Instant Messaging Agent for Natural Language Data Storage Management
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Solution Overview
Problem
Current data storage management systems lack efficient methods for processing natural language-based requests, leading to complexities in issuing and managing data storage commands, especially in multi-user environments where direct interaction with storage devices is abstracted and requires precise command syntax.
Innovation Solution
Implementing a system that uses natural language processing (NLP) to extract information from messages sent via an instant-messaging protocol, allowing clients to issue data storage management requests through a chat-based interface, where the IM agent analyzes and processes natural language inputs to formulate and execute commands, maintaining context and state information across message exchanges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural language processing is implemented to process user inputs, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The patent introduces an instant messaging agent as an intermediary between the user and the data storage management system. The agent receives natural language messages from users, processes them through NLP to extract commands and parameters, and translates them into formal data storage management requests. This intermediary layer shields users from system complexity while managing the processing burden systematically.
Solution Approach 2:
The patent replaces traditional mechanical interaction mechanisms (command-line interfaces, form-based interfaces) with a natural language processing system. Instead of requiring users to learn specific command syntax or navigate complex menus, the system uses NLP to interpret human-like language, automatically extracting intent and parameters to execute storage management operations.
2Ease of operation
If chat-based interface is used for command input, then ease of operation is improved, but measurement precision worsens
Solution Approach 1:
The instant messaging agent implements feedback mechanisms to clarify ambiguous inputs. When the NLP system cannot confidently interpret a message or when parameters are missing/ambiguous, the agent engages the user in a conversational exchange to request clarification, confirm understanding, or provide options. This iterative feedback loop ensures precise interpretation while maintaining the natural language interface.
Solution Approach 2:
The system performs preliminary processing of natural language messages to identify intent, extract parameters, and validate inputs before executing commands. The NLP pipeline pre-processes messages to structure unstructured data, identifies required parameters in advance, and prepares validation rules, ensuring that by the time execution occurs, the command interpretation is as precise as possible.
3Productivity
If natural language processing is implemented, then productivity is improved, but loss of information increases
Solution Approach 1:
The agent uses feedback to verify that extracted parameters match user intent before execution. It confirms critical parameters with the user, asks for clarification on ambiguous values, and provides summaries of interpreted commands for approval. This reduces information loss by ensuring accurate parameter extraction while maintaining fast processing through automated NLP.
Data Source
AI summary
Techniques for issuing a data storage management request may include: receiving, from a client at a data storage system, a set of one or more messages; performing natural language processing on the set of one or more messages to extract first information used in forming the data storage management request; executing the data storage management request in accordance with the first information extracted; and responsive to executing the request, sending a response to the client indicating a result of executing the data storage management request. State information may be retained in connection with a first conversation to obtain information for a first request or command. If the first conversation is interrupted to commence a second conversation for a second request, the state information may be stored for the duration of the second conversation and then restored to resume the first conversation from the point of interruption.