AI Capability Search Scoring for Context and Keyword Matching
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Solution Overview
Problem
Existing keyword-based search methods, such as TF-IDF, fail to consider context and synonyms in natural language queries, leading to inaccurate matching of user intents with AI productivity tool-enablable software applications.
Innovation Solution
A hybrid approach combining semantic similarity search, like cosine similarity, with TF-IDF to enhance the accuracy of matching user queries by considering both context and critical keywords, using vectorized intent values for natural language processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If keyword-based search methods like TF-IDF are used, then critical keywords can be identified, but context and synonyms are not considered leading to inaccurate matching
Solution Approach 1:
The patent combines TF-IDF keyword-based search with cosine similarity semantic search into a hybrid approach. The TF-IDF component identifies critical keywords while the cosine similarity component captures context and synonyms by comparing vectorized representations of queries and capabilities. This merging resolves the contradiction by integrating both keyword precision and contextual understanding.
Solution Approach 2:
The search system uses a composite scoring mechanism that integrates results from two different search methods (TF-IDF and cosine similarity). By combining these distinct approaches into a unified hybrid search model, the system achieves both keyword accuracy and contextual relevance, similar to how composite materials combine different properties to achieve superior performance.
2Loss of information
If semantic similarity search like cosine similarity is used, then context and synonyms are considered, but critical keyword matching may be weakened
Solution Approach 1:
The hybrid search system merges cosine similarity semantic search with TF-IDF keyword-based search. While cosine similarity captures context and synonyms through vector comparison, TF-IDF simultaneously identifies and weights critical keywords. The combination ensures that both contextual understanding and keyword precision are maintained in the final search results.
3Measurement precision
If a hybrid approach combining semantic similarity search with TF-IDF is used, then both context and critical keywords are considered, but system complexity increases
Solution Approach 1:
The hybrid search system is segmented into distinct functional components: a TF-IDF processing module for keyword extraction and weighting, a cosine similarity module for semantic comparison, and a result integration module. This segmentation allows each component to specialize in its strength while working together, managing complexity through modular design.
Solution Approach 2:
The patent creates a universal hybrid search framework that can handle both keyword-based and semantic-based queries through a single integrated system. This multi-functional approach eliminates the need for separate search systems for different query types, reducing overall system complexity while maintaining comprehensive search capabilities.
Data Source
AI summary
An on the box artificial intelligence productivity tool may comprise a hardware processor executing computer-readable program code instructions for gathering natural language descriptions of capabilities associated with each of a plurality of AI productivity tool-enablable software applications, generating capability intent values from the natural language descriptions of the gathered capabilities, generating a query input intent value for a user query input received via text or audio requesting an action to be taken by one of the plurality of AI productivity tool-enableable software applications, executing a cosine semantic similarity search comparing the capability intent values to the query input intent value to identify a best match capability for the received user query input having a capability intent value that generates a highest cosine semantic similarity search score, and instructing a first of the plurality of AI productivity tool-enableable software applications having the best match capability to execute the best match capability.