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TeknoAssistant : a domain specific tech mining approach for technical problem-solving support
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DOI：10.1007/s11192-022-04280-2.png)
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摘要
En 中文
This paper presents TeknoAssistant, a domain-specific tech mining method for building a problem-solution conceptual network aimed at helping technicians from a particular field to find alternative tools and pathways to implement when confronted with a problem. We evaluate our approach using Natural Language Processing field, and propose a 2-g text mining process adapted for analyzing scientific publications. We rely on a combination of custom indicators with Stanford OpenIE SAO extractor to build a Bernoulli Naive Bayes classifier which is trained by using domain-specific vocabulary provided by the TeknoAssistant user. The 2-g contained in the abstracts of a scientific publication dataset are classified in either problem, solution or none categories, and a problem-solution network is built, based on the co-occurrence of problems and solutions in the abstracts. We propose a combination of clustering technique, visualization and Social Network Analysis indicators for guiding a hypothetical user in a domain-specific problem solving process.
Keyword:
TeknoAssistant
Text mining
SAO
Naive Bayes
NLP
Natural language processing
期刊
IF:
3.5
论文数:
8.1K
被引数:
2.2W
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