What’s Trending in AI — Topic Modeling of AI Papers in 2022

The article presents a detailed guide on using Cohere's NLP platform to perform topic modeling, semantic search, and clustering on AI research papers. It illustrates how to utilize Cohere's Embed endpoint for generating word embeddings from AI paper titles, which are then visualized using PCA and Altair for dimensionality reduction and chart creation. Through web scraping techniques, a dataset of AI papers from the Journal of Artificial Intelligence Research is compiled and cleaned, focusing on publications from 2020 onwards. The guide also demonstrates conducting semantic searches by comparing query embeddings with the dataset's embeddings using cosine similarity, and it further explores clustering by employing the KMeans algorithm to identify and visualize clusters of similar documents. The tutorial is designed to be replicated with other text datasets, emphasizing the ease of integration and powerful capabilities of Cohere's platform for extracting meaningful insights from large text collections.

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