Search results using timeline visualizations

1. OVERVIEW As search applications keep gathering new and diverse information sources, presenting relevant information anchored in time becomes more important. Time can help in describing the context of a document or document collection or in recreating a particular historical period. Temporal information is available in every document either explicitly or implicitly. Recognizing such temporal information and exploiting it for document retrieval and presentation purposes are important features that can significantly improve the functionality of today’s search applications. A look at functionality of any of the current search engines shows that temporal aspects of documents are exclusively used to sort the hit list by date, which is primarily the date a Web page or a document has been created or last modified. In this demonstration, we present a new approach in which search results are arranged in a well-defined timeline using a few existing visualization metaphors. To take advantage of time related information for IR purposes, we process each document in a document annotation pipeline that extracts temporal expressions and produces output in TimeML. Recently TimeML has emerged as a standard markup language for events and temporal expressions in natural language [1]. As the basis for anchoring documents in time, we assume a discrete representation of time based on the Gregorian Calendar, with a single day being an atomic time interval called chronon. Our base