lda-topic-model is an implementation of LDA for node.js. It extracts topics from a collection of text documents and then associates the documents with their respective topics. The model is trained by ...

Selected response items and constructed response (CR) items are often found in the same test. Conventional psychometric models for these two types of items typically focus on using the scores for ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. (Related posts: An intro to topic models for text analysis, Making sense of ...

This repository contains source code of STM model presented in [publication link]. STM is spiking neural network topic model than can effectively detect topics from the corpus of documents. All the ...

The clinical notes in electronic health records have many possibilities for predictive tasks in text classification. The interpretability of these classification models for the clinical domain is ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. In two earlier posts on this blog, I introduced topic models and explored some ...

This article follows the Direct Message methodology, designed to cut through the noise and reveal the deeper truths behind the stories we live. We live in a time when data is both overabundant and ...