Anomalous States of Knowledge as a Basis for Information Retrieval

The Author

Nicholas J. Belkin is currently a Professor of Information Science, and Director of the Ph.D. Program at the School of Communication, Information and Library Studies at Rutgers University.  He has many awards and honors under his belt, including but not limited to the SCILS Excellence in Research Award (2001) and the Lucille Kelling Henderson Memorial Lecturer which he received here at the School of Information and Library Science, University of North Carolina at Chapel Hill in 1997.  For more detailed information, including his current research and publications please visit:

The Article

Belkin proposes that a search begins with a problem and a need to solve it - the gap between these is defined as the information need. The user gradually builds a bridge of levels of information, that may change the question or the desired solution as the process continues (Belkin, N.Oddy, and Brooks 1982).
In other words, this view of information seeking is as a dynamic process with varying levels of expertise growing in regard to knowledge about the solution and in using capabilities of the particular information system itself. Taking these ideas, Belkin advocates a systems design using a network of associations between items as a means of filling the knowledge gap. By establishing relationships between individual pieces of knowledge, a bridge of supporting information can be used to cross the knowledge gap. Using a collection of associations in this manner provides a framework that can be applied to designing Collaborative Filtering mechanisms, which work from building associations between users.

Anomalous:  unknown
State: condition
Knowledge: understanding

- Information needs are not always easy to identify
- There are categories of ASK
- These categories of ASK are what IR systems should be based on
- The problem questions or information needs of individuals may be defined and a compatible format found in the ASK design system

7 Steps of the ASK Model:

1. Userís UNSTRUCTURED Problem Statement (ASK)
2. ASK is converted to STRUCTURED category
3. Retrieval system selected
4. Information is presented to the user
5. User reviews information and then decidesÖ
    a. Systemís method of choice was
        i.   suitable;  not suitable
    b. Did the information relate to the problem?
        i. Yes;  no
    c. Have the information requirements changed?
        i. Yes; no
7. Based on responses
    a. Finish or Return to step 3
        i. System changes retrieval mechanism
    b. Finish or Return to step 2
        i. System modifies problem structure
    c. Finish or Return to step 1

Limitations of ASK:

- Representing knowledge that is not known is difficult
- A userís ASK changes with new information and knowledge
- One text will probably not be sufficient to satisfy a userís ASK


- A userís knowledge is the most important part of an ASK system
- An implication of ASK is that the Ďbest matchí system is not suitable for an IR system
- IR should be designed for ASK instead of for the documents
- Different strategies need to be used for different ASKs