Nicholas J. Belkin

Information filtering and information retrieval: two sides of the same coin?

Information filtering systems are designed for unstructured or semistructured data, as opposed to database applications, which use very structured data. The systems also deal primarily with textual information, but they may also entail images, voice, video or other data types that are part of multimedia information systems. Information filtering systems also involve a large amount of data and streams of incoming data, whether broadcast from a remote source or sent directly by other sources. Filtering is based on descriptions of individual or group information preferences, or profiles, that typically represent long-term interests. Filtering also implies removal of data from an incoming stream rather than finding data in the stream; users see only the data that is extracted. Models of information retrieval and filtering, and lessons for filtering from retrieval research are presented.

A case for interaction: a study of interactive information retrieval behavior and effectiveness

This study investigates the use and effectiveness of an ,advanced information retrieval (IR) system (INQUERY). 64 novice IR system users were studied in their use of a baseline version of INQUERY compared with one of three experimental versions, each offering a different level of interaction with a relevance feedback facility for automatic query reformulation. Results, in an inforumtion filtering task, indicate that: these subjects, after minimal training, were able to use the baseline system reasonably effectively; availability and use of relevance feedback increased retrieval effectiveness; and increased opportunity for user interaction with and control of relevance feedback made the interactions more efficient and usable while maintaining or increasing effective-

Cases, scripts, and information-seeking strategies: On the design of interactive information retrieval systems

Abstract The support of effective interaction of the user with the other components of the system is a central problem for information retrieval. In this paper, we present a theory of such interactions taking place within a space of information-seeking strategies, and discuss how such a concept can be used to design for effective interaction. In particular, we propose a model of information retrieval system design based on the ideas of: a multidimensional space of information-seeking strategies; dialogue structures for information seeking; cases of specific information-seeking dialogues; anti, scripts as distinguished prototypical cases. We demonstrate the use of this model by discussing in some detail the MERIT system, a prototype information retrieval system, that incorporates these design principles.

Combining the evidence of multiple query representations for information retrieval

Abstract We report on two studies in the TREC-2 program that investigated the effect on retrieval performance of combination of multiple representations of TREC topics. In one of the projects, five separate Boolean queries for each of the 50 TREC routing topics and 25 of the TREC ad hoc topics were generated by 75 experienced online searchers. Using the INQUERY retrieval system, these queries were both combined into single queries, and used to produce five separate retrieval results for each topic. In the former case, progressive combination of queries led to progressively improving retrieval performance, significantly better than that of single queries, and at least as good as the best individual single-query formulations. In the latter case, data fusion of the ranked lists also led to performance better than that of any single list. In the second project, two automatically produced vector queries and three versions of a manually produced P-norm extended Boolean query for each routing and ad hoc topic were compared and combined. This project investigated six different methods of combination of queries, and the combination of the same queries on different databases. As in the first project, progressive combination led to progressively improving results, with the best results, on average, being achieved by combination through summing of retrieval status values. Both projects found that the best method of combination often led to results that were better than the best performing single query. The combined results from the two projects have also been combined by data fusion. The results of this procedure show that combining evidence from completely different systems also leads to performance improvement.

Braque: design of an interface to support user interaction in information retrieval

We suggest that information retrieval is most appropriately considered as an inherently interactive process, and describe the design of an interface to a bibliographic information retrieval system that supports user interaction in an integrated fashion. A significant aspect of the interface design is its dependence upon a two-level hypertext model of information retrieval system databases, and the seamless support of a variety of information seeking strategies through the use of this model, and of a model of dimensions of information seeking behaviors.

Helping people find what they don't know

Imagine you are performing a task while interacting with a service hosted on the Internet or with an automated speech recognition mobile phone service. What if during your interaction with this service, a machine makes a recommendation suggesting how you could better perform your current task? An important problem relating to personalization concerns understanding how a machine can help an individual user via suggesting recommendations.

The cognitive viewpoint in information science

The meaning of the cognitive view of information science is briefly summarized, and representative works which propose or use this viewpoint are reviewed. It is shown, by example, that considering problems of information science from this point of view has led to significant advances in a variety of areas of information science, including bibliometrics, user studies, the reference interview and information retrieval. This variety of applications suggests that the cognitive viewpoint may be a powerful framework for the general theoretical and practical development of information science.

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

Information retrieval (IR) research has reached a point where it is appropriate to assess progress and to define a research agenda for the next five to ten years. This report summarizes a discussion of IR research challenges that took place at a recent workshop. The attendees of the workshop considered information retrieval research in a range of areas chosen to give broad coverage of topic areas that engage information retrieval researchers. Those areas are retrieval models, cross-lingual retrieval, Web search, user modeling, filtering, topic detection and tracking, classification, summarization, question answering, metasearch, distributed retrieval, multimedia retrieval, information extraction, as well as testbed requirements for future work. The potential use of language modeling techniques in these areas was also discussed. The workshop identified major challenges within each of those areas. The following are recurring themes that ran throughout: • User and context sensitive retrieval • Multi-lingual and multi-media issues • Better target tasks • Improved objective evaluations • Substantially more labeled data • Greater variety of data sources • Improved formal models Contextual retrieval and global information access were identified as particularly important long-term challenges.

Knowledge elicitation using discourse analysis

This paper is concerned with the use of discourse analysis and observation to elicit expert knowledge. In particular, we describe the use of these techniques to acquire knowledge about expert problem solving in an information provision environment. Our method of analysis has been to make audio-recordings of real-life information interactions between users (the clients) and human intermediaries (the experts) in document retrieval situations. These tapes have then been transcribed and analysed utterance-by-utterance in the following ways: assigning utterances to one of the prespecified functional categories; identifying the specific purposes of each utterance; determining the knowledge required to perform each utterance; grouping utterances into functional and focus-based sequences. The long-term goal of the project is to develop an intelligent document retrieval system based on a distributed expert, blackboard architecture.

The effect multiple query representations on information retrieval system performance

Five independently generated Boolean query formulations for ten different TREC topics were produced by ten different expert online searchers. These different formulations were grouped, and the groups, and combinations of them, were used as searches against the TREC test collection, using the INQUERY probabilistic inference network retrieval engine, Results show that progressive combination of query formulations leads to progressively improving retrieval performance, Results were compared against the performance of INQUERY natural language based queries, and in combination with them. The issue of recall as a performance measure in large databases was raised, since overlap between the searches conducted in this study, and the TREC-1 searches, was smaller than expected.