期刊名称：Eastern-European Journal of Enterprise Technologies
印刷版ISSN：1729-3774
电子版ISSN：1729-4061
出版年度：2021
卷号：1
期号：2
页码：6-13
DOI：10.15587/1729-4061.2021.225362
语种：English
出版社：PC Technology Center
摘要：The Porter stemmer algorithm is a broadly used, however, an essential tool for natural language processing in the area of information access. Stemming is used to remove words that add the final morphological and diacritical endings of words in English words to their root form to extract the word root, i.e. called stem/root in the primary text processing stage. In other words, it is a linguistic process that simply extracts the main part that may be close to the relative and related root. Text classification is a major task in extracting relevant information from a large volume of data. In this paper, we suggest ways to improve a version of the Porter algorithm with the aim of processing and overcome its limitations and to save time and memory by reducing the size of the words. The system uses the improved Porter derivation technique for word pruning. Whereas performs cognitive-inspired computing to discover morphologically related words from the corpus without any human intervention or language-specific knowledge. The improved Porter algorithm is compared to the original stemmer. The improved Porter algorithm has better performance and enables more accurate information retrieval (IR).
关键词：stemming algorithm;natural language processing;information retrieval;APSA;Porter algorithm
