TeknoAssistant
A domain specific tech mining approach for technical problem-solving support
Bibliographic Data
| ID | 21442667 |
|---|---|
| Authors | Gaizka Garechana-Anacabe (0000-0002-1913-3239, University of the Basque Country, corresponding author), Rosa-María Rio-Belver (0000-0002-4244-9098, University of the Basque Country), Enara Zarrabeitia Bilbao (0000-0002-2347-3885, University of the Basque Country), Izaskun Alvarez-Meaza (0000-0002-2110-0719, University of the Basque Country) |
| Year | 2022 |
| Volume | 127 |
| Issue | 9 |
| Pages | 5459-5473 |
| Publication date | 2022-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Scientometrics (JOURNAL) |
| Journal identifiers | ISSN: 0138-9130 • E-ISSN: 1588-2861 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11192-022-04280-2 |
| OpenAlex | W4210374967 |
| Language | EN |
| Citations received | 1 |
| References cited | 29 |
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
Classifier (UML) · Cluster analysis · Data mining · Data science · Domain (mathematical analysis) · Extractor · Field (mathematics) · Information retrieval · Machine learning · Naive Bayes classifier · Process (computing) · Support vector machine · Visualization · Vocabulary · Artificial Intelligence · Computer Science · Machine Learning in Materials Science · Open Source Software Innovations · Software Engineering Research
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |