Wo2019027992a1 Omnichannel, Intelligent, Proactive Digital Agent

by deepika

Also, the source area could additionally be no less than certainly one of an enterprise database, a streaming IoT system, a communication amongst workers, worksite infrastructure, and worksite gear. In embodiments, processing the ingested unstructured information may include executing a semantic engine that allows integration of a plurality of various information varieties right into a shared information domain information construction. The semantic engine may enable integration, for instance, of a minimum of one of data information, knowledge tables, knowledge cubes, and knowledge messages, among others. In embodiments, the semantic engine might apply statistical evaluation of the unstructured information to determine a type for integrating into the shared knowledge area knowledge structure.

For instance, this may embrace taking enterprise area and making a digital representation of area that is used as normalizing issue for all the different types of information sources. In another example, the AI agent system 10 might use domain mapping expertise that makes use of a “Semantic Web” (e.g., semantically linked web) for the purpose of mapping enterprise data and trade knowledge. Thus, when information is seen by way of a semantic area within the world model 16, the information could be recognized more easily for logic and reasoning functions. In an example, the AI agent system 10 may create mini semantic webs as a part of the world model 16 to make use of the info being semantically aligned with reference across the enterprise system 14. 9A illustrates an instance depiction of the world model 16 as forming different layers based mostly on scope and kind of knowledge.

Communication channels; and use the information graph of the world mannequin to no less than one of respond to a question and initiate an motion primarily based on communication with the client system. The system of the clauses of this paragraph whereby the world model is embodied as a knowledge graph representing an enterprise area. The system of the clauses of this paragraph wherein 160m series ftv capital the data graph facilitates mapping an intent of the query with enterprise-specific info. The system of the clauses of this paragraph wherein the knowledge graph facilitates mapping information accessible within the enterprise system with a minimal of one reality accessible on the planet mannequin that is relevant to an intent of the question.

Also, the speech analytics 8 may be used to extract data from the speech. In other examples, the ASR 7 itself or pure language understanding 3 itself or ASR 7 and NLU 3 together could present the same performance of extracting information from speech. The speech mannequin 134 could additionally be used to help ASR 7, speaker identification 9, NLU three, and speech analytics 8 with every respective function.

The world model sixteen might use machine studying to build its understanding of phrases being ingested and their relationships based on information gained from ingesting info from different types of companies or completely different products, such as from a single firm or industry. In embodiments, the semantic layer 9C-1 is a first layer that types a base for the world mannequin sixteen. This operational level facilitates disambiguation (e.g., disambiguating among a number of meanings) and understanding, corresponding to semantic meaning of phrases, queries, entities, intent and the like that is processed by the world model sixteen operational layers. Such a semantic layer 9C-1 may take into accounts a range of situations associated to queries and the wish to facilitate creating a readability of aspects of the query, such as context, intent, terminology, entities/actors and the like.

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