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Found 27 papers, 4 papers with code
Reading Users' Minds from What They Say: An Investigation into LLM-based Empathic Mental Inference
In human-centered design, developing a comprehensive and in-depth understanding of user experiences, i. e., empathic understanding, is paramount for designing products that truly meet human needs.
AutoTRIZ: Artificial Ideation with TRIZ and Large Language Models
Researchers and innovators have made enormous efforts in developing ideation methods, such as morphological analysis and design-by-analogy, to aid engineering design ideation for problem solving and innovation.
Linguistic and Structural Basis of Engineering Design Knowledge
We examine the constituents of these knowledge graphs to understand the linguistic and structural basis of engineering design knowledge.
Retrieval Augmented Generation using Engineering Design Knowledge
Large-language Models (LLMs) need to adopt Retrieval-Augmented Generation (RAG) to generate factual responses that are better suited to knowledge-based applications in the design process.
The Innovation Paradox: Concept Space Expansion with Diminishing Originality and the Promise of Creative AI
Innovation, typically spurred by reusing, recombining, and synthesizing existing concepts, is expected to result in an exponential growth of the concept space over time.
Toward Artificial Empathy for Human-Centered Design: A Framework
Specifically, we conduct an interdisciplinary investigation of research areas such as data-driven user studies, empathic understanding development, and artificial empathy.
Biologically Inspired Design Concept Generation Using Generative Pre-Trained Transformers
This paper proposes a generative design approach based on the generative pre-trained language model (PLM) to automatically retrieve and map biological analogy and generate BID in the form of natural language.
Generative Transformers for Design Concept Generation
Generating novel and useful concepts is essential during the early design stage to explore a large variety of design opportunities, which usually requires advanced design thinking ability and a wide range of knowledge from designers.
Enhancing Patent Retrieval using Text and Knowledge Graph Embeddings: A Technical Note
We obtain citation and inventor embeddings through TransE that is trained using the corresponding knowledge graphs.
Embedding Knowledge Graph of Patent Metadata to Measure Knowledge Proximity
Knowledge proximity refers to the strength of association between any two entities in a structural form that embodies certain aspects of a knowledge base.
Design Representation as Semantic Networks
Here, we propose a methodology that utilizes a pre-trained large-scale cross-domain design knowledge base to automatically generate design representation as a semantic network, i. e., a network of the entities and relations, based on design descriptions in texts or natural languages.
Guiding Data-Driven Design Ideation by Knowledge Distance
In turn, knowledge distance guides the network-based exploration and retrieval of inspirational stimuli for inferences across near and far fields to generate new design ideas by analogy and combination.
Generative Pre-Trained Transformers for Biologically Inspired Design
Biological systems in nature have evolved for millions of years to adapt and survive the environment.
Generative Design Ideation: A Natural Language Generation Approach
This paper aims to explore a generative approach for knowledge-based design ideation by applying the latest pre-trained language models in artificial intelligence (AI).
Natural Language Processing in-and-for Design Research
We review the scholarly contributions that utilise Natural Language Processing (NLP) techniques to support the design process.
Generative Pre-Trained Transformer for Design Concept Generation: An Exploration
Novel concepts are essential for design innovation and can be generated with the aid of data stimuli and computers.
Patent Data for Engineering Design: A Critical Review and Future Directions
Patent data have long been used for engineering design research because of its large and expanding size, and widely varying massive amount of design information contained in patents.
Technology Fitness Landscape for Design Innovation: A Deep Neural Embedding Approach Based on Patent Data
Technology is essential to innovation and economic prosperity.
Deep Learning for Technical Document Classification
In large technology companies, the requirements for managing and organizing technical documents created by engineers and managers have increased dramatically in recent years, which has led to a higher demand for more scalable, accurate, and automated document classification.
Engineering Knowledge Graph from Patent Database
We propose a large, scalable engineering knowledge graph, comprising sets of (entity, relationship, entity) triples that are real-world engineering facts found in the patent database.
Data-Driven Design-by-Analogy: State of the Art and Future Directions
Design-by-Analogy (DbA) is a design methodology wherein new solutions, opportunities or designs are generated in a target domain based on inspiration drawn from a source domain; it can benefit designers in mitigating design fixation and improving design ideation outcomes.
Design Knowledge Representation with Technology Semantic Network
Engineers often need to discover and learn designs from unfamiliar domains for inspiration or other particular uses.
Stopwords in Technical Language Processing
There are increasingly applications of natural language processing techniques for information retrieval, indexing and topic modelling in the engineering contexts.
A Convolutional Neural Network-based Patent Image Retrieval Method for Design Ideation
This approach is also illustrated in a case study of robot arm design retrieval.
TechNet: Technology Semantic Network Based on Patent Data
The growing developments in general semantic networks, knowledge graphs and ontology databases have motivated us to build a large-scale comprehensive semantic network of technology-related data for engineering knowledge discovery, technology search and retrieval, and artificial intelligence for engineering design and innovation.
The Superior Knowledge Proximity Measure for Patent Mapping
Network maps of patent classes have been widely used to analyze the coherence and diversification of technology or knowledge positions of inventors, firms, industries, regions, and so on.
Digital Libraries Social and Information Networks
Multicores-periphery structure in networks
Many real-world networks exhibit a multicores-periphery structure, with densely connected vertices in multiple cores surrounded by a general periphery of sparsely connected vertices.
Social and Information Networks Physics and Society
