Context-Aware Timeline for Entity Exploration
نویسندگان
چکیده
With millions of articles in multiple languages, Wikipedia has become the de-facto source of reference on the Internet today. Each article on Wikipedia contains encyclopedic information about various topics (people, events, inventions, etc.) and implicitly represents an entity. Extracting the most important facts about such entity will help users to find desired information more quickly and effectively. However, this task is challenging due to the incomplete and noisy nature of Wikipedia articles. This calls for a mechanism to detect and summarize the most important information about an entity on Wikipedia. This thesis proposes and implements CATE (Context-Aware Timeline for Entity Exploration), a framework that utilizes Wikipedia to summarize and visualize the important aspects of entities in a timeline fashion. Such a system will help users to draw quickly an informative picture of an entity (e.g. life of a person, or evolution of a research topic, etc.). The novelty of CATE lies in seeing the entity in different contexts, synchronous with contemporaneous events. In addition, CATE puts the entity in a relationship with other entities, and thus offers a broader portrait about it. In order to efficiently query and visualize the events related to the entity, a number of techniques have been developed, combining information extraction and information retrieval with a novel ranking model. The thesis also discusses several experiments and evaluation results to show the effectiveness of the methods proposed.
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