All workshops will be held on April 1st, 2012.
Workshops - Chair: David E. Losada
Research in Information Retrieval has traditionally focused on serving the best results for a single query. However, most users will issue multiple queries that form part of a search session involving an iteration of user-system interactions. This might be the result of users clarifying or refining their information needs (e.g. broadening or narrowing a search), in response to the search results (e.g. too few or too many hits). This workshop will focus on advances in Information Retrieval technology over query sessions. We aim to pro- vide discussion and promote research and development on three main themes: (1) retrieval models and ranking, (2) evaluation and test collections and (3) user interaction and interfaces.
This workshop aims to stimulate exploratory research in task-based and aggregated search, and to investigate synergies between these two areas. Research into 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. The challenge is when and how to capture and filter this context. Research into aggregated search (also known as integrated search) addresses the increasingly common IR paradigm of presenting to the user a result list with information from heterogeneous document and media types, such as Webpages, user-authored content, Wikipedia entries, images, locations, etc. The challenge is when and how to fuse different document and media types, and how to present results to the user.
People spend more and more time online, not just to find information, but with the goal of enjoying themselves and passing time. Research has begun to show that during casual-leisure search, peoples' intentions, their motivations, their criteria for success, and their querying behaviour all differ from typical web search, whilst potentially representing a significant portion of search queries. This workshop will investigate searching for fun, or casual-leisure search, and aims to understand this increasingly important type of searching, bring together relevant IR sub-communities (e.g. recommender systems, result diversity, multimedia retrieval) and related disciplines, discuss new and early research, and create a vision for future work in this area.
Searching for fun can be different in several ways: