ORGANIZING USER SEARCH HISTORIES

By – Pramod Shetty

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

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.

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.

Proposed System - Algorithm

Different Similarity Threshold

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

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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.

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.

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.

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.

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.

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.

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.

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.

Thank You