Natural language processing (NLP) and natural language understanding (NLU) are often-confused technologies that together make search more intelligent, ensuring people can find what they want. The intelligence is had through semantic search.

NLP is a branch of artificial intelligence (AI) that deals with the interaction between computers and humans using natural language. NLU is a subset of NLP that specifically focuses on the comprehension of human language. It involves the ability of a computer system to understand the meaning and intent behind the words and phrases used in natural language. NLU techniques go beyond the surface-level processing of text and aim to capture the semantics and context. The ultimate goal of NLU is to enable machines to process language in a way that simulates human understanding, leading to more sophisticated and contextually aware interactions.

Research predicts that the role of NLP will increase in-line with the growing trend of AI and machine learning. In order to leverage unstructured content and transform dark data into actionable information, a new approach to classification is required: one that harnesses machine learning and linguistic and semantic technologies. This is important, if we want to make decision-making more predictive.

NLP encompasses a wide range of language-related tasks, including both processing and generation, while NLU focuses specifically on understanding the meaning, intent, and context of human language. NLU is a crucial aspect of building more intelligent and context-aware AI systems, enabling them to communicate with users in a more human-like manner.

NLP still faces several deficits and challenges. It is inherently ambiguous and NLP models often struggle to disambiguate between multiple possible interpretations of a sentence or phrase. Resolving ambiguity is challenging, especially when the context is limited. NLP models may struggle to grasp the context and broader meaning of a text, particularly in cases where the context is implicit or requires world knowledge that is not explicitly present in the data.

Data Harmony is Access Innovations’ AI suite of tools that leverages explainable AI for efficient, innovative, and precise semantic discovery of new and emerging concepts, to help find the information you need when you need it.

Data Harmony is so much more than an editor. It’s a suite of tools to help you with your semantic search journey. The Data Harmony suite analyzes, manages, and enriches content – so much more than a single-purpose tool.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.