ThemeRiver: Visualizing Thematic Changes in Large Document Collections
IEEE Transactions on Visualization and Computer Graphics
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Analysis and Interpretation of Visual Hierarchical Heavy Hitters of Binary Relations
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
Einstein: physicist or vegetarian? summarizing semantic type graphs for knowledge discovery
Proceedings of the 20th international conference companion on World wide web
Mining semantics for culturomics: towards a knowledge-based approach
Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
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The constantly evolving Web reflects the evolution of society. Knowledge about entities (people, companies, political parties, etc.) evolves over time. Facts add up (e.g., awards, lawsuits, divorces), change (e.g., spouses, CEOs, political positions), and even cease to exist (e.g., countries split into smaller or join into bigger ones). Analytics of the evolution of the entities poses many challenges including extraction, disambiguation, and canonization of entities from large text collections as well as introduction of specific analysis and interactivity methods for the evolving entity data. In this demonstration proposal, we consider a novel problem of the evolution of named entities. To this end, we have extracted, disambiguated, canonicalized, and connected named entities with the YAGO ontology. To analyze the evolution we have developed a visual analytics system. Careful preprocessing and ranking of the ontological data allowed us to propose wide range of effective interactions and data analysis techniques including advanced filtering, contrasting timeliness of entities and drill down/roll up evolving data.