1. User Interfaces for Information Access Prof. Marti Hearst SIMS 202, Lecture 26

2. Marti A. Hearst SIMS 202, Fall 1997 User Interfaces for Information Access n User Interfaces is a large topic n Focus on only two aspects here n How to impart information about the relationship between n the query, n the document collection, and n the retrieval results n How to support the iterative process

3. Marti A. Hearst SIMS 202, Fall 1997 Today v Imparting Information about query, collection, and retrieval results v Supporting the Process of search v Videos!

4. Marti A. Hearst SIMS 202, Fall 1997 UIs for Information Access n Why Text is Tough n Collections are very large n Information is high-dimensional n Text is difficult to summarize n summarization produces more text n visualization doesn’t show the essence

5. Marti A. Hearst SIMS 202, Fall 1997 Assuming: User in the loop Full text documents Goal: reduce cognitive load on user n simple query n informative retrieval resultsQuestion: What is the relationship between the n query n retrieved documents? User Interface Goals

6. Marti A. Hearst SIMS 202, Fall 1997 To impart information (about the collection and retrieval results) n Interfaces should n give hints about the roles terms play in the collection n give hints about what will happen if various terms are combined n show explicitly why documents are retrieved in response to the query n summarize compactly the subset of interest

7. Marti A. Hearst SIMS 202, Fall 1997 Retrieval Result Display: Current Approaches n Ranked list of titles n Number of hits of each term n Inter-document similarity

8. Marti A. Hearst SIMS 202, Fall 1997

9. Marti A. Hearst SIMS 202, Fall 1997 Main Topics and Subtopics Observation: n Long texts often consist of main topics and a sequence of subtopical discussions n Standard IR does not take this into account

10. Marti A. Hearst SIMS 202, Fall 1997 Variations on Topic and Subtopic Distribution B A A B B A

11. Marti A. Hearst SIMS 202, Fall 1997 A Scenario v Query: funding for cold fusion research v A relevant article exists, in which: n the main topic is cold fusion n there is a subtopic funding discussion n but “cold fusion” is not adjacent to it v A standard system either: n retrieves all docs with both term sets n discards this doc -- no term overlap

12. Marti A. Hearst SIMS 202, Fall 1997 TextTiling Partition expository texts into multi- paragraph discourse units that reflect the texts’ subtopic structure 1-2 Intro: Magellan Space Probe 3-4 Intro: Venus 5-7 Missing Craters on Venus 8-11 Volcanic Action 12-15 River Styx 16-18 Crustal spreading 19-21 Recent volcanism 22-23 Future of Magellan

13. Marti A. Hearst SIMS 202, Fall 1997 Display of Retrieval Results Goal: minimize time/effort for deciding which documents to examine in detail Idea: show the roles of the query terms in the retrieved documents, making use of document structure

14. Marti A. Hearst SIMS 202, Fall 1997 TileBars v Graphical Representation of Term Distribution and Overlap v Simultaneously Indicate: n relative document length n query term frequencies n query term distributions n query term overlap

15. Marti A. Hearst SIMS 202, Fall 1997 Query terms: What roles do they play in retrieved documents? DBMS (Database Systems) Reliability Mainly about both DBMS & reliability Mainly about DBMS, discusses reliability Mainly about, say, banking, with a subtopic discussion on DBMS/Reliability Mainly about high-tech layoffs Example

16. Marti A. Hearst SIMS 202, Fall 1997

17. Marti A. Hearst SIMS 202, Fall 1997

18. Marti A. Hearst SIMS 202, Fall 1997 Exploiting Visual Properties n Variation in gray scale saturation imposes a universal, perceptual order (Bertin et al. ‘83) n Varying shades of gray show varying quantities better than color (Tufte ‘83) n Differences in shading should align with the values being presented (Kosslyn et al. ‘83)

19. Marti A. Hearst SIMS 202, Fall 1997 Key Aspect: Query formation n Conjunct of disjuncts n Each disjunct is a concept n osteoporosis, bone loss n prevention, cure n research, Mayo clinic, study n User does not have to specify which are main topics, which are subtopics n Ranking algorithm gives higher weight to overlap of topics

20. Marti A. Hearst SIMS 202, Fall 1997 Main Topic Context n Potential Problem with TileBars Given retrieved documents in which no query terms are well-distributed, The user does not know the context in which the query terms are used n Solution: Accompany with main topic display

21. Marti A. Hearst SIMS 202, Fall 1997 TileBars Summary n Compact, graphical representation of term distribution for full text retrieval results n simultaneously display term frequency, distribution, overlap, and doc length n allow for simple user-determined ordering strategies n Part of a larger effort: user-centric, content-sensitive information access

22. Marti A. Hearst SIMS 202, Fall 1997 TileBars v Preliminary User Studies v users understand them v find them helpful in some situations v sometimes terms need to be disambiguated v Future: v Integrate with Main Topic Context Indicators v Modify for Web information

23. Marti A. Hearst SIMS 202, Fall 1997 Other Approaches v Show how often each query term occurs in retrieved documents n VIBE (Korfhage ‘91) n InfoCrystal (Spoerri ‘94) n Problems: n can’t see overlap of terms within docs n quantities not represented graphically n more than 4 terms hard to handle n no help in selecting terms to begin with

24. Marti A. Hearst SIMS 202, Fall 1997 InfoCrystal (Spoerri 94)

25. Marti A. Hearst SIMS 202, Fall 1997 Support the Process n Two recent similar approaches that focus on supporting the process n SketchTrieve (Hendry & Harper, in reader) n DLITE (Cousins, on videotape)

26. Marti A. Hearst SIMS 202, Fall 1997 Informal Interface n Informal does not mean less useful n Show how the search is n unfolding or evolving n expanding or contracting n Prompt the user to n reformulate and abandon plans n backtrack to points of task deferral n make side-by-side comparisons n define and discuss problems

27. Marti A. Hearst SIMS 202, Fall 1997 SketchTrieve: An Informal Interface (Hendry & Harper 96, 97) n A “spreadsheet” for information access n Make use of layout, space, and locality n comprehension and explanation n search planning n A data-flow notation for information seeking n link sources to queries n link both to retrieved documents n align results in space for comparison

28. Marti A. Hearst SIMS 202, Fall 1997 Connecting Results with Next Query

29. Marti A. Hearst SIMS 202, Fall 1997 Improving User Interfaces n The surface has only been scratched n This is where the big improvements will happen (in my opinion).