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Thanthriwatta T.M
   The significance of effective and efficient
    information retrieval.

   Usage of Internet and web technologies.

   Advent of WWW and web search engines.
   Generic web search engine cannot identify
    the different needs of different customers.

   The search results should be personalized to
    address this issue.

   Personalized   Web Search concept was
    introduced.
   The importance of the          concept    of
    Personalized Web Search.

   Personal interest     to   study   on    this
    technological area.
   Ability to identify the different needs of
    different people who issue the same text
    query for web search.
    e.g. ‘Matrix’, ‘apple’

   Yahoo used this concept in 1998

   80 % of the users prefer to use personalized
    web search engines.
   User profiling
     Client side implementation
     Server side implementation
     Content analysis

   Hyperlink analysis

   Community based PWS

   User location based PWS
   A separate user profile should be maintained for
    each user.

   User      profile consists with   technical,
    demographical and geographical informations
    of users.


   Previously visited pages, total visit time, number
    of visits , used links, age, gender, education, IP
    addresses and bookmarks etc.
   Search engine has to maintain user profiles
    by using its resources.

   Engine can use its all resources to optimize
    the search results.

   Allocate a huge amount of memory and
    computing processes to maintain millions of
    user profiles.
   Users /clients are the responsible parties for maintaining
    their user profiles.

   An installed software/plugin should be used to facilitate.

   Violation of privacy and security can be preserved as
    much as possible.

   Cost of storage & computing processes are distributing
    among users.

   Limitation of network bandwidth.
   This is under User profiling technique

   Check the similarity between web pages and
    user profile details.

   User interested topics and title or content of
    the web pages are much concerned.
   Most of the leading search engine use this
    method

   Crawling and ranking concepts

   PageRank and Biased PageRank approaches
   Avoid the handling of separate user profile
    for each user.

   Search engine has to find the users who have
    similar kinds of interests.

   Efficient   identification    increases    the
    productivity of the collaborative web search.
   Groupization
     Give higher weights to pages that are relevant to
     more members of the group.

   Hit-Highlighting
     Users’ keywords appeared within the title,
     snippet or URL of each page are emphasized.
   Some users search things in a particular area. (by
    implicit local intent queries)
     E.g. Italian restaurants in San Francisco

   It uses IP addresses mapping for identifying city
    name, Zip code

   Issues
     Some names are ambiguous like Oakland
     Some have distinct meanings (Mountain view)
   Google Custom search engine

   Alpha search engine

   Google web history tool

   iGoogle & My Yahoo!

   Yoople! Collaborative web search engine
   This is an area, the concept can be used in a
    practical manner.

   Identify the people in destroyed location by
    analyzing user profiles.

   Alert people, before the disaster happens by
    analyzing scientific stuffs.
   PWS is more time and effort consumable than
    generic web search.

   Violation of privacy

   Ethical and security issues

   Users’ needs are not static.

   Handling more complex user profiles.
   How to overcome the limitations.

   Usage of location based PWS by covering
    more geographical area.

   Query expansions

   Enhance PWS by using the commonsense
    and folksonomy.
   The concept of PWS is an evolving study
    area.

   Adding more techniques frequently.

   PWS can use for managing the real world
    scenario like disasters etc.

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Personalized Web Search

  • 2. The significance of effective and efficient information retrieval.  Usage of Internet and web technologies.  Advent of WWW and web search engines.
  • 3. Generic web search engine cannot identify the different needs of different customers.  The search results should be personalized to address this issue.  Personalized Web Search concept was introduced.
  • 4. The importance of the concept of Personalized Web Search.  Personal interest to study on this technological area.
  • 5. Ability to identify the different needs of different people who issue the same text query for web search. e.g. ‘Matrix’, ‘apple’  Yahoo used this concept in 1998  80 % of the users prefer to use personalized web search engines.
  • 6. User profiling  Client side implementation  Server side implementation  Content analysis  Hyperlink analysis  Community based PWS  User location based PWS
  • 7. A separate user profile should be maintained for each user.  User profile consists with technical, demographical and geographical informations of users.  Previously visited pages, total visit time, number of visits , used links, age, gender, education, IP addresses and bookmarks etc.
  • 8. Search engine has to maintain user profiles by using its resources.  Engine can use its all resources to optimize the search results.  Allocate a huge amount of memory and computing processes to maintain millions of user profiles.
  • 9. Users /clients are the responsible parties for maintaining their user profiles.  An installed software/plugin should be used to facilitate.  Violation of privacy and security can be preserved as much as possible.  Cost of storage & computing processes are distributing among users.  Limitation of network bandwidth.
  • 10. This is under User profiling technique  Check the similarity between web pages and user profile details.  User interested topics and title or content of the web pages are much concerned.
  • 11. Most of the leading search engine use this method  Crawling and ranking concepts  PageRank and Biased PageRank approaches
  • 12. Avoid the handling of separate user profile for each user.  Search engine has to find the users who have similar kinds of interests.  Efficient identification increases the productivity of the collaborative web search.
  • 13. Groupization  Give higher weights to pages that are relevant to more members of the group.  Hit-Highlighting  Users’ keywords appeared within the title, snippet or URL of each page are emphasized.
  • 14. Some users search things in a particular area. (by implicit local intent queries)  E.g. Italian restaurants in San Francisco  It uses IP addresses mapping for identifying city name, Zip code  Issues  Some names are ambiguous like Oakland  Some have distinct meanings (Mountain view)
  • 15. Google Custom search engine  Alpha search engine  Google web history tool  iGoogle & My Yahoo!  Yoople! Collaborative web search engine
  • 16. This is an area, the concept can be used in a practical manner.  Identify the people in destroyed location by analyzing user profiles.  Alert people, before the disaster happens by analyzing scientific stuffs.
  • 17. PWS is more time and effort consumable than generic web search.  Violation of privacy  Ethical and security issues  Users’ needs are not static.  Handling more complex user profiles.
  • 18. How to overcome the limitations.  Usage of location based PWS by covering more geographical area.  Query expansions  Enhance PWS by using the commonsense and folksonomy.
  • 19. The concept of PWS is an evolving study area.  Adding more techniques frequently.  PWS can use for managing the real world scenario like disasters etc.

Editor's Notes

  • #8: User profile consists with technical,demographic and geographic information of users.