An overview of the special issue

This special issue of SIGIR Forum marks the 40th anniversary of the ACM SIGIR Conference by showcasing papers selected for the ACM SIGIR Test of Time Award from the years 1978-2001. These papers document the history and evolution of IR research and practice, and illustrate the intellectual impact the SIGIR Conference has had over time. The ACM SIGIR Test of Time Award recognizes conference papers that have had a long-lasting influence on information retrieval research. When the award guidelines were created, eligible papers were identified as those that were published in a window of time 10 to 12 years prior to the year of the award. This meant that the first year this award was given, 2014, eligible papers came from the years 2002-2004. To identify papers published during the period 1978-2001 that might also be recognized with the Test of Time Award, a committee was created, which was led by Keith van Rijsbergen. Members of the committee were: Nicholas Belkin, Charlie Clarke, Susan Dumais, Norbert Fuhr, Donna Harman, Diane Kelly, Stephen Robertson, Stefan Rueger, Ian Ruthven, Tetsuya Sakai, Mark Sanderson, Ryen White, and Chengxiang Zhai. The committee used citation counts and other techniques to build a nomination pool. Nominations were also solicited from the community. In addition, a sub-committee was formed of people active in the 1980s to identify papers from the period 1978-1989 that should be recognized with the award. As a result of these processes, a nomination pool of papers was created and each paper in the pool was reviewed by a team of three committee members and assigned a grade. The 30 papers with the highest grades were selected to be recognized with an award. To commemorate the 1978-2001 ACM SIGIR Test of Time awardees, we invited a number of people from the SIGIR community to contribute write-ups of each paper. Each write-up consists of a summary of the paper, a description of the main contributions of the paper and commentary on why the paper is still useful. This special issue contains reprints of all the papers, with the exception of a few whose copyrights are not held by ACM (members of ACM can access these papers at the ACM Digital Library as part of the original conference proceedings). As members of the selection committee, we really enjoyed reading the older papers. The style was very different from todays SIGIR paper: the writing was simple and unpretentious, with an equal mix of creativity, rigor and openness. We encourage everyone to read at least a handful of these papers and to consider how things have changed, and if, and how, we might bring some of the positive qualities of these older papers back to the SIGIR program.

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[2]  M. E. Maron,et al.  On Relevance, Probabilistic Indexing and Information Retrieval , 1960, JACM.

[3]  Don R. Swanson,et al.  Probabilistic models for automatic indexing , 1974, J. Am. Soc. Inf. Sci..

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[5]  Stephen P. Harter,et al.  A probabilistic approach to automatic keyword indexing. Part II. An algorithm for probabilistic indexing , 1975, J. Am. Soc. Inf. Sci..

[6]  Stephen E. Robertson,et al.  Relevance weighting of search terms , 1976, J. Am. Soc. Inf. Sci..

[7]  Jeffrey Katzer,et al.  A study of the overlap among document representations , 1983, SIGIR '83.

[8]  C. J. van Rijsbergen,et al.  A Non-Classical Logic for Information Retrieval , 1997, Comput. J..

[9]  Nicholas J. Belkin,et al.  Information filtering and information retrieval: two sides of the same coin? , 1992, CACM.

[10]  W. Bruce Croft,et al.  A language modeling approach to information retrieval , 1998, SIGIR '98.

[11]  Mounia Lalmas,et al.  Information Retrieval: Uncertainty and Logics: Advanced Models for the Representation and Retrieval of Information , 1998 .

[12]  Thomas Hofmann,et al.  Probabilistic latent semantic indexing , 1999, SIGIR '99.

[13]  Fabio Crestani,et al.  Mathematical, Logical and Formal Methods in Information Retrieval: An Introduction to the Specia Issue , 2003, J. Assoc. Inf. Sci. Technol..

[14]  Djoerd Hiemstra,et al.  Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002 , 2003, SIGF.

[15]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[16]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[17]  Gregory N. Hullender,et al.  Learning to rank using gradient descent , 2005, ICML.

[18]  Michael R. Lyu,et al.  Effective missing data prediction for collaborative filtering , 2007, SIGIR.

[19]  Victor Lavrenko,et al.  A Generative Theory of Relevance , 2008, The Information Retrieval Series.

[20]  Norbert Fuhr.  Salton award lecture information retrieval as engineering science , 2012, SIGIR Forum.

[21]  Gediminas Adomavicius,et al.  Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques , 2012, IEEE Transactions on Knowledge and Data Engineering.

[22]  Mingxuan Sun,et al.  Learning multiple-question decision trees for cold-start recommendation , 2013, WSDM.

[23]  Jeffrey Dean,et al.  Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.

[24]  George Karypis,et al.  A Comprehensive Survey of Neighborhood-based Recommendation Methods , 2011, Recommender Systems Handbook.