Conversational Search Context Retrieval Across Previous Sessions
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Solution Overview
Problem
Existing search systems struggle to leverage contextual data from previous conversational searches to enhance user experience, efficiency, and accuracy, particularly in natural language processing.
Innovation Solution
A conversational search system that retrieves and utilizes contextual data from previous user sessions by associating session identifiers with tags in an index repository, allowing for intelligent retrieval and action based on retrieved data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If contextual data from previous sessions is retrieved and used, then user experience and accuracy are improved, but system complexity increases
Solution Approach 1:
The system segments the search process into distinct components: a query processing component that handles current queries, a session management component that tracks user sessions and their contextual data, and a retrieval component that fetches relevant contextual information. This segmentation allows the system to manage complexity by organizing functions into separate, manageable modules while still achieving improved accuracy through contextual awareness.
Solution Approach 2:
The patent introduces an intermediary session management layer that acts as a mediator between the query processing system and the contextual data storage. This intermediary component (session manager) handles the complexity of tracking and retrieving contextual data across sessions, shielding the core search algorithm from complexity while enabling accuracy improvements through contextual information.
2Ease of operation
If contextual data from previous sessions is retrieved and used, then user experience is improved by allowing partial task completion, but data storage requirements increase
Solution Approach 1:
The system extracts only the essential contextual elements needed for conversational search continuity, such as session identifiers, query histories, and relevant metadata, while discarding redundant information. This selective extraction enables improved user experience through partial task completion while minimizing data storage requirements by keeping only the necessary contextual data.
Solution Approach 2:
The system implements partial task completion by retrieving and utilizing only the portion of contextual data that is necessary to answer the current query, rather than storing or processing complete session histories. This partial action approach improves ease of operation by providing relevant context without the overhead of managing extensive data storage requirements.
3Productivity
If session identifiers are associated with tags in an index repository, then contextual retrieval efficiency is improved, but index structure complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-tagging and indexing session data with relevant metadata and identifiers during session creation and updates. This preliminary organization of data into a structured index enables efficient contextual retrieval when needed, improving productivity without requiring complex query-time processing. The index structure complexity is managed by establishing clear tagging conventions during the preliminary indexing phase.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for retrieving and using contextual data from previous conversation sessions in conversational searches. In one aspect, a method includes receiving a first query for a first user session, determining that the first query refers to one or more tags in a first repository, the first repository associating respective identifiers to respective tags, each identifier representing a corresponding user session, determining one or more particular identifiers associated with the one or more tags in the first repository, retrieving particular contextual data associated with the determined particular identifiers in a second repository, the second repository associating respective identifiers to respective contextual data associated with corresponding user sessions represented by the respective identifiers, and performing an action responsive to the first query based on the retrieved particular contextual data.