Lecture 22: Interfaces for Information Retrieval I

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Lecture 22 Interfaces for Information Retrieval I
SIMS 202 Information Organization and Retrieval

• Prof. Ray Larson Prof. Marc Davis
• UC Berkeley SIMS
• Tuesday and Thursday 1030 am - 1200 pm
• Fall 2002
• http//www.sims.berkeley.edu/academics/courses/is2
  02/f03/

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Lecture Overview

• Review of Last Time
• Web Search Engines and Algorithms
• Interfaces for Information Retrieval
• Introduction to HCI
• Why Interfaces Dont Work
• Early Visions Memex
• Discussion Questions
• Action Items for Next Time

Credit for some of the slides in this lecture
goes to Marti Hearst
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Lecture Overview

• Review of Last Time
• Web Search Engines and Algorithms
• Interfaces for Information Retrieval
• Introduction to HCI
• Why Interfaces Dont Work
• Early Visions Memex
• Discussion Questions
• Action Items for Next Time

Credit for some of the slides in this lecture
goes to Marti Hearst
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Directories vs. Search Engines

• Directories
• Hand-selected sites
• Search over the contents of the descriptions of
  the pages
• Organized in advance into categories

• Search Engines
• All pages in all sites
• Search over the contents of the pages themselves
• Organized after the query by relevance rankings
  or other scores

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Challenges for Web Searching Data

• Distributed data
• Volatile data/Freshness 40 of the web changes
  every month
• Exponential growth
• Unstructured and redundant data 30 of web pages
  are near duplicates
• Unedited data
• Multiple formats
• Commercial biases
• Hidden data

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Challenges for Web Searching Users

• Users unfamiliar with search engine interfaces
  (e.g., Does the query apples oranges mean the
  same thing on all of the search engines?)
• Users unfamiliar with the logical view of the
  data (e.g., Is a search for Oranges the same
  things as a search for oranges?)
• Many different kinds of users

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Web Search Queries

• Web search queries are SHORT
• 2.4 words on average (Aug 2000)
• Has increased, was 1.7 (1997)
• User expectations
• Many say the first item shown should be what I
  want to see!
• This works if the user has the most
  popular/common notion in mind

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Search Engines

• Crawling
• Indexing
• Querying

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Standard Web Search Engine Architecture
Check for duplicates, store the documents
DocIds
crawl the web
user query
create an inverted index
Inverted index
Search engine servers
Show results To user
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Google

• Google maintains (currently) the worlds largest
  Linux cluster (over 15,000 servers)
• These are partitioned between index servers and
  page servers
• Index servers resolve the queries (massively
  parallel processing)
• Page servers deliver the results of the queries
• Over 3 Billion web pages are indexed and served
  by Google

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Starting Points What is Really Being Used?

• Todays search engines combine these methods in
  various ways
• Integration of directories
• Today most web search engines integrate
  categories into the results listings
• Lycos, MSN, Google
• Link analysis
• Google uses it others are also using it
• Words on the links seems to be especially useful
• Page popularity
• Many use DirectHits popularity rankings

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Ranking Link Analysis

• Assumptions
• If the pages pointing to this page are good, then
  this is also a good page
• The words on the links pointing to this page are
  useful indicators of what this page is about
• References Page et al. 98, Kleinberg 98

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Ranking Link Analysis

• Why does this work?
• The official Toyota site will be linked to by
  lots of other official (or high-quality) sites
• The best Toyota fan-club site probably also has
  many links pointing to it
• Less high-quality sites do not have as many
  high-quality sites linking to them

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Lecture Overview

• Review of Last Time
• Web Search Engines and Algorithms
• Interfaces for Information Retrieval
• Introduction to HCI
• Why Interfaces Dont Work
• Early Visions Memex
• Discussion Questions
• Action Items for Next Time

Credit for some of the slides in this lecture
goes to Marti Hearst
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Drawing the Circles
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Drawing the Circles
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Drawing the Circles
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Drawing the Circles
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Drawing the Circles
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Drawing the Circles
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Drawing the Circles
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Drawing the Circles
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Drawing the Circles
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Human-Computer Interaction (HCI)

• Human
• The end-users of a program
• The others in the organization
• The designers of the program
• Computer
• The machines the programs run on
• Interaction
• The users tell the computers what they want
• The computers communicate results
• The computer may also tell users what the
  computer wants them to do

