Learning to Rank (full proceedings)
The main purpose of this workshop is to bring together information retrieval researchers and
machine learning researchers... The goal is to design and apply methods to automatically learn a function from training data, such that the function can sort objects (e.g., documents) according to their degrees of relevance, preference, or importance as defined in a specific application.
See Jon's coverage.
Focused Retrieval - (full proceedings)
Focused retrieval has been used to extract relevant sections from academic documents; and the application to text book searching is obvious (such commercial systems already exist). The purpose of this workshop is to raise issues and promote discussion on focused retrieval - that is, Question Answering (QA), Passage Retrieval, and Element Retrieval (XML-IR).
Information Retrieval for Advertising - (full proceedings)
Online advertising systems incorporate many information retrieval techniques by combining content analysis, user interaction models, and commercial constraints. Advances in online advertising have come from integrating several core research areas: information retrieval, data mining, machine learning, and user modeling. The workshop will cover a range of topics on advertising, with a focus on application of information retrieval techniques.
Mobile Information Retrieval (MobIR '08) - ( full proceedings)
Mobile Information Retrieval (MobIR'08) is a timely workshop concerned with the indexing and retrieval of textual, audio and visual information such as text, graphics, animation, sound, speech, image, video and their various possible combinations for use in mobile devices with wireless network connectivity.
Beyond Binary Relevance: Preferences, Diversity, and Set-Level Judgments - ( full proceedings)
New methods like preference judgments or usage data require learning methods, evaluation measures, and collection procedures designed for them. This workshop will address research challenges at the intersection of novel measures of relevance, novel learning methods, and core evaluation issues.
Future Challenges in Expertise Retrieval - (full proceedings and slides)
The main theme of the workshop concerns future challenges in Expertise Retrieval. Instead of focusing on core algorithmic aspects of a specific expert finding scenario (as is the case for the TREC Expert Finding task), our aim is to broaden the topic area and to seek for potential connections with other related fields.
Analytics for Noisy Unstructured Text Data (full proceedings behind ACM web login)
Noise in text can be defined as any kind of difference between the surface form of a coded
representation of the text and the intended, correct, or original text. The goal of the AND workshops is to focus on the problems encountered in analyzing noisy documents coming from various sources.
Best student paper award: Latent Dirichlet Allocation Based Multi-Document Summarization by Rachit Arora and Balaraman Ravindran
Workshops without proceedings online (yet):
Speech Search (SSCS)
Lastly, an older, but highly related workshop from WWW 2008:
Adversarial Information Retrieval (AIRWeb) - (program with papers and slides)
The program is structured around 3 sessions with presentations of peer-reviewed papers on Adversarial IR on the Web, covering usage analysis, network analysis and content analysis; followed by one session with the Web Spam Challenge results and a panel on the future of Adversarial IR on the Web.