1. Information Retrieval in the Digital Age
IR Environment
Information Retrieval in the Digital Age

3. Gary Marchionini
Dean of the School of Library and Information Science at the University of North Carolina at Chapel Hill

4. Adds to Theories of Information Seeking
Previously –
Information Need
Information Searcher
Information Environment
Adds –
Interaction between all three components
Feedback loops

6. Creating a more Definitive Model
Of Information Seeking in Electronic Formats

7. Phases Recognize and accept an information problem
Define and understand the problem
Choose a search system
Formulate a query
Execute search
Examine results
Extract information
Reflect/iterate/stop
The arrows in the model illustrate how complex the search process is. We constantly move from one phase to another when we seek information.

8. Nodes of Information related by links
Hypertext
Nodes of Information related by links
Characteristics:
Allows large collections of information in a variety of media
Promotes an enabling rather than directive environment
Potential to alter student and teacher roles

9. Problems with Hypertext
Disorientation
Distraction
Technological Progress
Human psychology and Sociology

10. As our formal educational systems become more dependent on technology, we can be assured of confusion, false starts, grandiose expectations, gross underestimations, and hopefully some serious improvements.

11. Failure to meet this challenge will condemn future learners to the chaos and ineffectiveness of random walks through the universe of information that continues to expand around us.

12. Studied future design of hypertext documents and how to best enhance and organize systems for the use of the viewer.
How complex is too complex to be used easily?

13. Digital Libraries
Most of Marchionini’s studies have to do with Digital Libraries or online repositories.
How to connect the world.
How to make them the most efficient
Problems and recommendations.
Specifically addresses navigation

14. The Goal is to make the user interface an easy interactive experience.

15. Collected literature to point out problems with digital libraries.
Technical interoperability – hardware, networks, data types, protocols.
Informational interoperability – content scope, language, semantics, user interfaces.
Social interoperability – personal and organizational rights and responsibilities.

16. User Study Framework

17. Studied all areas of computer/human interaction.
Especially best design for representations (surrogates) that will lead to the best ability to navigate information.
What speed to play clips at, what interval of frames to pull out for a storyboard, etc.
Layouts that led to least frustration and ease of use.

18. Mobius Strip of Research and Practice
Questions lead to
Research that leads to
Results that lead to
Practice that leads to
Problems that lead to
Questions that lead to
Research
Etc.

19. Perseus
Digital
Library

20. Open Video Digital Library

21. The Cognitive Perspective of information Retrieval
Peter Ingwersen
The Cognitive Perspective of information Retrieval

22. Polyrepresentation
Cognitively and functionally different representations of information objects may be used in information retrieval to improve the quality of results.
Cognitively different – Derive from the interpretations of different actors
Functionally different – derived from the same actor; author generated text structures and images.

23. Polyrepresentation
The more representations of different cognitive and functional nature overlap, and the more intense the overlap, the higher the probability that such objects are relevant.
Polyrepresentation attempts to make simultaneous combination of evidences that are cognitively contextual to one another in a structure way.

24. Polyrepresentation

25. Polyrepresentation Continuum
Structured – sets of documents are retrieved for each representation, overlaps are formed and a pseudo ranking is developed.
Unstructured – implementations are based on best match principles leading to a rank of the retrieved documents per representation as input for polyrepresentation.

26. Polyrepresentation Continuum

27. Polyrepresentation Continuum
The Query continuum from structured to unstructured.
Structured queries provide conceptual and structural information about the search that are connected by explicit operators.
Unstructured queries provide no conceptual or structural information and have no explicit operators.

28. Polyrepresentation Continuum

29. Cognitive Perspective
The cognitive perspective of information retrieval takes the stance that there are two levels to the transfer of information.
The linguistic level is the words, symbols, images or text strings.
The cognitive level is the actual state of knowledge where the information stored in the linguistic level is perceived through the actor’s world model.

30. Cognitive Perspective

31. Cognitive Model
From the cognitive perspective, the cognitive model of information retrieval was developed. The interactions between actors, systems, information objects and the environment is explored in both a functional and cognitive manner.

