INSYS 300 -- Week 8 Effective Information Retrieval

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INSYS 300 -- Week 8Effective Information
Retrieval

• Dr. Xia Lin
• Assistant Professor
• College of Information Science and Technology
• Drexel University

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Effective Information Retrieval

• Iteration
• Relevance Feedback
• Use User's Profiles
• Graphical Display of Search Results
• Browsing/Interactive Searching

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Iteration

• Most search needs to be done iteratively
• From the users point of view
• The first query often does not retrieve what the
  user wants
• The user needs to see the output of previous
  queries to construct the next query
• The user often needs to reconstruct his/her
  information needs after they read/browse search
  results.

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Iteration Users strategies

• Modify queries repeatedly based on some goals
• Starting with high precision
• Use a specific query first
• Broaden queries to include more relevant
  documents
• "pearl growing"
• Starting with high recall
• Use a very broad query
• Improve precision gradually
• "onion peeling"
• Starting with known items
• Find documents similar to the known items
• Browsing/interactive searching

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Iteration Systems strategies

• From the systems point of views
• If the system can learn from the users
  activities, the system likely can retrieve better
  results to meet users needs.
• Relevance feedback
• Users profiles
• The system should provide better output
  representations to help the user
• Browse
• Conduct interactive searches.

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Relevance Feedback

• Feedback The user provides information that the
  system can use to modify its next search or next
  display
• Relevant Feedback
• Users let the system know
• what documents are relevant to their information
  needs
• What concepts or terms are related to their
  information needs
• What weights they would like the system to put on
  each relevant documents/terms

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Relevant Feedback Systems view

• The system should invite the user to select
  relevant documents/terms from the retrieved
  results before the second retrieval is conducted
• The system should use information from user's
  feedback to conduct next search.

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Design IR Systems with relevance feedback

• Collect relevance feedback through
• Binary vs. scales
• Positive and negative feedback
• Apply relevance feedback to
• Query
• Profile
• Document
• Retrieval algorithm

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User Profiles

• User profiles
• information about the users information needs
  that IR system can use to modify its search
  process.
• Simple user profiles
• A list of terms that the user selects to
  represent his/her information needs
• A list of terms with weights

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• Extended user profiles
• More complex term structures
• Information use patterns
• levels of interests
• Users background information
• Users browsing behaviors
• What pages the user has visited last week, last
  month,
• From which page to which page

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Use of user Profiles

• Selective Dissemination of Information (SDI)
• The system regularly runs the search to get any
  new information that matches users profiles.
• The user can set up several profiles
• Once they are set up, the queries are always the
  same.
• The user can set the frequency of the update
  searches.

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SDI

• Advantages of SDI
• Automatic retrieval of new information for the
  user
• Set up a profile once, use the profile for
  retrieval many times.
• The user can change the profiles or the search
  frequency as needed.
• Disadvantages of SDI
• The query based on the profile is static
• Timing problems
• Information in need is information indeed.
• Something I am very interest, but it did not come
  at the time I want to read it.

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Use profiles during the search

• Modify the query
• When the user sends a query, the system
  automatically adds some terms to the query from
  the users profiles.
• When the user sends a query, the system checks if
  the query terms is in users profile. If it is,
  increase the weight for the terms.
• Organize the search results
• When the user sends a query, the system uses the
  profiles information to organize the search
  results (such as clustering, ranking, )

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Information Agents

• a software that applies user profiles,
  dynamically and intelligently, to search tasks
• Search distributed, possibly heterogeneous
  information resources on the users behalf.
• Gather and integrate search results by some
  Artificial Intelligence techniques
• Accept users feedback and use the feedback to
  modify the user profiles and search strategies

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Why Surf alone?

• What if you had an assistant always looking ahead
  for you when browsing the web.
• The assistant could warn you if the page was
  irrelevant, could alert you if that link or some
  other link merited your attention.
• The assistant could save you time and
  frustration.

CACM,44(8), p.71, 2001