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Latest Version
Avg Release Cycle
82 days
Latest Release
1060 days ago

Changelog History
Page 7

  • v0.8.1 Changes

    October 10, 2011
    • 👀 transactional similarity server: see docs/simserver.html
    • 🚚 website moved from university hosting to radimrehurek.com
    • much improved speed of lsi[corpus] transformation:
    • accuracy tests of incremental svd: test/svd_error.py and http://groups.google.com/group/gensim/browse_thread/thread/4b605b72f8062770
    • further improvements to memory-efficiency of LDA and LSA
    • 👌 improved wiki preprocessing (thx to Luca de Alfaro)
    • 🖨 model.print_topics() debug fncs now support std output, in addition to logging (thx to Homer Strong)
    • 🛠 several smaller fixes and improvements

  • v0.8.0 Changes

    June 28, 2011
    • 🔄 changed all variable and function names to comply with PEP8 (numTopics->num_topics): BREAKS BACKWARD COMPATIBILITY!
    • added support for similarity querying more documents at once (index[query_documents] in addition to index[query_document]; much faster)
    • rewrote Similarity so that it is more efficient and scalable (using disk-based mmap'ed shards)
    • simplified directory structure (src/gensim/ is now only gensim/)
    • 🛠 several small fixes and optimizations

  • v0.7.8 Changes

    March 26, 2011
    • ➕ added corpora.IndexedCorpus, a base class for corpus serializers (thx to Dieter Plaetinck). This allows corpus formats that inherit from it (MmCorpus, SvmLightCorpus, BleiCorpus etc.) to retrieve individual documents by their id in O(1), e.g. corpus[14] returns document #14.
    • 🔀 merged new code from the LarKC.eu team (corpora.textcorpus, models.logentropy_model, lots of unit tests etc.)
    • 🛠 fixed a bug in lda[bow] transformation (was returning gamma distribution instead of theta). LDA model generation was not affected, only transforming new vectors.
    • 📚 several small fixes and documentation updates

  • v0.7.7 Changes

    February 13, 2011
    • 🆕 new LDA implementation after Hoffman et al.: Online Learning for Latent Dirichlet Allocation
    • distributed LDA
    • ⚡️ updated LDA docs (wiki experiments, distributed tutorial)
    • matrixmarket header now uses capital 'M's: MatrixMarket. (André Lynum reported than Matlab has trouble processing the lowercase version)
    • 🚚 moved code to github
    • started gensim Google group

  • v0.7.6 Changes

    January 10, 2011
    • ➕ added workaround for a bug in numpy: pickling a fortran-order array (e.g. LSA model) and then loading it back and using it results in segfault (thx to Brian Merrel)
    • bundled a new version of ez_setup.py: old failed with Python2.6 when setuptools were missing (thx to Alan Salmoni).

  • v0.7.5 Changes

    November 03, 2010
    • further optimization to LSA; this is the version used in my NIPS workshop paper
    • got rid of SVDLIBC dependency (one-pass LSA now uses stochastic algo for base-base decompositions)

  • v0.7.4 Changes

    • sped up Latent Dirichlet ~10x (through scipy.weave, optional)
    • 👀 finally, distributed LDA! scales almost linearly, but no tutorial yet. see the tutorial on distributed LSI, everything's completely analogous.
    • 🛠 several minor fixes and improvements; one nasty bug fixed (lsi[corpus] didn't work; thx to Danilo Spinelli)

  • v0.7.3 Changes

    • ➕ added stochastic SVD decomposition (faster than the current one-pass LSI algo, but needs two passes over the input corpus)
    • published gensim on mloss.org

  • v0.7.2 Changes

    • ➕ added workaround for a numpy bug where SVD sometimes fails to converge for no good reason
    • 🔄 changed content of gensims's PyPi title page
    • completed HTML tutorial on distributed LSA

  • v0.7.1 Changes

    • 🛠 fixed a bug in LSA that occurred when the number of features was smaller than the number of topics (thx to Richard Berendsen)