Abstract
Information Retrieval (IR) is the study of finding relevant information in unstructured collections of material based on a poorly specified query. In these lectures, I will describe the range of approaches used by search engines to retrieve relevant material. These approaches allow the modern search engines, which we are all familiar with, to be astonishingly accurate in locating what we seek. Here, text processing, link analysis, and extraction of data from interaction logs will be described. The lectures will cover the means used to evaluate the search engines. This final task has proven to be challenging, as it turns out that users are harder to model and measure than was perhaps once thought. By the end of the presentation, attendees will understand the key principles that underlie the algorithms of the major search engines; from the evaluation portion of the talk, they will learn methods of gathering feedback from users that has applications beyond IR.

Biography
Mark Sanderson is a Professor at RMIT University in the School of Computer Science and Information Technology. He is a researcher in information retrieval (IR) (e.g. web search engines) with particular interest in evaluation of search engines, as well as geographic search, cross language IR, summarisation, image retrieval by captions, and word sense ambiguity. He has raised over $6 million in research grant income over his career and has published extensively. He is currently Associate Editor of ACM Transactions on the Web and Information Processing and Management. He is also on the editorial board of Foundations and Trends® in Information Retrieval and will be the co-PC Chair of ACM SIGIR in 2012.