Task-based search aims to understand the user's current task and desired outcomes, and how this may provide useful context for the Information Retrieval (IR) process. An example of task-based search is situations where additional user information on e.g. the purpose of the search or what the user already knows about the topic can provide valuable additional evidence that can significantly improve retrieval performance.

Task-based search may be especially useful in cases of aggregated search, also known as integrated search in the digital libraries domain. Aggregated search describes the increasingly common IR paradigm of presenting to the user one result list with information from different document and media types, such as Wikipedia entries, Webpages, user-authored content,
images, locations, etc. Research into aggregated search addresses the challenge of when and how to fuse different document and media types, and how to present results to the user. An example of aggregated search is the retrieval of scientific content, which involves searching among different domain-dependent document types and structures (e.g. full articles, short
abstracts, tables of content).

This workshop aims to stimulate exploratory research in task-based and aggregated search, and to investigate synergies between these two areas