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We live in an information age that requires us, more than ever, to represent, access, and use information. Over the last several decades, we have developed a modern science and technology for information retrieval, relentlessly pursuing the vision of a "memex" that Vannevar Bush proposed in his seminal article, "As We May Think." Faceted search plays a key role in this program. Faceted search addresses weaknesses of conventional search approaches and has emerged as a foundation for interactive information retrieval. User studies demonstrate that faceted search provides more effective information-seeking support to users than best-first search. Indeed, faceted search has become increasingly prevalent in online information access systems, particularly for e-commerce and site search. In this lecture, we explore the history, theory, and practice of faceted search. Although we cannot hope to be exhaustive, our aim is to provide sufficient depth and breadth to offer a useful resource to bothresearchers and practitioners. Because faceted search is an area of interest to computer scientists, information scientists, interface designers, and usability researchers, we do not assume that the reader is a specialist in any of these fields. Rather, we offer a self-contained treatment of the topic, with an extensive bibliography for those who would like to pursue particular aspects in more depth. Table of Contents: I. Key Concepts / Introduction: What Are Facets? / Information Retrieval / Faceted Information Retrieval / II. Research and Practice / Academic Research / Commercial Applications / III. Practical Concerns / Back-End Concerns / Front-End Concerns / Conclusion / Glossary
List of contents
I. Key Concepts.- Introduction: What Are Facets?.- Information Retrieval.- Faceted Information Retrieval.- II. Research and Practice.- Academic Research.- Commercial Applications.- III. Practical Concerns.- Back-End Concerns.- Front-End Concerns.- Conclusion.- Glossary.
About the author
Daniel Tunkelang is co-founder and chief scientist at Endeca, a leading provider of enterprise information access solutions. He heads up Endeca's efforts to develop features and capabilities that emphasize interactive information retrieval. Daniel is recognized as a leading advocate of human-computer information retrieval, a multidisciplinary effort to bridge the gap between the more systems-oriented work in information retrieval and the more cognitively focused approach in library and information science. He has organized annual workshops on the subject. He publishes The Noisy Channel, a widely read and cited blog on the information-seeking process. He also participates actively in both academic and industry conferences, recently attempting to bridge the gap between the two by organizing an Industry Track at SIGIR, the leading academic conference on information retrieval. Daniel holds undergraduate degrees in mathematics and computer science from MIT and a PhD in computer science fromCMU. Before co-founding Endeca, he worked at the IBM T. J. Watson Research Center and AT&T Labs. He lives in New York with his wife Kristin and daughter Lily.
