This award honors those who have made “… significant, sustained and continuing contributions to research in information retrieval”.
||“Information Retrieval as Augmentation of Human Intelligence”
“For significant and sustained contributions to information retrieval and data science. His work has defined many of the theoretical foundations of the language modeling approach, yielding major insights into areas such as smoothing methods, relevance feedback, topic diversification, and text representations that incorporate positional information. He and his collaborators have also pioneered the axiomatic approach to information retrieval, which continues to provide inspiration for retrieval model and evaluation research.”
|2018||Kalervo P. Jarvelin
||“Information Interaction in Context”
“For sustained and substantial contributions in the areas of information retrieval and seeking, interactive and task-based retrieval, and evaluation metrics and models. His contributions include one of the most widely used evaluation measures in information retrieval, multiple insights on information seeking tasks in real-world contexts, and the creation and use of searcher simulations to better understand search behaviors and to evaluate systems. His ability to integrate research in retrieval algorithms, models and evaluation with research in information seeking and context, reflect the breadth of his scholarly influence.”
|2015||Nicholas J. Belkin
||“People, Interacting with Information”
“For forty years of significant, sustained and continuing contributions to, and advocacy of, the study of information retrieval in the context of human information seeking. Of particular importance are his contributions to the study of user-system interaction, to the understanding of human information seeking tasks and strategies, and to the twin challenges of designing systems which accommodate these tasks and strategies, and of evaluating such systems in the context of these tasks and strategies.”
||“Information Retrieval as Engineering Science”
“For pioneering, sustained, and continuing contributions to the theoretical foundations of information retrieval and database systems. His work describing how learning methods can be used with retrieval models and indexing anticipated the current interest in learning ranking functions, his development of probabilistic retrieval models for database systems and XML was ground-breaking, and his recent work on retrieval models for interactive retrieval has inspired new research. His rigorous approach to research and research methods is an outstanding example for our field.”
||“An Interdisciplinary Perspective on Information Retrieval”
“For nearly thirty years of significant, sustained, and continuing contributions to research, for exceptional mentorship, and for leadership in bridging the fields of information retrieval and human computer interaction. Her contributions to both the theoretical development and practical implementations of Latent Semantic Indexing, question-answering, desktop search, combining search and navigation, and incorporating the user and their context, have all substantially advanced and enriched the field of Information Retrieval.”
|2006||C.J. “Keith” van Rijsbergen
“This acceptance talk is a curious mixture of personal history and developing ideas in the context of the growing field of IR covering several decades. I want to concentrate on models and theories, interpreted loosely, and try and give an insight into where I have got to in my thinking, where the ideas came from, and where I believe we are going. In the last few years I have been working on the development of what might be coined as a design language for IR. It takes its inspiration from Quantum Mechanics, but by analogy only. The mathematical objects represent documents; these objects might be vectors (or density operators) in an n-dimensional vector space (usually a Hilbert space).”
|2003||W. Bruce Croft
||“Information Retrieval and Computer Science: An Evolving Relationship”
For… “More than twenty years of significant, sustained and continuing contributions to research in information retrieval. His contributions to the theoretical development and practical use of Bayesian inference networks and language modelling for retrieval, and to their evaluation through extensive experiment and application, are particularly important. The Center for Intelligent Information Retrieval which he founded illustrates the strong synergies between fundamental research and its application to a wide range of practical information management problems.”
||“On theoretical argument in information retrieval”
SIGIR Forum, 34 (1), 1-10 (April 2000)
For… “Thirty years of significant, sustained and continuing contributions to research in information retrieval. Of special importance are the theoretical and empirical contributions to the development, refinement, and evaluation of probabilistic models of information retrieval.”
||“Users lost (summary): reflections on the past, future, and limits of information science”
SIGIR Forum, 31 (2), 16-27 (Fall 1997).
The first part contains personal reflections of the author related to the major events and issues that formed his professional life and research agenda. The second, and major part, considers the broad aspects of information science as a field: origin, problems addressed, areas of study, structure, specialties, paradigm splits, and education problems. The third part discusses the limits of information science in terms of internal limits imposed by the activities in the field and external limits imposed by the very human nature of information processing and use. Throughout, issues related to users and use are transposed, as being of primary concern.
||“The formalism of probability theory in IR: a foundation or an encumbrance?”
Probabilistic theories of retrieval bring to bear on the information search problem a high degree of theoretical coherence and deductive power. In principle, this power ought to be an invaluable asset. In practice, it has turned out to be a mixed blessing. The question considered here is whether the trappings of the probabilistic formalism strengthen or encumber IR research on balance.
|“The significance of the Cranfield tests on index languages”
See also Journal of Documentation 54(3), June 1998, 265-280.
|1988||Karen Spärck Jones
|“A look back and a look forward”
This paper is in two parts, following the suggestion that I first comment on my own past experience in information retrieval, and then present my views on the present and future.
|“About the future of automatic information retrieval”
See also SIGIR Forum 31(1) Salton memorial issue.