Search Augmentation via Dual Data Store Association Indexing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional search systems face challenges in maintaining up-to-date indices due to the time-consuming process of indexing documents, which fails to reflect frequent changes and does not account for social context, leading to inefficient search results.
Innovation Solution
Implementing a dual data store system where a first data store uses an inverted index for document indexing and a second data store stores association information between users and documents, allowing for near-real-time monitoring and updating of user activities, such as likes and views, to enhance search efficiency and functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional inverted index is used for document searching, then search speed is improved, but the index cannot reflect frequent document changes due to time-consuming periodic indexing
Solution Approach 1:
The patent segments the search index into two separate components: a traditional inverted index for efficient text-based searching and a separate data structure (such as a hash table or counter-based index) for tracking document change frequencies. This segmentation allows each component to serve its specific function optimally without interfering with the other, resolving the contradiction between search speed and index freshness.
Solution Approach 2:
The patent implements periodic updating of document change frequencies at predetermined intervals (e.g., every minute, every hour, or daily) without requiring full re-indexing of the inverted index. This periodic action maintains index freshness for frequently changing documents while preserving the efficiency of the traditional inverted index structure.
2Reliability
If document indexing is performed frequently to maintain up-to-date results, then index freshness is improved, but system resource consumption increases
Solution Approach 1:
The patent applies partial action by selectively tracking and updating only the document change frequencies that are necessary for search relevance, rather than performing complete re-indexing operations. The system monitors document access patterns and change frequencies partially, updating only those portions of the index that have changed, thereby maintaining index freshness while minimizing resource consumption.
3Device complexity
If traditional search systems only index document content, then indexing complexity is reduced, but search relevance is worsened by ignoring user interactions and social context
Solution Approach 1:
The patent makes the search system multi-functional by enabling it to handle both traditional text-based searches using the inverted index and social context-aware searches using the document change frequency data. The system can universally process different types of search queries, combining full-text matching with relevance signals from user interactions, thereby improving search relevance without significantly increasing indexing complexity.
Data Source
AI summary
Techniques and tools are described for augmenting search using association information. Searches can be performed using a combination of index information and association information. In some examples, index information is stored in a first data store and association information is stored in a second data store. Search queries can be received and modified using association information. Modified search queries can be executed using a combination of index information and association information. Index information can be generated by indexing a set of documents. Association information can be generated by monitoring user activity occurring between users and a set of documents.