About: Python Framework for Vector Space Modelling that can handle unlimited datasets (streamed input, online algorithms work incrementally in constant memory).

• added the "hashing trick" (by Homer Strong)
• support for adding target classes in SVMlight format (by Corrado Monti)
• fixed problems with global lemmatizer object when running in parallel on Windows
• parallelization of Wikipedia processing + added script version that lemmatizes the input documents
• added class method to initialize Dictionary from an existing corpus (by Marko Burjek)

About: "Pattern" is a web mining module for Python. It bundles tools for data retrieval, text analysis, clustering and classification, and data visualization.

• Small bug fixes in overall + performance improvements.
• Module pattern.web: updated to the new Bing API (Bing API has is paid service now).
• Module pattern.en: now includes Norvig's spell checking algorithm.
• Module pattern.de: new German tagger/chunker, courtesy of Schneider & Volk (1998) who kindly agreed to release their work in Pattern under BSD.
• Module pattern.search: the search syntax now includes { } syntax to define match groups.
• Module pattern.vector: fast implementation of information gain for feature selection.
• Module pattern.graph: now includes a toy semantic network of commonsense (see examples).
• Module canvas.js: image pixel effects & editor now supports live editing

About: Source code for EM approximate learning in the Latent Topic Hypertext Model.

Initial Announcement on mloss.org.

About: The Hidden Topic Markov Model

Initial Announcement on mloss.org.

About: SenseClusters is a package of (mostly) Perl programs that allows a user to cluster similar contexts together using unsupervised knowledge-lean methods. These techniques have been applied to word [...]

Initial Announcement on mloss.org.