Compared and visualized the differences of term frequency and average response time in 3 years.

scrape Jokowi's speech in 2017 from official website and extract relevant keywords

This is solution for first assignment of Information Retrival course. The main task is to create the inverted index from given corpus with using only basic functionality (without using any moduls like nltk etc)) unless specified in task.

A Term Frequency and inverse distance Frenquency (TF-idF) algorithm in Java language using concurrent techniques

This program constructs an inverted index for the purposes of information retrieval. The index is sorted by documentID and displays document frequency for each term and term frequency for each posting.

A term frequency-inverse document frequency implementation (with Rocchio's algorithm) to find the most important terms in a given website obtained from the Google query.

A tool to help up and coming bloggers find trending content in their niche to maximize their traffic and engagement

Vector space modeling of MovieLens & IMDB movie data

Coursework project for STINTSY with the task of classifying excerpts according to who authored them. The Jupyter Notebook contains the ML text classification pipeline as well as a comprehensive documentation of the methodology and experiments done to achieve the best results.

Keywords network builder based on TF-IDF with the use of Hadoop platform

Returns Top 10 URL results and corresponding ranking scores for user entered search query.Implements conjunctive as well as disjunctive query processing and uses BM25 as the ranking function.Very Efficient, returns results for conjunctive queries in less than 50ms.

Indexed Twitter data in three distinct languages and implemented the BM25, Vector Space Model and DFR relevance models by tuning the parameters for obtaining optimal query processing results.

Source code for my team's project at Natural Language Processing Subject. The project is a Summarizer Text Application that using Term Frequency Logarithm Algorithm.

My implementation for Naive Bayes - As a part of Intro to Machine Learning at HUST

Calculated the term frequency for terms present in 2000 documents

A web crawler we created in CS 121: Information Retrieval class at UCI

A complete Python code used for "vectorizing" the given documents, and givng the "Cosine-Similarity" between the given documents.