Document Scoring Using External Signals
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Solution Overview
Problem
Search engines face difficulties in scoring documents with poor link structures, such as print documents, as link-based scoring methods are not effective for these types of content.
Innovation Solution
The method involves generating scores for documents based on external signals like best seller list information, circulation data, publisher and author sales, user behavior, and link-based scores, combining these to provide a comprehensive scoring system that accounts for both online and offline document attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If link-based scoring is used to evaluate documents, then web documents can be scored based on hyperlink structure, but documents with poor link structure (such as print documents) cannot be effectively scored
Solution Approach 1:
The scoring system is segmented into multiple independent scoring modules: link-based scoring module, best-seller list scoring module, circulation information scoring module, publisher/author scoring module, and user behavior scoring module. Each module processes different types of signals separately and then the results are combined, allowing the system to handle both web documents with good link structure and print documents with poor link structure effectively
Solution Approach 2:
The scoring system is designed to be universal by accepting multiple types of input signals (link structure, best-seller lists, circulation data, publisher/author metadata, user behavior) and processing them through a unified scoring framework. This multi-functional approach allows the same system to accurately score diverse document types including web pages, books, and other print materials without requiring document-type-specific processing
2Measurement precision
If multiple external signals are collected and processed for document scoring, then scoring comprehensive information is improved, but system complexity increases
Solution Approach 1:
The complex scoring system is divided into distinct scoring modules, each responsible for processing specific types of signals. The link-based scoring module handles hyperlink data, the best-seller list module processes publication list information, the circulation module handles sales data, and the user behavior module processes access patterns. This segmentation allows each component to be independently optimized and maintained
Solution Approach 2:
Multiple scoring results from different modules are merged into a single comprehensive document score through a weighting and aggregation mechanism. The system combines link-based scores, best-seller list scores, circulation scores, publisher/author scores, and user behavior scores into a unified ranking, allowing the system to leverage the strengths of each signal type while presenting a simple output
Data Source
AI summary
A system generates a score for a document based on best seller list information relating to the document, circulation information relating to the document, publisher sales information relating to a publisher associated with the document, author sales information relating to an author associated with the document, user behavior information relating to access of the document by users, and/or a link-based score of a web document relating to the document.