Introduction

Luma Knowledge is a system that facilitates organizations to store and retrieve knowledge, improve collaboration, locate knowledge sources, capture, and use knowledge. It helps to organize documents, frequently asked questions, and other information into easily accessible formats and enhances the user experience for both internal and external customers.

Serviceaide’s Luma Knowledge is a knowledge repository that processes information available in various sources like Word documents, Excel workbooks, Websites, Multimedia content, and generates Knowledge Artifacts like FAQs, Articles, and Metadata. Luma Knowledge provides a framework for a guided search to retrieve the most suitable content from the artifact.

Below are the main elements of the Luma Knowledge :

Knowledge Building

One of the essential Elements in Luma Knowledge is Knowledge Building. It refers to the process of adding, processing and managing information in the system, that can be consumed by the End users. As part of Knowledge Building, information is Curated and saved as Artifacts in Luma Knowledge. System administrators / Curators manage the Artifacts to maintain the effectiveness of the content.

Artifacts:

An Artifact is the source of information and is the basic building block of Luma Knowledge. It can be a document, web source, multimedia file, or any other content that contains information deemed important for knowledge sharing within the organization or to the external world. The information available in the artifacts is processed by the system to generate Knowledge Artifacts. Below are the phases of Artifact life cycle in Luma Knowledge:

Candidate Artifact: These are written articles, documents, publications, frequently asked questions (FAQ’s), service definitions, manuals, etc. or knowledge held in the minds of subject matter experts that are used to build knowledge in Luma Knowledge.
Knowledge Artifact: Processed artifact decomposed into FAQs, Attributes, enhanced with metadata and Approved for distribution
Retired Artifact: An Artifact that is no longer in use or searched by users.

Knowledge Curation

Curation is the process that builds Knowledge Artifacts. The process involves :

Creating an artifact
Processing the information to generate Questions and Answers it may address (FAQs)
Determine metadata
Information Review
Publishing to make it available for End Users

Another essential fundamental element of Luma Knowledge is Knowledge Sharing. It is referred to as the system's ability to Share and Exchange the available Knowledge with Users and interface systems. Luma Knowledge allows searching, accessing, and sharing Knowledge via Search Widget and APIs. It enhances user experience by understanding the request context and identifies the best response for the user’s request from the available Knowledge artifacts repository. The knowledge search consists of the following steps:

Parsing the inquiry and Normalizes terms to understand the user's intent.
Perform an ontology search in Luma Knowledge databases
Determine and return the best response

Knowledge Improvement

Luma Knowledge aims at improving the effectiveness and efficiency of the organization’s Knowledge available in the system from time to time. It includes updating the existing knowledge, Reviewing and Publishing the content, and augmenting the existing information.

Luma Knowledge continuously assesses feedback received from End Users on the artifacts and Surveys responses. This feedback is used to generate KPIs and recommendations for System Administrators and Curators to keep the Artifacts up to date.

Knowledge Discovery

Knowledge discovery is identifying the new implicit knowledge from Artifacts, User Inquiries, and information gathered from the user’s interaction with the system. Luma Knowledge identifies and stores meta-data, search patterns, and user’s actions. The implicit information is used to determine the effectiveness of the system and manage Knowledge Gaps.

Knowledge Foundation

Knowledge Foundation outlines the models and methods used to store Knowledge in the system. Luma Knowledge processes the information, generates the metadata, and saves the details in the below models:

Application database to save the Knowledge artifact content and metadata.
A graph database to store the relationships between Domain, topics, artifacts, and FAQs.
Elastic Search database to enable fast searches against the large volume of data available in the system

The information available in the system can be viewed as Artifacts & FAQs in Knowledge Base, their relationships in Knowledge Graph, and the Original Document that is used to create the artifact.

Knowledge Base

The Knowledge base is a data store that holds the physical Knowledge artifacts. It consists of Articles (source information used to generate Knowledge artifacts), FAQs, and the Metadata generated during the curation process. It also contains the required configurations to support knowledge curation.

Knowledge Ontology

Knowledge Ontology represents the vocabulary of business knowledge in the system and should be the primary source of vocabulary used by all components in the system. In Luma Knowledge, it holds metadata about all existing Knowledge artifacts. It consists of entities, their hierarchical order, and relationships with other entities. The ontology grows when knowledge artifacts are curated.

Knowledge Graph

The knowledge graph is the visual representation of entities in Luma Knowledge (Topics, Parent Topics, Articles, and FAQs) as Nodes and directional Relationships between the Nodes. The search request and meta-data are saved in the knowledge graph, which is used to enhance other inquiries and identify knowledge gaps.

Vocabulary

Vocabulary in Luma Knowledge is the term an organization uses to describe its knowledge. It essentially is the meta-data of knowledge artifacts with synonyms and abbreviations. Along with out-of-the-box vocabulary, curated vocabulary is built as meta-data is reviewed and saved by the curator.

Let us learn more about Luma Knowledge.