7 research outputs found
Tools and Methods to Analyze Multimodal Data in Collaborative Design Ideation
Collaborative design ideation is typically characterized by informal acts of sketching, annotation, and discussion. Designers have always used the pencil-and-paper medium for this activity, partly because of the flexibility of the medium, and partly because the ambiguous and ill-defined nature of conceptual design cannot easily be supported by computers. However, recent computational tools for conceptual design have leveraged the availability of hand-held computing devices for creating and sharing ideas. In order to provide computer support for collaborative ideation in a way that augments traditional media rather than imitates it, it is necessary to study the affordances made available by digital media for this process, and to study designers\u27 cognitive and collaborative processes when using such media. In this thesis, we present tools and methods to help make sense of unstructured verbal and sketch data generated during collaborative design, with a view to better understand these collaborative and cognitive processes. This thesis has three main contributions
ConceptScope: Organizing and Visualizing Knowledge in Documents based on Domain Ontology
Current text visualization techniques typically provide overviews of document
content and structure using intrinsic properties such as term frequencies,
co-occurrences, and sentence structures. Such visualizations lack conceptual
overviews incorporating domain-relevant knowledge, needed when examining
documents such as research articles or technical reports. To address this
shortcoming, we present ConceptScope, a technique that utilizes a domain
ontology to represent the conceptual relationships in a document in the form of
a Bubble Treemap visualization. Multiple coordinated views of document
structure and concept hierarchy with text overviews further aid document
analysis. ConceptScope facilitates exploration and comparison of single and
multiple documents respectively. We demonstrate ConceptScope by visualizing
research articles and transcripts of technical presentations in computer
science. In a comparative study with DocuBurst, a popular document
visualization tool, ConceptScope was found to be more informative in exploring
and comparing domain-specific documents, but less so when it came to documents
that spanned multiple disciplines.Comment: 19 pages, 5 figure
ConceptEVA: Concept-Based Interactive Exploration and Customization of Document Summaries
With the most advanced natural language processing and artificial
intelligence approaches, effective summarization of long and multi-topic
documents -- such as academic papers -- for readers from different domains
still remains a challenge. To address this, we introduce ConceptEVA, a
mixed-initiative approach to generate, evaluate, and customize summaries for
long and multi-topic documents. ConceptEVA incorporates a custom multi-task
longformer encoder decoder to summarize longer documents. Interactive
visualizations of document concepts as a network reflecting both semantic
relatedness and co-occurrence help users focus on concepts of interest. The
user can select these concepts and automatically update the summary to
emphasize them. We present two iterations of ConceptEVA evaluated through an
expert review and a within-subjects study. We find that participants'
satisfaction with customized summaries through ConceptEVA is higher than their
own manually-generated summary, while incorporating critique into the summaries
proved challenging. Based on our findings, we make recommendations for
designing summarization systems incorporating mixed-initiative interactions.Comment: 16 pages, 7 figure