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.
MCHttpRepositoryThe individual files can be downloaded at the following link:
location: 'https://www.hpi.uni-potsdam.de/swa/squeaksource/ldas'
user: ''
password: ''
This project is hosted on the SwaSource platform, which is now in read-only mode. Existing projects have been archived for read-only access.
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