Paper Info
Title
TeknoAssistant : a domain specific tech mining approach for technical problem-solving support
Abstract
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.
Year
DOI
Venue
2022
10.1007/s11192-022-04280-2
Scientometrics
Keywords
DocType
Volume
TeknoAssistant, Text mining, SAO, Naive Bayes, NLP, Natural language processing
Journal
127
Issue
ISSN
Citations 
9
0138-9130
0
PageRank 
References 
Authors
0.34
11
4
Name
Order
Citations
PageRank
Garechana Gaizka100.34
Río-Belver Rosa200.34
Zarrabeitia Enara300.34
Alvarez-Meaza Izaskun400.34