Search Engine Query Generation and De-duplication
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Solution Overview
Problem
Current search engines face challenges in returning relevant results due to duplicate entries and limitations in searching unstructured data, with hash algorithms leading to false positives and an inability to access structured data sources effectively.
Innovation Solution
A search engine that generates multiple search strings from user input by rearranging and combining search terms, and includes a de-duplication mechanism to remove duplicates by comparing search results against a stored data set, allowing for structured data source querying and improved result relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hash algorithms are used to remove duplicate search results, then duplicate detection capability is improved, but false positives occur and data may be lost
Solution Approach 1:
The patent segments the search result processing into multiple stages: initial hash-based filtering followed by detailed comparison of specific fields (title, URL, content). This multi-level approach allows the hash algorithm to quickly eliminate obvious duplicates while preserving results that require more nuanced evaluation, thereby reducing false positives while maintaining duplicate detection efficiency.
Solution Approach 2:
The patent applies preliminary hash-based filtering before performing more complex duplicate detection. By using hash algorithms as a first-pass filter to identify potential duplicates, the system prepares a reduced set of candidates for detailed comparison, improving overall efficiency while maintaining reliability through subsequent verification steps.
2Speed
If traditional search engines index only unstructured data, then search speed is improved, but ability to access structured data sources is limited
Solution Approach 1:
The patent creates a universal search engine architecture that can handle both unstructured and structured data through the same indexing and query processing pipeline. By designing the system to accept diverse data types (web pages, databases, file systems, email systems) and process them uniformly, the engine achieves multi-functionality without sacrificing search speed or adaptability to different data sources.
Solution Approach 2:
The patent introduces an intermediary indexing layer that sits between various data sources (structured and unstructured) and the search engine core. This intermediary layer standardizes data from different sources into a common format suitable for indexing, allowing the search engine to access diverse data types without requiring separate processing paths, thus maintaining speed while improving versatility.
3Measurement precision
If multiple search queries are generated from user input, then search result relevance is improved, but query processing complexity increases
Solution Approach 1:
The patent segments the user's search query into multiple component terms and generates separate search queries for different combinations of these terms. By breaking down a complex query into smaller, manageable sub-queries, the system can process each segment independently and then combine results, improving relevance while keeping individual query processing simple and efficient.
Solution Approach 2:
The patent generates multiple search queries with different term combinations, performing more searches than a single query would require. This excessive action approach ensures comprehensive coverage of potential relevant results by searching with various term subsets, then filtering and ranking results to deliver the most relevant matches, thereby improving precision through controlled redundancy.
Data Source
AI summary
A search engine for generating an improved search query, the engine comprising: input means for receiving a search request, the search request comprising N search terms; processing means arranged to formulate a search query from the received search request; output means arranged to output the search query wherein the processing means is arranged to formulate the search query by generating a plurality of search strings, each search string comprising a different combination of a subset of the N search terms.