Dear all,
the LIMES team [1] is happy to announce the first open-source release of
LIMES 1.0.0, code name "Arctic Albatros". LIMES is an extensible,
time-efficient and accurate link discovery framework for the Web of Data
and implements time-efficient algorithms for link discovery such as the
original LIMES approach [2] for edit distances, EdJoin and PPJoin+, HR3
[3], HYPPO [4] and ORCHID [5]. LIMES supports the first planning
technique for link discovery HELIOS [7] for improving the runtime of
complex specifications. The new version also supports supervised and
unsupervised machine-learning algorithms for finding accurate link
specifications. Try it out and let us know what you think.
Website: http://limes.sf.net
Download: https://github.com/AKSW/LIMES-dev/releases/tag/1.0.0
GitHub: https://github.com/AKSW/LIMES-dev
User manual: http://aksw.github.io/LIMES-dev/user_manual/
Developer manual: http://aksw.github.io/LIMES-dev/developer_manual/
Feedback and tickets: https://github.com/AKSW/LIMES-dev
What is new in LIMES 1.0.0:
* New LIMES GUI
* New Controller that supports manual and graphical configuration
* New machine learning pipeline: supports supervised, unsupervised and
active learning algorithms
* New dynamic planning for efficient link discovery
* Updated execution engine to handle dynamic planning
* Added support for qualitative (Precision, Recall, F-measure etc.) and
quantitative (runtime duration etc.) evaluation metrics for mapping
evaluation, in the presence of a gold standard
* Added support for configuration files in XML and RDF formats
* Added support for pointsets metrics such as Mean, Hausdorff and Surjection
* Added support for MongeElkan, RatcliffObershelp string measures
* Added support for Allen's algebra temporal relations for event data
* Added support for all topological relations derived from the DE-9IM model
* Migrated the codebase to Java 8 and Jena 3.0.1
We would like to thank everyone who helped creating this release. We
also acknowledge the support of the SAKE [8], HOBBIT [9] and GEISER
projects [10].
View this announcement on Twitter and the AKSW blog:
* http://blog.aksw.org/limes-1-0-0-released/
* https://twitter.com/akswgroup/status/786864628579995648
Kind regards and link on,
The LIMES team
[1] http://limes.sf.net
[2] http://ijcai.org/Proceedings/11/Papers/385.pdf
[3] http://link.springer.com/chapter/10.1007%2F978-3-642-35176-1_24
[4] http://link.springer.com/article/10.1007%2Fs13740-012-0012-y
[5] http://link.springer.com/chapter/10.1007%2F978-3-642-41335-3_25
[6] http://svn.aksw.org/papers/2012/ESWC_EAGLE/public.pdf
[7]
http://iswc2014.semanticweb.org/raw.githubusercontent.com/lidingpku/iswc2014/master/paper/87960017-helios-execution-optimization-for-link-discovery.pdf?raw=true
[8] https://www.sake-projekt.de/en/start/
[9] https://project-hobbit.eu/
[10] http://www.projekt-geiser.de
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