for the English language, algorithmic stemming or various morphological analysis approaches have been suggested. Based on Cross-Language Evaluation Forum test c...
متن کاملA Comprehensive Analysis of Stemmers Available for Indic Languages
Stemming is the process of term conflation. It conflates all the word variants to a common form called as stem. It plays significant role in numerous Natural Language Processing (NLP) applications like morphological analysis, parsing, document summarization, text classification, part-of-speech tagging, question-answering system, machine translation, word sense disambiguation, information retrie...
متن کاملComparative Study of Various Persian Stemmers in the Field of Information Retrieval
In linguistics, stemming is the operation of reducing words to their more general form, which is called the ‘stem’. Stemming is an important step in information retrieval systems, natural language processing, and text mining. Information retrieval systems are evaluated by metrics like precision and recall and the fundamental superiority of an information retrieval system over another one is mea...
متن کاملEnhancing Root Extractors Using Light Stemmers
The rise of Natural Language Processing (NLP) opened new possibilities for various applications that were not applicable before. A morphological-rich language such as Arabic introduces a set of features, such as roots, that would assist the progress of NLP. Many tools were developed to capture the process of root extraction (stemming). Stemmers have improved many NLP tasks without explicit know...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- CoRR
دوره abs/1310.0754 شماره
صفحات -
تاریخ انتشار 2013