Scientists at St. Jude Children's Research Hospital have reconciled two closely related but contentious mechanisms underlying ...

Large language models (LLMs), such as the model underpinning the functioning of the well-known conversational platform ChatGPT, have proved to be very promising for summarizing and generating written ...

Topic modeling is a method used in machine learning and natural language processing to discover abstract topics within text. The most common algorithm for topic modeling is Latent Dirichlet Allocation ...

The expansion of the World Wide Web and the increasing popularity of microblogging websites such as Twitter and Facebook has created massive stores of textual data that is short in length. Although ...

The contributions of Fific et al., Chechile et al. and Zhang et al. represent fundamental theoretical advances in individual difference modeling. Chechile's contribution argues for the viability of ...

One approach is to combine short texts into long pseudo-documents before training LDA. Another approach is to assume that there is only one topic per document [3]. jLDADMM provides implementations of ...

Measuring and analyzing the impact of your topic clusters To determine if your topic clusters are working effectively and to measure the success of your strategy, you can use various metrics and ...

Mining a document structure from multiple data sources in terms of their underlying topics has become an important task of document clustering. The traditional document clustering approach cannot be ...