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Releases: mazlo/lodcc

v0.5.1

10 Jun 15:59
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With this minor release refactorings and changes in the package structure were expanded. This concerns in particular the util and graph.helpers package. Code in these packages was split up. New packages extras and graph.extras were introduced.

Besides that, this release comes with some fixes and improvements.

v0.5

30 May 22:33
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This release publishes a major refactoring and changes in the package structure of the framework. For instance,

  • core graph measures were extracted into a separate subpackage,
  • executable code can now be found in additional subpackages called *.tasks.*,
  • README files were updated and added for each of the subpackages.

Additionally, support for sqlite3 database was added and support for postgresql and mysql database was removed.

v0.4

23 Mar 16:06
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This release includes a whole bunch of new measures that can be computed on the graphs: RDF graph measures. The measures are contained in the sub-package graph/fernandez_at_el. It is a subset of measures from the paper "Characterizing RDF Graphs" by Fernandez et al.

Apart from that it includes lot of fixes.

v0.3

05 Jun 13:25
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The release targets a new feature: query generation. The sub-package "query" contains a generator that generators example queries for data graphs.

v0.2

05 Jun 13:22
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This release targets a restructuring and refactoring of the project. We created packages and sub-packages and renamed the main package from "lodcc" to "graph". The main executing program is "main.py".

v0.1.2

11 Dec 13:29
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This release contains updates to README (How to Cite, Links to results of a case study) and a LICENSE file.

v0.1.1

09 Dec 16:28
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Release for doi registration

v0.1.0

09 Dec 16:22
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This release contains the last stable version of the framework, used for
the analysis of 280 datasets in the LOD Cloud August 2017.

Supported feature sets:

  • Basic graph measures, e.g. vertices, edges, unique-edges, ..,
  • Degree-based measures, e.g. max-{in|out}-degree, graph
    centralization, ..,
    etc),
  • Edge-based measures, e.g. parallel-edges, diameter, .., and
  • Decriptive statistical measures, e.g. standard deviation and variable,
    power-law exponent values, ..