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What is HCI?
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Shneiderman on HCI

• Well-designed interactive computer systems
• Promote
• Positive feelings of success
• Competence
• Mastery
• Allow users to concentrate on their work,
  exploration, or pleasure, rather than on the
  system or the interface

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Design Guidelines

• Set of design rules to follow
• Apply at multiple levels of design
• Are neither complete nor orthogonal
• Have psychological underpinnings (ideally)

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Shneidermans Design Principles

• Provide informative feedback
• Permit easy reversal of actions
• Support an internal locus of control
• Reduce working memory load
• Provide alternative interfaces for expert and
  novice users

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HCI for IR

• Information seeking is an imprecise process
• UI should aid users in understanding and
  expressing their information needs
• Help formulate queries
• Select among available information sources
• Understand search results
• Keep track of the progress of their search

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Provide Informative Feedback

• About
• The relationship between query specification and
  documents retrieved
• Relationships among retrieved documents
• Relationships between retrieved documents and
  metadata describing collections

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Reduce Working Memory Load

• Provide mechanisms for keeping track of choices
  made during the search process
• Allow users to
• Return to temporarily abandoned strategies
• Jump from one strategy to the next
• Retain information and context across search
  sessions
• Provide browsable information that is relevant to
  the current stage of the search process
• Related terms or metadata
• Search starting points (e.g., lists of sources,
  topic lists)

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Interfaces For Expert And Novice Users

• Simplicity vs. power tradeoffs
• Scaffolded user interface
• How much information to show the user?
• Number and complexity of user operations
• Variants of operations
• Inner workings of system itself
• System history
• Example
• Television remote control

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User Differences

• Abilities, preferences, predilections
• Spatial ability
• Memory
• Reasoning abilities
• Verbal aptitudes
• Personality differences
• Age, gender, ethnicity, class, sexuality,
  culture, education
• Modalilty preferences/restrictions
• Vision, audition, speech, gesture, haptics,
  locomotion

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Nielsens Usability Slogans

• Your best guess is not good enough
• The user is always right
• The user is not always right
• Users are not designers
• Designers are not users
• Less is more
• Details matter

(from Nielsens Usability Engineering)
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Who Builds UIs?

• A team of specialists (ideally)
• Graphic designers
• Interaction / interface designers
• Technical writers
• Marketers
• Test engineers
• Software engineers
• Enthnographers
• Cognitive psychologists

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How to Design and Build UIs

• Task analysis
• Rapid prototyping
• Evaluation
• Implementation

Iterate at every stage!
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Task Analysis

• Observe existing work practices
• Create examples and scenarios of actual use
• Try out new ideas before building software

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Rapid Prototyping

• Build a mock-up of design
• Low fidelity techniques
• Paper sketches
• Cut, copy, paste
• Video segments
• Interactive prototyping tools
• Visual Basic, HyperCard, Director, etc.
• UI builders
• NeXT, etc.

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Evaluation Techniques

• Qualitative vs. quantitative methods
• Qualitative (non-numeric, discursive,
  ethnographic)
• Focus groups
• Interviews
• Surveys
• User observation
• Participatory design sessions
• Quantitative (numeric, statistical, empirical)
• User testing
• System testing

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Qualitative Questions

• User experience
• User preferences
• User recommendations
• Design dialogue

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Quantitative Questions

• Precision
• Recall
• Time required to learn the system
• Time required to achieve goals on benchmark tasks
• Error rates
• Retention of the use of the interface over time

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Lecture Overview

• Review of Last Time
• Web Search Engines and Algorithms
• Interfaces for Information Retrieval
• Introduction to HCI
• Why Interfaces Dont Work
• Early Visions Memex
• Discussion Questions
• Action Items for Next Time

Credit for some of the slides in this lecture
goes to Marti Hearst
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Why Interfaces Dont Work

• Because
• We still think of using the interface
• We still talk of designing the interface
• We still talk of improving the interface
• We need to aid the task, not the interface to
  the task.
• The computer of the future should be invisible.

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Norman on Design Priorities

1. The userwhat does the person really need to have
   accomplished?
2. The taskanalyze the task. How best can the job
   be done?, taking into account the whole setting
   in which it is embedded, including the other
   tasks to be accomplished, the social setting, the
   people, and the organization.
3. As much as possible, make the task dominate make
   the tools invisible.
4. Then, get the interaction right, making things
   the right things visible, exploiting affordances
   and constraints, providing the proper mental
   models, and so onthe rules of good design for
   the user, written about many, many times in many,
   many places.

