System Implementation and Testing of Proposed Language Independent Stemmer - Kasthuri, M (International Journal of Computer Sciences and Engineering, 2025)
Information Retrieval (IR) is an emerging discipline that involves methods, models and patterns to find the documents of an unstructured nature in the dynamic environment. Information Retrieval System (IRS) retrieves the user required information over billions of documents stored in millions of computers. Search Engine is playing a major role in Information Retrieval Systems (IRS) to identify the morphological variants of the language using Stemming. Stemming is an important pre-processing step in query-based systems such as IRS, Web Search Engine, Natural Language Processing (NLP), Big Data Analysis, etc. The purpose of stemming is to diminish different grammatical or word forms to a common base form. In this digital era, most of the web pages are designed using English and European languages. Similarly, the web pages designed with Indian and other Asian languages are also increasing. Search Engines available in Information Retrieval Systems required for dealing with the morphologically different languages in every fraction of a second. The study reveals that the approaches for developing the stemmer involve rule-based, machine learning and hybrid approach. However, each one of them has its own limitations. Therefore, it has been proposed to design the model for Language Independent Stemmer using Dynamic Programming (DP) to retrieve the multi-linguistic web documents with the greater speed and accuracy. However, this research paper presents system implementation and testing of Proposed Language Independent Stemmer (PLIS). The performance of the proposed LIS has been analyzed using a test bed.