A Multi-Entity Knowledge Joint Extraction Method of Communication Equipment Faults for Industrial IoT
نویسندگان
چکیده
The Industrial Internet of Things (IIoT) deploys massive communication devices for information collection and process control. Once it reaches failure, will seriously affect the operation industrial system. This paper proposes a new method multi-entity knowledge joint extraction (MEKJE) IIoT equipment faults. constructs multi-task tightly coupled model fault entity relationship extraction. We use to implement word embedding bidirectional semantic capture generate computable text vectors. At same time, segmentation is proposed, which uses noise filtering distinguish multi-fault single corpus. constructed dataset failures in power conducted experiments. experimental results show that performs best tests with Faulty Text CLUENER dataset. In particular, achieves an F1 value 78.6% evaluation multiple entities, significant improvement 5–8% its accuracy recall. It enables effective mapping accurate data.
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ژورنال
عنوان ژورنال: Electronics
سال: 2022
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics11070979