Visual Analytics with Biclusters: Exploring Coordinated Relationships in Context

Exploring coordinated relationships is an important task in data analytics. For example, an intelligence analyst may want to find three suspicious people who all visited the same four cities. However, existing techniques that display individual relationships, such as between lists of entities, require repetitious manual selection and significant mental aggregation in cluttered visualizations to find coordinated relationships. This work presents a visual analytics approach that applies biclusters to support coordinated relationships exploration. Each computed bicluster aggregates individual relationships into coordinated sets. Thus, coordinated relationships can be formalized as biclusters. However, how to incorporate biclusters into a visual analytics tool to support sensemaking tasks is challenging. To address this, this work features three key contributions: 1) a five-level design framework for bicluster visualizations, 2) BiSet, highlighting bicluster-based edge bundling, seriation-based multiple lists ordering, and interactions for dynamic information foraging and management, and 3) an evaluation of BiSet.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Computer Science and Applications

Department dc:contributor.department

Computer Science

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2016

Author dc:creator

• Sun, Maoyuan

Chair dc:contributor.committeechair

• North, Christopher L.

Committee members dc:contributor.committeemember

• Luther, Kurt
• Riche, Nathalie
• Yao, Danfeng (Daphne)
• Ramakrishnan, Naren

• visual analytics
• biclusters
• coordinated relationship
• edge bundling

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

vt_gsexam:8722

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/72890