TechNet 2.0: Expanding technology semantic network with qualitative relations to enhance reasoning capabilities

Serhad Sarica; Jianxi Luo

doi:10.1007/978-3-031-20418-0_6

TechNet 2.0: Expanding technology semantic network with qualitative relations to enhance reasoning capabilities

Serhad Sarica^*
, Jianxi Luo

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

3 Citations (Scopus)

Abstract

This paper introduces a new semantic network knowledge base that can support both explicit and implicit inferences across engineering design concepts. Our approach is to merge the previously constructed Engineering Knowledge Graph (EKG) and Technology Semantic Network (TechNet). The terms in EKG are mapped to TechNet and then their qualitative relations are added into TechNet. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Original language	English
Title of host publication	Design Computing and Cognition'22
Editors	John S Gero
Place of Publication	Cham
Publisher	Springer
Pages	85-93
ISBN (Electronic)	9783031204180
ISBN (Print)	9783031204173
DOIs	https://doi.org/10.1007/978-3-031-20418-0_6
Publication status	Published - 2023
Externally published	Yes
Event	10th International Conference on Design Computing and Cognition (DCC’22) - University of Strathclyde, Glasgow, United Kingdom Duration: 4 Jul 2022 → 6 Jul 2022

Conference

Conference	10th International Conference on Design Computing and Cognition (DCC’22)
Place	United Kingdom
City	Glasgow
Period	4/07/22 → 6/07/22

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@inproceedings{79a696f2ba8841dab327aa42a518b1a1,

title = "TechNet 2.0: Expanding technology semantic network with qualitative relations to enhance reasoning capabilities",

abstract = "This paper introduces a new semantic network knowledge base that can support both explicit and implicit inferences across engineering design concepts. Our approach is to merge the previously constructed Engineering Knowledge Graph (EKG) and Technology Semantic Network (TechNet). The terms in EKG are mapped to TechNet and then their qualitative relations are added into TechNet. {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.",

author = "Serhad Sarica and Jianxi Luo",

year = "2023",

doi = "10.1007/978-3-031-20418-0\_6",

language = "English",

isbn = "9783031204173",

pages = "85--93",

editor = "Gero, \{John S\}",

booktitle = "Design Computing and Cognition'22",

publisher = "Springer ",

note = "10th International Conference on Design Computing and Cognition (DCC{\textquoteright}22) ; Conference date: 04-07-2022 Through 06-07-2022",

}

Sarica, S & Luo, J 2023, TechNet 2.0: Expanding technology semantic network with qualitative relations to enhance reasoning capabilities. in JS Gero (ed.), Design Computing and Cognition'22. Springer , Cham, pp. 85-93, 10th International Conference on Design Computing and Cognition (DCC’22), Glasgow, United Kingdom, 4/07/22. https://doi.org/10.1007/978-3-031-20418-0_6

TechNet 2.0: Expanding technology semantic network with qualitative relations to enhance reasoning capabilities. / Sarica, Serhad; Luo, Jianxi.
Design Computing and Cognition'22. ed. / John S Gero. Cham: Springer , 2023. p. 85-93.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - TechNet 2.0

T2 - 10th International Conference on Design Computing and Cognition (DCC’22)

AU - Sarica, Serhad

AU - Luo, Jianxi

PY - 2023

Y1 - 2023

N2 - This paper introduces a new semantic network knowledge base that can support both explicit and implicit inferences across engineering design concepts. Our approach is to merge the previously constructed Engineering Knowledge Graph (EKG) and Technology Semantic Network (TechNet). The terms in EKG are mapped to TechNet and then their qualitative relations are added into TechNet. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

AB - This paper introduces a new semantic network knowledge base that can support both explicit and implicit inferences across engineering design concepts. Our approach is to merge the previously constructed Engineering Knowledge Graph (EKG) and Technology Semantic Network (TechNet). The terms in EKG are mapped to TechNet and then their qualitative relations are added into TechNet. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

UR - https://www.scopus.com/pages/publications/85181501602

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85181501602&origin=recordpage

U2 - 10.1007/978-3-031-20418-0_6

DO - 10.1007/978-3-031-20418-0_6

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9783031204173

SP - 85

EP - 93

BT - Design Computing and Cognition'22

A2 - Gero, John S

PB - Springer

CY - Cham

Y2 - 4 July 2022 through 6 July 2022

ER -

TechNet 2.0: Expanding technology semantic network with qualitative relations to enhance reasoning capabilities

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