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Lecture Overview

• Review of Last Time
• Web Search Engines and Algorithms
• Interfaces for Information Retrieval
• Introduction to HCI
• Why Interfaces Dont Work
• Early Visions Memex
• Discussion Questions
• Action Items for Next Time

Credit for some of the slides in this lecture
goes to Marti Hearst
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What Dr. Bush Foresees

• Cyclops Camera
• Worn on forehead, it would photograph anything
  you see and want to record. Film would be
  developed at once by dry photography.
• Microfilm
• It could reduce Encyclopaedia Britannica to
  volume of a matchbox. Material cost 5. Thus a
  whole library could be kept in a desk.
• Vocoder
• A machine which could type when talked to. But
  you might have to talk a special phonetic
  language to this mechanical supersecretary.
• Thinking machine
• A development of the mathematical calculator.
  Give it premises and it would pass out
  conclusions, all in accordance with logic.
• Memex
• An aid to memory. Like the brain, Memex would
  file material by association. Press a key and it
  would run through a trail of facts.

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Memex
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Memex Detail
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Cyclops Camera
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Vocoder Supersecretary
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Investigator at Work

• One can now picture a future investigator in his
  laboratory. His hands are free, and he is not
  anchored. As he moves about and observes, he
  photographs and comments. Time is automatically
  recorded to tie the two records together. If he
  goes into the field, he may be connected by radio
  to his recorder. As he ponders over his notes in
  the evening, he again talks his comments into the
  record. His typed record, as well as his
  photographs, may be both in miniature, so that he
  projects them for examination.

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Memex

• A memex is a device in which an individual
  stores all his books, records, and
  communications, and which is mechanized so that
  it may be consulted with exceeding speed and
  flexibility. It is an enlarged intimate
  supplement to his memory.

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Associative Indexing

• associative indexing, the basic idea of
  which is a provision whereby any item may be
  caused at will to select immediately and
  automatically another. This is the essential
  feature of memex. The process of tying two items
  together is the important thing.

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The WWW circa 1945

• It is exactly as though the physical items had
  been gathered together from widely separated
  sources and bound together to form a new book.
  But it is more than this for any item can be
  joined into numerous trails, the trails can
  bifurcate, and they can give birth to side
  trails.
• Wholly new forms of encyclopaedias will appear,
  ready-made with a mesh of associative trails
  running them, ready to be dropped into the memex
  and there amplified.

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Selection

• The heart of the problem, and of the personal
  machine we have here considered, is the task of
  selection. And here, in spite of great progress,
  we are still lame.
• Selection, in the broad sense, is still a stone
  adze in the hands of a cabinetmaker.
• Memex Revisited (Bush 1965)

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Interaction Paradigms for IR

• Direct manipulation
• Query specification
• Query refinement
• Result selection
• Delegation
• Agents
• Recommender systems
• Filtering

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The Adaptive Memex

• In an adaptive Memex, the owner has delegated to
  the machine the ability to propose or effect
  changes in the stored information. By analogy to
  business practice, the Memex is said to be
  functioning as an agent (Kay, 1984). The machine
  is playing an autonomous role within a restricted
  charter to attempt a more effective organization
  of the information based on observations of
  actual use and topical similarities.

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Lecture Overview

• Review of Last Time
• Web Search Engines and Algorithms
• Interfaces for Information Retrieval
• Introduction to HCI
• Why Interfaces Dont Work
• Early Visions Memex
• Discussion Questions
• Action Items for Next Time

Credit for some of the slides in this lecture
goes to Marti Hearst
59
Discussion Questions

• Alison Billings on MIR 10.1 10.3
• In section 10 of Modern Information Retrieval
  Marti A. Hearst touches on the difficulty
  untrained users face in doing Boolean searches
  (i.e. the misinterpretation of OR and AND, nets
  being cast too wide or too narrow) so I thought
  it best to rely on both our experience and the
  reading to address the following questions In
  doing the Boolean searches for assignment 8, did
  you use the KWIC search function to help you sort
  through the documents you retrieved? Did it help
  you find the information you needed? Did you
  have to reformat your Boolean queries several
  times in order for them to return the results you
  expected? Is it reasonable to expect users to
  continue use Boolean searches when there are more
  effective search methods available?

