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@article{185876,
        author = {Binu P Chacko},
        title = {Applications of Information Extraction for Information Retrieval},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {3601-3611},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185876},
        abstract = {Large language models have emerged as transformative forces across various research fields, such as natural language processing (NLP), recommender systems, finance, and molecule discovery. They are primarily based on the Transformer architecture and undergo extensive pre-training on diverse textual sources, including web pages, research articles, books, and codes. The information is the most valuable resource for this kind of research works. It is necessary to get apt information in response to user query. In this respect, different tasks in information retrieval are elaborated in this article. Also, module-wise description is given to information retrieval, one of the applications of information extraction. For personalisation of LLM, RAG and PEFT are included. This article gives an outline of the information extraction/retrieval processes with personalisation ability.},
        keywords = {Information extraction, Information retrieval, RAG, PEFT},
        month = {October},
        }