Interface Issues and Interaction Strategies for Information Retrieval Systems

Scott Henninger
Department of Computer Science and Engineering
University of Nebraska
115 Ferguson Hall, Box 880115
Lincoln, NE 68588-0115 USA
+1 402 472 8394
scotth@cse.unl.edu

Nicholas J. Belkin
The School of Communication, Information, and Library Studies
Rutgers University
4 Huntington Street
New Brunswick, NJ 08901-1071 USA
+1 908 932 8585
nick@belkin.rutgers.edu

ABSTRACT

The need for effective information retrieval systems becomes increasingly important as computer-based information repositories grow larger and more diverse. In this tutorial, we present the key issues involved in the use and design of effective interfaces to information retrieval systems. The process of satisfying information needs is analyzed as a problem solving activity in which users learn and refine their needs as they interact with a repository. Current systems are analyzed in terms of key interface and interaction techniques such as querying, browsing, and relevance feedback. We discuss the impact of information seeking strategies on the search process and what is needed to more effectively support the search process. Retrieval system evaluation techniques is discussed in terms of its implications for users. We close by outlining some user-centered design strategies for retrieval systems.

KEYWORDS

information retrieval, user interfaces, databases, information systems, interaction strategies.

INFORMATION RETRIEVAL AS A PROBLEM SOLVING PROCESS

The field of information retrieval can be divided along the lines of its system-based and user-based concerns. While the system-based view is concerned with efficient search techniques to match query and document representations, the user-based view must account for the cognitive state of the searcher and the problem solving context. People are drawn to an information retrieval system because they perceive that they lack some knowledge to solve a problem or perform a task. This creates an "anomalous state of knowledge"[1] or "situation of irresolution" [6] in which information seekers must find something they know little or nothing about.

Information retrieval systems must not only provide efficient retrieval, but must also support the user in describing a problem that s/he does not understand well. The process is not only one of providing a good query language, but also one of supporting an iterative dialogue model. As users query and browse the repository, they learn more about the problem and potential solutions and therefore refine their conceptualization of the problem. The information being sought differs from that being sought at the beginning of the session. The user is engaged in a problem solving session in which the problem to be solved, that of finding relevant information, evolves and is refined through the process of seeing the results of intermediate queries.

THE VOCABULARY PROBLEM

Even in cases where the information is well-known, a vocabulary problem still exists. Users may know what they are looking for, but lack the knowledge needed to articulate the problem in terms and abstractions used by the retrieval system. An inherent problem is that people use a surprisingly diverse set of terms to refer to the same object, such that the probability for choosing the same term for a familiar object is less than 15 percent [3]. This problem is exacerbated by the fact that information repositories are often indexed by experts and by the inherent properties of the objects. Expert indexing causes problems because less knowledgeable users, who define the majority of people experiencing anomalous states of knowledge, are less likely to understand the terminology used by experts. Indexing by inherent properties causes problems because most information seeking is engaged in some problem solving context. People are looking for information that is used for something and are therefor more concerned with how an object is used, not its inherent properties [4].

INTERFACES FOR RETRIEVAL SYSTEMS

Current information retrieval systems have addressed these inherent properties of information seeking and indexing in a variety of ways. Browsing has been employed to facilitate the iterative and ill-defined nature of information seeking, but can lead to a loss of direction and overly narrow searches. Queries provide a means to direct the search, but often rely on the user understanding a complex query language and proper vocabulary to be effective. An integration of these strategies is a promising approach that can solve some of these problems [5]. Information visualization techniques such as the Perspective Wall at Xerox PARC [2] can be used in interface design to improve both browsing and querying.

Good information retrieval system design combines a combination of support for information seeking strategies, such as browsing and direct querying, in an interface that provides effective cues to the location, use, and characteristics of the retrieved information. Feedback techniques are also crucial to support the iterative refinement of information needs.

EVALUATION TECHNIQUES

Traditional retrieval system evaluation relies on the measures of recall (the proportion of relevant items in the entire repository which have been retrieved) and precision (the proportion of retrieved items which are relevant) for assessment of system effectiveness. There are significant problems with these measures of effectiveness, and the criterion on which they are based, relevance. These include such issues as:

who makes the relevance judgments, and how are these judgments related to the user's context and the use of the items;
lack of knowledge of the total number of relevant items in the repository for any given information problem;
how to evaluate these measures over the course of an interaction; and,
the validity of the measures themselves as indicators of the effectiveness of the information interaction.

This suggests the need for new measures of retrieval effectiveness in interactive retrieval systems.

Furthermore, new evaluation techniques are needed that account not only for the accuracy of a retrieval system, but also its interactive abilities and ease of use. A system that measures poorly in recall and precision, but provides good browsing and iterative querying facilities may be more successful overall in responding to a person's information problem than a system which is "more effective" in terms of recall and precision

DESIGN STRATEGIES

Guidelines for the design of information retrieval systems must address not only issues of look-and-feel, but also of effective interaction. Dialog models based on relevance feedback and query reformulation explicitly address the ill-defined nature of information seeking by allowing users to learn from the repository and iteratively refine the information need. Systems need to support a number of interaction styles, such as querying and browsing, to accommodate the different kinds of search strategies users may need to use.

Design strategies for retrieval systems need to pay particular attention to the interaction between users and the texts they retrieve. People's information seeking behavior needs to be analyzed in the problem solving context in which their information needs arise. For example, what are some of the common associations people make? What information is closely related? What different perspectives can a piece of information be viewed from? The answers to these questions often differ, depending critically on the nature of the task and the individuals performing the task. Task analysis, user modeling and interaction modeling are some of the strategies that can be used to improve the design of retrieval systems.

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