Web Search Ranking via User Browsing Behavior Tracking
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Solution Overview
Problem
Conventional web search ranking algorithms do not consider user browsing behavior, making it difficult for users to efficiently find relevant information amidst numerous search results.
Innovation Solution
A system and method that utilizes a server and client architecture to track user-specific word counts in short passages, adjusting search results based on user behavior by calculating a matching score for each search item, thereby prioritizing relevant items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional ranking algorithms are used to rank search results based on keyword location and frequency, then the search engine can process results efficiently, but the relevance of search results deteriorates because user browsing behavior is not considered
Solution Approach 1:
The system implements feedback by tracking user browsing behavior (which short passages users view) and using this feedback to dynamically adjust search result ranking. The server records user interactions and updates word count records to reflect actual user interest, creating a closed-loop system that continuously improves relevance based on real user behavior data.
Solution Approach 2:
The system performs preliminary action by pre-tracking and storing word count records for users before they perform searches. The server records which words appear in short passages that users view, building up a profile of user interests in advance. This preliminary data collection enables more accurate ranking without adding complexity to the search execution process.
2Quantity of substance
If the search engine indexes every word in every web page, then the search database becomes comprehensive, but the processing time and computational resources increase significantly
Solution Approach 1:
The system extracts only the necessary information from web pages - specifically, it indexes only the words that appear in short passages (abstracts or summaries) rather than every word in every page. This extraction approach maintains database completeness for search purposes while dramatically reducing the volume of data that needs to be processed and stored.
Solution Approach 2:
The system applies partial action by indexing only a subset of web page content (short passages) rather than the complete page content. This partial indexing approach provides sufficient search capability while reducing computational resources and processing time requirements compared to full-page indexing.
3Ease of operation
If the search engine uses simple keyword frequency counting, then the system remains simple and fast, but the ability to distinguish relevant from irrelevant results deteriorates
Solution Approach 1:
The system introduces dynamics by transitioning from static keyword frequency counting to dynamic word count tracking that incorporates user behavior data. The word count records are continuously updated based on which short passages users view, making the ranking system adaptive and responsive to actual user interests rather than relying on fixed, static analysis alone.
Solution Approach 2:
The system merges multiple ranking factors together - it combines traditional keyword frequency analysis with user behavior-based word count tracking. This merging creates a hybrid ranking approach that maintains the simplicity of keyword matching while adding the accuracy of user behavior consideration, achieving both ease of operation and improved reliability.
Data Source
AI summary
A system and method thereof for web search. A server comprises a storage device and a first program module. The storage device stores word count records. Each word count record has information regarding occurrences of words in short passages which have been referenced by a user. The first program module receives a user ID and a keyword, acquires multiple HTML documents corresponding the keyword, calculates a first value for each HTML document according to the word count records corresponding to the user ID, arranges multiple items corresponding to the HTML documents according to the first values thereof in descending order, and displays a web page comprising the ordered items.