2022 •
TeknoAssistant : a domain specific tech mining approach for technical problem-solving support
Authors:
Enara Zarrabeitia, Izaskun Alvarez-Meaza, Rosa M Rio-Belver, Gaizka Garechana
Abstract:AbstractThis 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 Ber (...) AbstractThis 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.(Read More)
Gaizka Garechana, Rosa Río-Belver, Enara Zarrabeitia, Izaskun Alvarez-Meaza
Scientometrics ·
2022
Data mining |
Data science |
Artificial intelligence |
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