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Discussion Questions

• danah boyd on Why Interfaces Dont Work
• While Norman frames his argument through users,
  tasks, invisible tools, and make the right things
  visible, his examples are quite flawed.
• He spent the majority of the paper talking about
  the problems with set-up. Yesterday, i purchased
  a brand new 12" Mac to replace my battered one.
  Turned it on it worked and connected to my
  wireless. Put a cable between it and my old one
  and sucked off all of the data, including the
  programs. I installed 2 new programs. Inserted
  them into the CD drive and dragged them from the
  disk to my Applications folder. They worked.
  Brand new machine and it was immediately
  functional and identical to my old one in less
  than 2 hours (copy time). Even the proprietary
  stuff like my Audible.com files just asked me if
  i wanted to assign them to this new machine.
• I opened up a Sidekick yesterday. Turned it on.
  It connected to T-Mobile, told me what my email
  address was, told me to sign on to AIM and voila
  it worked.
• Is set-up really the problem?

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Discussion Questions

• danah boyd on Why Interfaces Dont Work
• Norman argues to put the user first. What user?
  Can you really design a mass-produced item that
  takes into consideration all users who use it?
• Take the keyboard. What size is chosen? I have
  small fingers and yet it's hard to find small
  keyboards.
• What are the consequences of designing for an
  "average" user?

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Discussion Questions

• danah boyd on Why Interfaces Dont Work
• Norman argues for a comparison to RL tasks,
  making the task the priority.
• Users have vastly different sets of tasks that
  they want, but the majority of computer consumers
  use their computer to 1) communicate (email, IM,
  chatrooms, voice over IP) 2) find information on
  the Web (surf).
• Neither of these tasks has a comparable off-line
  equivalent. How can you do a task-first analysis
  without an interface when you don't have an
  offline model to work with? What are the
  problems with modeling this behavior off of
  physical metaphors?
• For example, we've conceptualized email to be a
  metaphor to mail. This has created more problems
  than trying to design for an entirely new
  behavior.

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Discussion Questions

• Jeff Towle on As We May Think
• Vannevar Bush throws out quite a few ideas in
  this piece. A large portion of his piece is an
  analysis of instances where and idea was not
  feasible at the time, but was later built into
  something successful. Is this the case with
  Bush's ideas? They were clearly not feasible
  when he wrote this, but are they now?
• Many of Bush's proposals sound very familiar.
  His description of 'dry photography' seems to
  closely match digital photography technology.
  His description of information trails is quite
  similar to hypertext. But are we still missing
  some of Bush's great ideas?

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Discussion Questions

• Denise Green on Memex II
• Vannevar Bush suggests that Memex "...merely
  supplements a human memory, does so precisely
  and comprehensively, and aids the process of
  recollection." At the heart of Memex are
  information trails, which Bush believes are
  similar in nature to trails of association in our
  brains. How does this model compare with current
  ideas about how the brain works?
• How are Memex trails related to today's
  hypertext, as used commonly on the Internet? How
  are they dissimilar?

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Discussion Questions

• Ryan Shaw on Memex Revisited
• Bush emphasizes compression and rapid access as
  the two most important developments for
  data-handling technology. In retrospect, he seems
  to have given networking short shrift. Given
  Bush's uncanny vision, why did he overlook the
  importance of the network?
• While the Memex is a marvelous idea, Bush's
  article on the topic betray certain biases in his
  views on who uses information and why. How might
  these biases have affected his beliefs about 1)
  the feasibility of actually building a Memex-like
  system and 2) the effects of such a system, were
  it to be built?

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Lecture Overview

• Review of Last Time
• Web Search Engines and Algorithms
• Interfaces for Information Retrieval
• Introduction to HCI
• Why Interfaces Dont Work
• Early Visions Memex
• Discussion Questions
• Action Items for Next Time

Credit for some of the slides in this lecture
goes to Marti Hearst
67
Next Time HCI For IR

• Browsing
• Visualizing collections and documents
• Navigating collections and documents
• Searching
• Formulating queries
• Visualizing results
• Navigating results
• Refining queries
• Selecting results

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Next Time HCI for IR

• Interfaces for Information Retrieval
• Readings
• MIR 10.4 10.10