We present a dynamic web tool that allows interactive search and visualization of large news archives using an entity-centric approach. Users are able to search entities using keyword phrases expressing news stories or events and the system retrieves the most relevant entities to the user query based on automatically extracted and indexed entity profiles. From the computational journalism perspective, TimeMachine allows users to explore media content through time using automatic identification of entity names, jobs, quotations and relations between entities from co-occurrences networks extracted from the news articles. TimeMachine demo is available at http://maquinadotempo.sapo.pt/

翻译：我们提出了一个动态的网络工具,利用以实体为中心的方法对大型新闻档案进行互动搜索和可视化,用户能够使用关键词搜索实体,表达新闻报道或事件,该系统根据自动提取和索引化的实体概况检索用户查询的最相关实体。从计算新闻的角度来看,TimeMachine允许用户通过时间通过自动识别从新闻报道中提取的实体名称、工作、报价和实体之间的关系来探索媒体内容。TimeMachine演示可在http://maquinadotempo.sapo.pt/http://maquinatempo.pt/上查阅。