User Query Clustering for Web
Personalization
Contents
• Objective
• Modules
• Input Dataset
• Module Description
• References
• Objective:
To organize users search history into a set of
query groups.
Modules
The proposed system has the following
modules:
•Query Group
•Search History
•Query Relevance
•Dynamic Query Groupi...
Input Dataset
Query Time Query ClickURL
2008-11-13
00:01:30
kitchen counter
in new or leans
http://www.su
perpages.com
200...
Query Group Module
• This module is responsible for computing groups.
• First and foremost, query grouping allows the
sear...
Search History
• This module is responsible for storing the
search history of the user.
• User’s search history consists o...
Query Relevance Module
• This module is responsible to compute query
relevance between two queries using QFG.
• The edges ...
• This module calculates the query relevance by
performing random walks over the query
fusion graph.
Dynamic Query Grouping Module
• This module is responsible to group queries
dynamically.
• The proposed similarity functio...
References
• Organizing User Search Histories Heasoo Hwang, Hady W. Lauw, Lise
Getoor, and Alexandros Ntoulas IEEE TRANSAC...
Thank You
Organizing User Search Histories
Organizing User Search Histories
Organizing User Search Histories
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Organizing User Search Histories

  1. 1. User Query Clustering for Web Personalization
  2. 2. Contents • Objective • Modules • Input Dataset • Module Description • References
  3. 3. • Objective: To organize users search history into a set of query groups.
  4. 4. Modules The proposed system has the following modules: •Query Group •Search History •Query Relevance •Dynamic Query Grouping
  5. 5. Input Dataset Query Time Query ClickURL 2008-11-13 00:01:30 kitchen counter in new or leans http://www.su perpages.com 2008-11-13 00:01:33 photo example quarter doubled die coin http://www.coi nresource.com 2008-11-13 00:01:39 plays Perry cox wife scrubs http://www.ref erence.com
  6. 6. Query Group Module • This module is responsible for computing groups. • First and foremost, query grouping allows the search engine to better understand a user’s session and potentially tailor that user’s search experience according to her needs. • Once query groups have been identified, search engines can have a good representation of the search context behind the current query using queries and clicks in the corresponding query group.
  7. 7. Search History • This module is responsible for storing the search history of the user. • User’s search history consists of the Query, URL with the corresponding time and date. • User’s search history is stored in the database which is used for organizing according to the group.
  8. 8. Query Relevance Module • This module is responsible to compute query relevance between two queries using QFG. • The edges in Query Fusion Graph correspond to pairs of relevant queries extracted from the query logs and the click logs. • Query Fusion Graph merges the information of both Query Reformulation Graph and Query Click Graph.
  9. 9. • This module calculates the query relevance by performing random walks over the query fusion graph.
  10. 10. Dynamic Query Grouping Module • This module is responsible to group queries dynamically. • The proposed similarity function is used to find the similarity of queries while grouping them.
  11. 11. References • Organizing User Search Histories Heasoo Hwang, Hady W. Lauw, Lise Getoor, and Alexandros Ntoulas IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 24, NO. 5, MAY 2012 • Agglomerative clustering of a search engine query log Doug Beeferman Lycos Inc. 4002 Totten Pond Road Waltham, MA 02451
  12. 12. Thank You
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