MetapathVis: Inspecting the Effect of Metapath in Heterogeneous Network Embedding via Visual Analytics

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dc.contributor.authorLi, Quanen_US
dc.contributor.authorTian, Yunen_US
dc.contributor.authorWang, Xiyuanen_US
dc.contributor.authorXie, Laixinen_US
dc.contributor.authorLin, Dandanen_US
dc.contributor.authorYi, Linglingen_US
dc.contributor.authorMa, Xiaojuanen_US
dc.date.accessioned2025-03-07T16:49:09Z
dc.date.available2025-03-07T16:49:09Z
dc.date.issued2025
dc.description.abstractIn heterogeneous graphs (HGs), which offer richer network and semantic insights compared to homogeneous graphs, the technique serves as an essential tool for data mining. This technique facilitates the specification of sequences of entity connections, elucidating the semantic composite relationships between various node types for a range of downstream tasks. Nevertheless, selecting the most appropriate metapath from a pool of candidates and assessing its impact presents significant challenges. To address this issue, our study introduces , an interactive visual analytics system designed to assist machine learning (ML) practitioners in comprehensively understanding and comparing the effects of metapaths from multiple fine‐grained perspectives. allows for an in‐depth evaluation of various models generated with different metapaths, aligning HG network information at the individual level with model metrics. It also facilitates the tracking of aggregation processes associated with different metapaths. The effectiveness of our approach is validated through three case studies and a user study, with feedback from domain experts confirming that our system significantly aids ML practitioners in evaluating and comprehending the viability of different metapath designs.en_US
dc.description.number1
dc.description.sectionheadersOriginal Article
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume44
dc.identifier.doi10.1111/cgf.15285
dc.identifier.issn1467-8659
dc.identifier.pages20
dc.identifier.urihttps://doi.org/10.1111/cgf.15285
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15285
dc.publisherEurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.subjectheterogeneous graphs
dc.subjectmetapath
dc.subjectnetwork embedding
dc.subjectvisual analytics
dc.subject• Human‐centred computing → Human computer interaction (HCI); Visualization; User studies
dc.titleMetapathVis: Inspecting the Effect of Metapath in Heterogeneous Network Embedding via Visual Analyticsen_US
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