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Road Map
David Jurgens edited this page Aug 10, 2013
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After semi-regular hiatuses, the S-Space package will be back in regular development. This page serves as a road map of features that are planned for futures versions. Users are encouraged to file issues for features they would like to see in future releases.
- Better support for writing SemanticSpace instances to external-program-friendly formats.
- Export to Matlab-friendly formats
- Complete re-working of how documents are handled by SemanticSpaces
- Allow tracking documents by name if the algorithm supports it
- Allow customized tokenization by the user. This could be just wrapping a List in a Document instance
- Allow for automatic parsing of documents, rather than requiring CoNLL-formatted input
- Out of the box support for Stanford or Malt parsers
- Add support for more IAA statistics (e.g., Kappa)
- Add a terrible GUI
- Seriously, this will be terrible, but at least it will lower the learning curve and potentially make it useful for non-programmers to work with the software
- Better support for compositional models
- Implementation of the common baseline compositional models:
- Mitchell and Lapata (2008)
- Erk and Padó (2008)
- Baroni and Zamparelli (2010)
- Some kind of common interface to support easily generating in-context meaning from a pre-built model
- Implementation of the common baseline compositional models:
- Deprecate (or hide) all of the static-method SVD and MatrixIO code
- Use the new MatrixFactorization interfaces
- Optionally start depending on some nice matrix library to do the heavy lifting (might be a 4.0.0 change, ha!)
- Support for automatically tuning the number of dimensions using the method described in Fourtassi and Dupoux (2013) at ACL 2013
- Support for new Deep Learning methods of generating semantic vectors
- Possible algorithms include
- Support for more compositional models
- Possibly support tensor operations?