LivingKnowledge goal is to bring a new quality into search and knowledge management technology for more concise, complete and contextualised search results.
The paper “Entity Timelines: Visual Analytics and Named Entity Evolution” co-written by A. Mazeika, T. Tylenda and G. Weikum has been published in the ACM Conference on Information and Knowledge Management CIKM’11, in Glasgow, UK, on October 24-28, 2011.
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.