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A simple search engine built using Python 3.11 that implements TF-IDF weighting, page ranking, and cosine vector similarity, and utilizes NLTK libraries for tokenization and stemming.
An implementation for vector space models used in Information Retrieval for ranked retrieval. Uses TF, IDF, and normalizing on a textual dataset, mostly corpus from novels.
IR and text mining project to calculate candidate's job profile score based on factors such as Education, Discipline, Required Skills, Desired Skills, and Years of Experience. Implemented Inverted Index algorithm for job filtering and Vector Space Model algorithm for ranking the documents (Jobs).