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Packs (add-ons) for SWI-Prolog |
Title: | RDF matching utils |
---|---|
Rating: | Not rated. Create the first rating! |
Latest version: | 0.1.5 |
SHA1 sum: | d7c6a6fc5978f4b6b7992b872fda3810a491e3d8 |
Author: | Chris Mungall <cmungall@gmail.com> |
Packager: | Chris Mungall <cmungall@gmail.com> |
Home page: | https://github.com/cmungall/index_util |
Download URL: | https://github.com/cmungall/rdf_matcher/releases/*.zip |
Requires: | index_util |
sparqlprog |
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Version | SHA1 | #Downloads | URL |
---|---|---|---|
0.1.5 | d7c6a6fc5978f4b6b7992b872fda3810a491e3d8 | 22 | https://github.com/cmungall/rdf_matcher/archive/v0.1.5.zip |
0.1.3 | 6f75440414c8ecd27f806f188476c7cf5c4e5b5d | 3 | https://github.com/cmungall/rdf_matcher/archive/v0.1.3.zip |
0.1.2 | c47d6b7c3c34afaa585f2e775d3193c9e778842e | 2 | https://github.com/cmungall/rdf_matcher/archive/v0.1.2.zip |
0.1.1 | 629127f82d6e80223711e7b5e5a0b6fd5e7abc38 | 2 | https://github.com/cmungall/rdf_matcher/archive/v0.1.1.zip |
![DOI](https://zenodo.org/badge/latestdoi/13996/cmungall/rdf_matcher)
(see below for use via Docker)
To run these examples, first:
`cd tests/data`
All matches, as TSV:
`rdfmatch -f tsv -i basic.ttl match`
Contrain to classes with `http://example.org/x/` prefix:
`rdfmatch -p x -f tsv -i basic.ttl match`
New matches:
`rdfmatch -p x -f tsv -i basic.ttl new_match`
Cache index in a temp folder:
`rdfmatch -X tmp -p x -f tsv -i basic.ttl new_match`
Learn match rule probabilities:
`rdfmatch -p x -X tmp -T -f tsv -v -i tests/data/basic.ttl -i tests/data/equivs.ttl learn > probrules.pro`
Note this requires a training set - owl:equivalentClass
is used for this
Once you you created the probabilistic rules, these can be applied:
`rdfmatch -f tsv -i tests/data/basic.ttl classify probrules.pro`
The library index_util is used for caching. Optionally this can go to disk
Use `./run.sh` instead of rdfmatch
. E.g.
`./run.sh -p x -f tsv -i tests/data/basic.ttl match`
Pack contains 17 files holding a total of 51.5K bytes.