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This was a HTML web scraping project with Python's libraries. The objective of the project was to extract user's comments in "mac power user" forum, cleanse data, tokenize text/comments, classify and store the words in datafrom.
TF-IDF (Term frequency, Inverse Document Frequency) is an algorithm or way to score the importance of words (or 'terms') based on how frequently they appear
A complete search engine experience built on top of 75 GB Wikipedia corpus with subsecond latency for searches. Results contain wiki pages ordered by TF/IDF relevance based on given search word/s. From an optimized code to the K-Way mergesort algorithm, this project addresses latency, indexing, and big data challenges.
This is NLP based project, completed during FALL of 2020 for CSE 4022 - Natural Language Processing. Nepali Text Summarizer circulates on the idea of tf-idf and cosine similarity.