VAST 2010 Mini Challenge #1 Award:VisWorks Text and Network Visual AnalyticsLei Shi, Weihong Qian, Furu Wei and Li TanIBMResearch-China.Visualizations- TIARA trend visualization combining river theme and word cloudmetaphorPeonynetworkvisualizationwithcustomizednode/edge/clusterrendering, styling and data mapping- Mashups synthesizing text, network, map and document visualizationsAnalytics Process- Data pre-processing: Segmentation, NE (people/location/organization)extraction/cleansingCategorization & correlation & summarization: clustering with countryinfo,people/location network generation,time-sensitivekeywordsummarization- Data-vis mapping: categorized temporal content - TIARA Vispeople/location relationships - Peony Network Vis-Visual analytics:interactive network role/relationship analysis,textcontentinteractive analyticsovervisualrepresentation
VAST 2010 Mini Challenge #1 Award: VisWorks Text and Network Visual Analytics Lei Shi, Weihong Qian, Furu Wei and Li Tan IBM Research - China • Visualizations − TIARA trend visualization combining river theme and word cloud metaphor − Peony network visualization with customized node/edge/cluster rendering, styling and data mapping − Mashups synthesizing text, network, map and document visualizations • Analytics Process − Data pre-processing: Segmentation, NE (people/location/organization) extraction/cleansing − Categorization & correlation & summarization: clustering with country info, people/location network generation, time-sensitive keyword summarization − Data-vis mapping: categorized temporal content – TIARA Vis people/location relationships – Peony Network Vis − Visual analytics: interactive network role/relationship analysis, text content interactive analytics over visual representation
Visual Analytics of Player and Key Location Network. Player networks built from documents by NE extractionand correlationSame network withNetwork withplayer icon sizeplayer's nationalitymapped to nodeand inter-countrybetweennessconnectioncentralityin thehighlighted (orangegraph, key playersedge),player iconconnectingthegroupssize indicatesare revealedoccurrence inthedocumentsColor coding the nodeMore connectedicon with playernetworkafteraddilgroup info, againkeylocations,icon"Dubai"is connectingsize still mapped todifferent playernodebetweennessgroups together, it iscentrality."Dubai" ihypothesized thatbridgingthey will comedisconnectedtogether at"Dubai"componentsfor the final armsdealing
• Player networks built from documents by NE extraction and correlation Visual Analytics of Player and Key Location Network ─ Network with player’s nationality and inter-country connection highlighted (orange edge), player icon size indicates occurrence in the documents ─ Same network with player icon size mapped to node betweenness centrality in the graph, key players connecting the groups are revealed ─ More connected network after adding key locations, icon size still mapped to node betweenness centrality, “Dubai” is bridging disconnected components ─ Color coding the node icon with player group info, again “Dubai” is connecting different player groups together, it is hypothesized that they will come together at “Dubai” for the final arms dealing
Text Content Summarization & AnalyticsSynthesizedvisualization ofpeople/locations/activities bycountry (group)calSaudYmuBMOICEGDrill downtoonespecific country"Venezuela"andthe discovery of"call-send-transfer-meet"PontiaipatterncoverSmeer ofee
• Synthesized visualization of people/location s/activities by country (group) Text Content Summarization & Analytics • Drill down to one specific country “Venezuela” and the discovery of “call-sendtransfer-meet” pattern
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Visualization Mashups for Crime Analysis