Organizing user search histories. Search engine technique.

1. ORGANIZING USER SEARCH
HISTORIES
By – Pramod Shetty

2. Introduction
• Users are increasingly pursuing complex task-oriented
goals on the Web, such as making travel arrangements,
managing finances or planning purchases.
• To this end, they usually break down the tasks into a
few co-dependent steps and issue multiple queries
around these steps repeatedly over long periods of
time.
• To better support users in their long-term information
quests on the Web, search engines keep track of their
queries and clicks while searching online. We propose
a more robust approach that leverages search query
logs

3. Existing System
• Google
PageRank works by counting the number and quality of
links to a page to determine a rough estimate of how
important the website is. The underlying assumption is
that more important websites are likely to receive
more links from other websites.
• Yahoo
Click Popularity is part of Yahoo's Algorithm, Google
doesn't put much on that to determines one website
ranking. The more visitors click on your website from
Yahoo SERP's, the more you'll get close to the Top
Ranking.

4. Proposed System
• Helps users during their complex search quests
online is the capability to identify and group
related queries together.
• Identifying groups of related queries has
applications beyond helping the users to make
sense and keep track of queries and clicks in their
search history.
• 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.

5. Proposed System - Algorithm

6. Different Similarity Threshold

8. System Architecture
Login with
username
and
password
Is
Correct?
NO
User Enters
Search
Query
Is
Admin?
Upload
New Results
Query
Grouping and
Result Display
using groups
YES
NO
YES
1.
2.
3.
4.
5.
6.
7.

9. Different Modules of the System
• Login and Registration.
• Search Tracking.
• Search History Revelance and Query Group
Analysis.
• Keyword Seach using Query Groups.
• View Search History.

10. Login and Registration
• This module facilitates the system to
authenticate and add users into the system.
Thereby, the system facilitates a limited set of
users to access the system.

11. Search Tracking
• The system keeps track of all searches
performed by the users, thereby creating the
dataset required for further analysis and
identification of query groups. This feature
populates the complete set of search queries
required for generation of the search output
results in an accurate format.

12. Search History Relevance and Query
Group Analysis
• The search history generated is analyzed here
and its categorization in terms of relevance
with each other to generate search groups is
the main motive here. This relevance of
various generated queries will be analyzed to
decide the Query Groups and thereby
facilitate the history analysis and generation
of the final output.

13. Keyword Search using
• The history based search module facilitates
utilizing the Query Groups generated to
analyze the current keywords specified and
decide whether the current query belongs to
which Query Group. Based on the mapped
Query Group the system decides the final
output information to be displayed to the user
related to the Search Query and the identified
Query Group.

14. View Search Histories
• The search history tracked by the system is
displayed to the user along with a set of
details related to the search and the output
generated. This enables the user to get a
better view of the search history queries
executed till date.

15. Advantages
• 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.
• Search engines can have a good representation of the
search context behind the current query using queries and
clicks in the corresponding query group.
• This will help to improve the quality of key components of
search engines such as query suggestions, result
ranking, query alterations, sessionisation, and collaborative
search.
• We can select the ones that are highly relevant to the
current user’s query activity and recommend them to her.

16. Conclusion
• We show how such information can be used
effectively for the task of organizing user
search histories into query groups. As future
work, we intend to investigate the usefulness
of the knowledge gained from these query
groups in various applications such as
providing query suggestions and biasing the
ranking of search results.

17. Thank You