Automatic extraction of key data from design specifications is an important means to assist in engineering design automation. Considering the characteristics of diverse data types, small scale, insufficient character information content and strong contextual relevance of design specification, a named entity recognition model integrated with high-quality topic and attention mechanism, namely Quality Topic-Char Embedding-BiLSTMAttention-CRF, was proposed to automatically identify entities in design specification. Based on the topic model,an improved algorithm for high-quality topic extraction was proposed first, and then the high-quality topic information obtained was added into the distributed representation of Chinese characters to better enrich character features. Next, the attention mechanism was used in parallel on the basis of the BiLSTM-CRF model to fully mine the contextual semantic information. Finally, the experiment was performed on the collected corpus of Chinese ship design specification, and the model was compared with multiple sets of models. The results show that F-score (harmonic mean of precision and recall) of the model is 80.24%. The model performs better than other models in design specification, and is expected to provide an automatic means for engineering design.
周成，蒋祖华
. Named Entity Recognition of Design Specification Integrated with High-Quality Topic and Attention Mechanism[J]. Journal of Shanghai Jiaotong University(Science), 2024
, 29(6)
: 1169
-1180
.
DOI: 10.1007/s12204-022-2534-2
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