MINing On Semantics
MINoS is a Semantic Web Mining pipeline that facilitates an implementation of a descriptive rule-mining algorithm. The pipeline consists of two high-level components: a backend and a frontend. All processing and computational steps occur within the former, whereas the former concerns a CLI to the user.
Users should first provide a set of constraints. These constraints will be used to automatically generate a suitable SPARQL query that matches the users' current topic of interest. This query will be used to retrieve a subset from a local or remote (SPARQL endpoint) Knowledge Graph. Upon the successful retrieval of the subset, its data will be made suitable for further processing by sampling the semantic contexts of all instances in the data set. These will then be offered to the rule-mining module, which will generate Semantic Association Rules with support and confidence values. Once generated, the rules will be presented to the user for evaluation, who may separate the wheat from the chaff by adding various filters. Finally, the user may choose to store any or all of the rules.
At present, the pipeline consists of three primary modules.
usage: rule_miner [-h] [-a ABOX] [-d DIRECTIVE] [-i] [-o OUTPUT] -t [TBOX] [-v]
arguments:
- -h, --help show this help message and exit
- -a ABOX, --abox ABOX ABox graph
- -d DIRECTIVE, --directive DIRECTIVE Directive for rule learning
- -i, --interactive Interactive mode
- -o OUTPUT, --output OUTPUT output path
- -t TBOX, --tbox TBOX TBox graph
- -v, --verbose increase output verbosity
usage: model_evaluator [-h] [-f FILTER] [-m MODEL] [-o OUTPUT] [-v]
arguments:
- -h, --help show this help message and exit
- -f FILTER, --filter FILTER Custom filter
- -m MODEL, --model MODEL Rule-based model
- -o OUTPUT, --output OUTPUT Output path
- -v, --verbose Increase output verbosity
usage: anomaly_detector [-h] [-a ABOX] [-i] [-m MODEL] [-o OUTPUT] [-v]
arguments:
- -h, --help show this help message and exit
- -a ABOX, --abox ABOX ABox graph
- -i, --interactive Interactive mode)
- -m MODEL, --model MODEL Rule-based model
- -o OUTPUT, --output OUTPUT output path
- -v, --verbose increase output verbosity