Open-source AI paper index and fine-grained topic atlas across major conferences and journals.
HDBSCAN Tuning for BERTopic Models
We created a topic modeling pipeline to evaluate different topic modeling algorithms, including their performance on short and long text, preprocessed and not preprocessed datasets, and with different embedding models. Finally, we summarized the results and suggested how to choose algorithms based on the task.
LLM-adaptive embeddings (Zero-shot / LoRA) with Generative Topic Modeling & Agent-based workflow for social science text mining
Information extraction from unstructured text to build a knowledge graph using techniques from traditional NLP to pre-trained transformers and LLMs for NER and Linking, and Relation Extraction.
Project scripts for network analysis of topics discovered by Math Research Compass
An interactive dashboard for exploring mathematical research trends on arXiv
Topic modeling for NYT articles.
Slides, Notebook and Data for Presentation: DataHour: Harnessing ML and NLP for Elevated Customer Experiences
Meta-Lingo is a comprehensive desktop application designed for corpus linguistics research. Built with modern technologies (Electron + React + Python FastAPI), it provides powerful tools for multimodal corpus management, linguistic analysis, and annotation.
We present our concept of a new type of Active-Learning for Deep Learning with NLP text classification and experimentally prove its performance against Random Sampling as well as its runtime performance on the Security Threat dataset from CySecAlert. These new Active Learning algorithms are based on Sentence-BERT and BERTopic clustering algorith…
Topic modelling and analysis of different UK newspapers, primarily using BERTopic
AI-powered YouTube comment analysis with BERT sentiment detection, BERTopic clustering, and Ollama AI summaries. Built with Next.js 15, FastAPI, and HuggingFace transformers.
Forecasting Private Capital Market using published research and patents. Project developed at Michigan State University under the guidance of Dr. Mohammed Ghassemi for JP Morgan Chase.
Build interactive topic modeling pipelines.
Submission for CL4HEALTH @ LREC-COLING 2024
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