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User Interfaces and Visualization: Supporting the Search Process with Informative Feedback and Hierarchical Navigation

This chapter discusses the importance of human-computer interaction in information retrieval systems. It covers topics such as interface design principles, informative feedback, and the use of visualization techniques for data exploration. The chapter also explores different approaches to query specification and the role of hierarchical navigation in supporting the search process.

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User Interfaces and Visualization: Supporting the Search Process with Informative Feedback and Hierarchical Navigation

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  1. Special Topics in Computer ScienceThe Art of Information RetrievalChapter 10: User Interfaces and Visualization Alexander Gelbukh www.Gelbukh.com

  2. Previous chapter: Conclusions • Inverted files seem to be the best option • Other structures are good for specific cases • Genetic databases • Sequential searching is an integral part of manyindexing-based search techniques • Many methods to improve sequential searching • Compression can be integrated with search

  3. Previous chapter: Research topics • Perhaps, new details in integration of compression and search • “Linguistic” indexing: allowing linguistic variations • Search in plural or only singular • Search with or without synonyms

  4. Topic “Interfaces”: Overview • Human-computer interaction • Search process • Support for its parts: • What to start from • Query specification • Showing the results • Relevance feedback • Support for the whole process • Many specific examples of systems • Long. I’ll omit details

  5. Human-computer interaction... • Most important part of the problem • Bad interface kills all the fancy technical features of asystem. If you cannot use it, you don’t care how good it is • Chopsticks • A good interface “disappears” -- like air • Design principles • Informative feedback (e.g., relationships) • Internal locus of control (= this feedback is customizable) • Reduce working memory load (e.g., keep track) • Permits to return to a temporally abandoned strategy • Distinct interfaces for novices / experts (simplicity vs power) • Example: Google / Advanced search

  6. ...Human-computer interaction... Bad interfaces -- Why? I think: • Different weight of tasks foruser and programmer • Programmer: a list of (equal)tasks (functions) • User: Goals. Some tasks arefrequent and some not • Example: Windows XP: • Copy, Print, Delete, publish in Web ...

  7. ...Human-computer interaction...Information visualization • Humans are better at images than words • Abstract info: more difficult. Interactive mode helps • Types • Brushing and linking: different views of the same info;changing one changes others • Panning and zooming: Example: clustering. • Focus and context: fisheye camera • Magic lenses: temporally change a part of info under lens • Combination: overview plus details • Hierarchically

  8. ...Human-computer interactionEvaluation • What is evaluated: • the quality of final result (mostly precision, not recall) • time to learn the system • time to achieve goals • error rates • retention of the use of interface over time • People are very different: what’s good for someis not for others • Difficult to measure and evaluate

  9. Information access process • Goals. Tool. Tasks • Basic interaction model: query  result  (repeat) • Advanced models take into account: • integration with browsing • near-miss is acceptable: use hyperlinks • Selection of source collection • Learning while searching. Goal shift while searching • Getting the info by pieces, not as a set of relevant docs • Temporal lateral goals, then return to the main goal • Interface needs to support this

  10. Not only search • Search is a part of an activity on ... • Other tasks of this activity include • finding trends, making comparisons • aggregating information, assessing, interpreting, ... • Search is intermitted with them, not a separate subtask • Need for a common interface that supports the wholeprocess. One tool.

  11. Topic “Interfaces”: Overview • Human-computer interaction • Search process • Support for its parts: • What to start from • Query specification • Showing the results • Relevance feedback • Support for the whole process

  12. Starting points • Choosing information source (collection) • How to choose? • Lists. Hard to guess • Overviews: Panning and zooming • Category hierarchies. Example: Yahoo! • Large hierarchies  need for good interfaces to navigate them • Clustering • Similarity measures: text, co-citations, co-links (Google), ... • Clustering on the fly. Summaries of the clusters. Zooming in. • Clustering of search results (combination of search & navigation) • Graphical views like stars or landscapes. Not clear if useful

  13. ...Starting points • Examples • Start from some object and correct its desired properties • Problem: how to find from which one to start? • Dialogues • Model a human librarian. Too complicated • Wizards • Only useful for simple tasks, not IR • Guided tours • Automated source selection • Search in descriptions of collections. Or: meta-search

  14. Query specification • Types • command language?? (problem!), • form fillin, menu selection, direct manipulation, • natural language • Problem: people have difficulties using Booleanexpressions (e.g., confuse AND and OR) • A lot of efforts to help the users to (visually)construct what is internally a Boolean query • (cf. Bengt’s talk) • Query preview helps

  15. Presentation of results: context Documents by keywords • Result list: document surrogates (detailed/not) • KWIC – key words in context (kind of abstract for query) • Now used for Web (e.g., Google) • Full text • Highlight hits in full text • Tilebars: representation of keyword distribution at a glance Keywords by documents • Helps understanding which keywords are important

  16. ... Presentation of results: context • Organizing the query results • Table of Contents • automatically generated trough hyperlinks • Hyperlink structure • Tables (but: only two attributes) • too little • improvement: TableLens

  17. Using relevance judgments • Relevance feedback: control in terms of the task, notof the machinery that performs it (keyword weights) • Degree of control (over the keywords to include) • Control only (users set the keywords) – worst, • opaque (reaction only), transparent (users see new words) • penetrable: users have control over new words – best.

  18. Interface for the whole program • Example of problem: search window; old resultsversus newly typed query (not executed) • Windows layout: monolithic (simple/little), tiled,overlapping (large/crowded). • Workspaces. Persistent. • Use the possibilities of windows • bad example: Lexis-Nexis • Provide history information.  User preferences

  19. Research topics • Many ideas throughout the chapter • some may be obsolete • New interface types! 3D interfaces • Ways of assessing the quality of interfaces

  20. Conclusions • Interface is a key element of the system. If the userscannot use it, it does not matter how good it is. • Interface design choices are important at any stageof the process • Especially to formulate queries • Also to present results • 3D interfaces to present results • Also, overall system interface and action tracking • Difficult to assess quality. Difficult to find new ideas • Very promising if you find them!

  21. Thank you! Till December 4 compensation lecture: December 11, combined with normal (last) lecture

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