Automated Keyword Extraction and Summarization for Romanian Texts

This research explores the theoretical and practical aspects of two fundamental tasks in Natural Language Processing: keyword extraction and extractive summarization, with a focus on the Romanian language. The study investigates the TextRank algorithm's application for identifying key terms and generating extractive summaries from texts in Romanian. The investigation reveals the algorithm's language independence, with minimal preprocessing requirements. The findings underscore the significance of automated text processing tools in enhancing information retrieval and document organization in Romanian. This study contributes to advancing Natural Language Processing methodologies and tools for Romanian language applications.