We propose a method to evaluate the significance of historical entities (people, events, and so on.). Here, the significance of a historical entity means how it affected other historical entities. Our proposed method first calculates the tempo-spacial impact of historical entities. The impact of a historical entity varies according to time and location. Historical entities are collected from Wikipedia. We assume that a Wikipedia link between historical entities represents an impact propagation. That is, when an entity has a link to another entity, we regard the former is influenced by the latter. Historical entities in Wikipedia usually have the date and location of their occurrence. Our proposed iteration algorithm propagates such initial tempo-spacial information through links in the similar manner as PageRank, so the tempo-spacial impact scores of all the historical entities can be calculated. We assume that a historical entity is significant if it influences many other entities that are far from it temporally or geographically. We demonstrate a prototype system and show the results of experiments that prove the effectiveness of our method.
Abstract. We propose techniques for achieving the geographical navigation of historical events described in Web pages as "Virtual History Tour". First, we develop a method for extracting information on the historical events from the Web and organizing it into a chronological table. Our method can effectively handle ambiguous cases -homonyms and multiple location names in a sentence -by using the number of cooccurrences among events, person names, location names, and addresses in the Web. Next, we propose a method for ranking historical entities according to their impacts at specific time and location. We extend the PageRank algorithm to calculate the temporal and spatial impacts of entities. Finally, we introduce our concrete application demonstrating how users can browse historical events through timeline and map interfaces.
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