Search Query Reformulation Using Entity Data Store
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Solution Overview
Problem
Existing search systems often fail to accurately capture users' intentions when searching for software applications, as keyword-based searches may not yield relevant results, especially when users' desires are not explicitly mentioned in the query.
Innovation Solution
A method that involves receiving a search query, identifying entity records from an entity data store, and generating reformulated queries by inserting or replacing terms from the entity records into the original query to improve search relevance, including techniques such as inserting entity types, names, and information to broaden search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If keyword-based search is used, then search speed is fast, but search relevance is poor
Solution Approach 1:
The patent introduces an entity data store as an intermediary between the user's search query and the application search results. The entity data store contains pre-processed entity information (names, types, descriptions) that acts as a mediator to bridge the gap between simple keyword matching and complex semantic understanding, thereby improving search relevance without requiring the search system itself to become overly complex
Solution Approach 2:
The system performs preliminary action by pre-processing and storing entity information in the entity data store before actual search queries are executed. Entity names, types, and descriptions are organized and stored in advance, allowing the search system to quickly retrieve and utilize this structured information during query reformulation without performing complex processing in real-time
2Measurement precision
If entity-based query reformulation is performed, then search relevance is improved, but processing time increases
Solution Approach 1:
Entity information including names, types, and descriptions are pre-processed and stored in the entity data store before search queries are executed. This preliminary organization of data allows the system to quickly retrieve relevant entity terms during query reformulation without performing complex processing in real-time, thus reducing processing time while maintaining improved search accuracy
Solution Approach 2:
The system applies partial action by selectively reformulating queries only when entity information is available and relevant, rather than always performing full query reformulation. The system inserts entity terms into search queries based on the specific needs of each query and the availability of matching entity records, avoiding unnecessary processing overhead
Data Source
AI summary
A method includes receiving a search query and identifying an entity record in an entity data store using the search query. The entity data store includes a plurality of entity records. Each of the plurality of entity records includes an entity name, an entity type, and entity information. The entity type indicates a category in which the entity name and the entity information belongs. The method further includes generating a reformulated query by inserting one or more terms from the identified entity record into the search query. Additionally, the method includes performing a search for software applications using the reformulated query and generating a list of software applications identified during the search.