Content related to Identifying Security Risks Using Auto-Tagging and Text Analytics
Natural Language Processing and Taxonomy Design
Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that processes and analyzes human language found in text. Some of the exciting capabilities that NLP offers includes parsing out the significant entities in content through a statistical analysis … Continue reading
Best Practices for Successful Metadata Governance
Metadata governance is often seen as burdensome, tough to implement, and even harder to prioritize. When organizations embark on a metadata initiative, they tend to focus on design and development rather than governance. Metadata and taxonomies are living tools that … Continue reading
Applying The Five Laws of Library Science to your Next Taxonomy or Digital Product
The rate at which we are producing new information is unprecedented. Each year our ability to capture and create information becomes easier. As a result, the need to find information becomes more and more important. Designing the structure of information … Continue reading
Structuring Unstructured Content: The Power of Knowledge Graphs and Content Deconstruction
Unstructured content is ubiquitous in today’s business environment. In fact, the IDC estimates that 80% of the world’s data will be unstructured by 2025, with many organizations already at that volume. Every organization possesses libraries, shared drives, and content management … Continue reading
Keys to Successful Ontology Design
Ontologies can capture highly complex ideas and business logic, provide more intuitive ways to structure information, and can ultimately power new use cases, such as semantic search, recommendation engines, and AI. While many organizations aim to leverage an ontology, they … Continue reading
From Taxonomy to Ontology
As interest in designing personalized user experiences, recommendation engines, knowledge graphs, and the broader implementation of the semantic web grows, the need for the creation and implementation of ontologies becomes more critical. At Enterprise Knowledge, we define an ontology as … Continue reading
Why a Taxonomist Should Know SPARQL
As the Knowledge and Information Management field moves towards adopting semantic technologies like ontologies and enterprise knowledge graphs, taxonomists and taxonomy managers need to know about W3C semantic web standards including RDF, SKOS, SPARQL because data is becoming more interconnected … Continue reading
Designing Content for the Apprehensive Consumer
Content consumers, regardless of their form, be they a shopper, a reader, a creative, (the list goes on), are increasingly trepidatious about the content they choose to trust. With an ever-increasing slew of web content from a range of sources … Continue reading
Overcoming Enterprise Taxonomy and Ontology Design Challenges
In almost every taxonomy project, certain inescapable challenges arise. Many of these are the tangible business challenges, such as gaining stakeholder buy-in, configuring systems implementation and integration, drafting a governance procedure, and ensuring the business needs are met during every … Continue reading
What’s the Difference Between an Ontology and a Knowledge Graph?
As semantic applications become increasingly hot topics in the industry, clients often come to EK asking about ontologies and knowledge graphs. Specifically, they want to know the differences between the two. Are ontologies and knowledge graphs the same thing? If … Continue reading