Implementation of the LDA topic model in Squeak. Useful for natural language processing and code mining tasks.

'LDAllocator' consumes a set of "documents" (arrays of numbers between 1 to n), computes a set of "topics" (distributions over those numbers) and assigns to each document a distribution of topics. Topics and topic-document-assignments are chosen to maximize the probability of all documents being sampled, which results in orthogonal "concerns" being isolated.


Code commited to this repository will be automatically under MIT license.


location: 'https://www.hpi.uni-potsdam.de/swa/squeaksource/ldas'
user: ''
password: ''
The individual files can be downloaded at the following link:


This project is hosted on the SwaSource platform, which is now in read-only mode. Existing projects have been archived for read-only access.