TeknoAssistant : a domain specific tech mining approach for technical problem-solving support

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...

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Bibliographic Details
Published in:Scientometrics 2022-09, Vol.127 (9), p.5459-5473
Main Authors: Garechana, Gaizka, Río-Belver, Rosa, Zarrabeitia, Enara, Alvarez-Meaza, Izaskun
Format: Article
Language:English
Subjects:
Bayesian analysis
Clustering
Computer Science
Data mining
Indicators
Information Storage and Retrieval
Library Science
Natural language processing
Network analysis
Problem solving
Scientific papers
Social networks
Social organization
Technicians
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Summary: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 Naïve 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.
ISSN:0138-9130
1588-2861
DOI:10.1007/s11192-022-04280-2