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Method and System for Offline Cognitive Data Mining

IP.com Disclosure Number: IPCOM000248316D
Publication Date: 2016-Nov-15
Document File: 2 page(s) / 64K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system is disclosed for leveraging cognitive data mining by projecting possible needs/scenarios for a physical/virtual appliance with different domain specific plugin modules.

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Method and System for Offline Cognitive Data Mining

In current scenario, constant connectivity is an essential pre-requisite for cognitive engines/platforms to deliver a response on demand. Constant connectivity is not a practical solution due to reasons which may be, but are not limited to security/privacy issues and bandwidth of an internet connection. Also, the erstwhile methods of providing offline data from local database copies follow static rules for replicating data based on parameters which may be, but not limited to set criteria and timeframe, and may not serve the purpose effectively.

Disclosed is a method and system for leveraging cognitive data mining by projecting possible needs/scenarios for a physical/virtual appliance with different domain specific plugin modules. The method and system provides faster computing features by dynamically loading offline "snapshots" for fast and/or off-line delivery of cognitive data based on the percentage of confidence of the projected need/scenario.

As illustrated in Figure 1 below, any computing architecture with reference to an enterprise topology, functioning to provide cognitive features would include a cognitive appliance.

Figure

Domain specific plugin modules may be inserted into the cognitive appliance, wherein the plugin modules comprises snapshots of existing domain knowledge. The plugins or modules are usually relevant to a business or organization with a physical or virtual presence, (ex: fire fighters, lifeguards, bridge inspectors, airplane maintenance, oil refinery inspectors, power plant managers) to which the solution is being provided. The

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existing domain knowledge further comprises historical data retrieved by a cognitive engine in line with a projected case of need/scenario.

The snapshots of the existing domain knowledge is based on cognitive analysis conducted by the system. The factors determining the percentage of confidence as per the cognitive analysis may be, but are not lim...