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Timeline as Information Retrieval and Ranking Unit in News Search

News articles are one of the most often read online documents, and the amount of news stories generated daily is quite large. News search engines are then often used to retrieve relevant news articles. The understanding of the returned results can be however impaired when the returned articles are about events being parts of complex or long stories. In this paper we discuss the difficulties resulting from the missing context and information complexity that users searching in temporal news collections may face. To support users in their search and learning we propose the concept of timeline as a retrieval and ranking unit of news search. We believe that automatically generating and ranking timelines could become an effective mechanism to facilitate search and browsing in large news collections.