32. Cognitive Model

33. Web Information Seeking
The Work of Amanda Spink

34. Foundations
Spink’s work is a sort of culmination of the works of Marchionini and Ingwersen, which of course built upon earlier works like Wilson, Ellis, Johnson & Meischke, and Bates.
Saracevic’s work correlates to Spink’s own work and the two often worked together during the early 2000s in web surfing research.

35. The Basis of Web Information Seeking
An understanding of user interactions with the web is required to develop effective web IR systems.
A person’s mental makeup alters the way they navigate the web.
The use of ‘push and pull’ technology such as recommended links and specially formulated search algorithms influences search patterns and motivations.

37. According to Spink, each user enters into IR with a built-in preference for either information seeking behavior or information searching behavior.
Despite being separate methods, they share basic behaviors, and most users will switch between the two methods one or more times during their entire IR process.
As noted by Marchionini and Ingwersen, a user’s perception of their skills and their own cognitive predispositions alters their choice of process.

38. Information Seeking Behavior
Influenced by behaviorally focused models such as Ellis and Johnson & Meischke, and their models’ flexible, non-linear nature. This is the reason for the focus on the browse-seek method of web interaction.

39. Information Searching Behavior
Influenced by Spink’s own work, Bates’ Berry-Picking Model, and the work of Marchionini and Ingwersen. Though these influences mix free-flow and linear models, their focus on query-based methods is what supports search-seek behavior.

40. System Feedback
This is the results of the search process. Once the user has received this, they have to begin value judgment of what they’ve received. If they don’t like what they’ve got, they can start again. Spink notes that this point is where most of the behavior switching occurs.
Assuming they are pleased with what they’ve been given, the user can proceed to actually retrieving their information.

41. Conclusions
Spink’s intent with this macro model is to attempt a solid representation of human interaction with the web by combining the mostly linear nature of Marchionini’s models with the multi-level processing of Ingwersen’s cognitive perspective.
Investigating the motivating information need, the cognitive makeup of the user, and search setting under an umbrella of user and web interactions is what allows web based IR to occur.

42. References
Geisler, G., & Marchionini, G. (2002) The open video digital library. D-Lib Magazine, 8(12).
Geiser, G., & Marchionini, G., & Wildemuth, B. (2006). The open video digital library: A möbius strip of research and practice. Journal of the American Society for Information Science and Technology, 57(12),
Knight, S.A., & Spink, A. (2008). Toward a web search information behavior model – 234 In Spink, A.,& Zimmer, M. (Eds.) (2008). Web Search, Multidisciplinary Perspectives. Springer Series in Information Science and Knowledge Management. 14, Berlin, Heidelberg: Springer-Verlag.
Marchionini, G. (1988). Hypermedia and learning: Freedom and chaos. Educational Technology, November 1988, 8-12.
Marchionini, G., & Shneiderman, B. (1988). Finding facts vs. browsing knowledge in hypertext systems. Computer. January 1988
Marchionini, G., & Maurer, H. (1995). The roles of digital libraries in teaching and learning. Communications of the ACM, 38(4), 67 – 75.

43. References
Ingwersen, P. (1996). Cognitive perspectives of information retrieval interaction: elements of a cognitive IR theory. Journal of Documentation, 52(1), 3-50
Larsen, B., Ingwersen, P., & Kekalainen, J. (2006). The Polyrepresentation continuum in IR. In Proceedings of IIiX
Knight, S.A. and Spink, A. (2008). Toward a web search information behavior model. A. Spink  and M. Zimmer (eds.), Web Search, Springer Series in Information Science and  Knowledge Management 14. Berlin, Germany: Springer.  
Spink, A. (Fall 2003). Web search: emerging patterns.  Library Trends, 52, 2. p.299(9).
Spink, A., Wolfram, D., Jansen, M B, & Saracevic, T. (Feb 1, 2001). Searching the Web: the  public and their queries.  Journal of the American Society for Information Science and  Technology, 52, 3. p.226(9).
Chun, W.C., Detlor, B., & Turnbull, D. (2000). Information seeking on the web: an  integrated model of browsing and searching. First Monday, 5(2).