Introduction to semantics
Inside an enterprise, information that is missing or ineffectively managed can be costly, resulting in lost business opportunities or too much time wasted on the wrong activities. Here, semantics can play a key role to make sure that all enterprise information is available, especially the unstructured data.
What is semantics? Introduction to the topic
Semantics is the study of the meaning of words and sentences; at its simplest, it concerns with the relation of linguistic forms to non-linguistic concepts and mental representations in order to explain how sentences are understood by the speakers of a language.
We can start by thinking of semantics as the “magic” that happens when people communicate and, most importantly, when they understand each other. This magic is actually a well-balanced combination of:
- being able to understand words
- having general knowledge
- and using your experience
To make sense out of a work of art, you need to combine the objective representation with your knowledge of the world; when you consider words within a context, you are able to understand the meaning and the message. That’s semantics!
Since we define what semantics is, we can understand why semantic technology is relevant for some of the most critical business activities.
Semantic technology is a way of processing content that relies on a variety of linguistic techniques including text mining, entity extraction, concept analysis, natural language processing, categorization, normalization and sentiment analysis. Compared to traditional technologies that process content as data, semantic technology is based on not just data, but the relationships between pieces of data. When it comes to analyzing text, this network enables both high precision and recall in search, and automatic categorization and tagging.
Thanks to the ability to understand the meaning of the words in context the way that humans do, semantic technology can manage a huge knowledge base to integrate information and data and allow organizations to find the information necessary for making decisions.
Information growth in terms of volume, velocity, variety and complexity, as well as in the variety of ways in which it is being used, makes its management more difficult than ever before. Here, semantics plays a key role in extracting meaning from unstructured data, transforming it into ready to use information for knowledge management, customer service, operational risk management and social media monitoring.
Semantics for Operational Risk Management
Semantic technology helps organizations manage unstructured information and transform it into usable, searchable and actionable intelligence. It uncovers data from within the organization and from the web to provide valuable insight.
Semantics for Customer Service
Managing customer experience today requires being able to streamline interactions with customers, maintaining a high level of customer satisfaction and hearing the Voice of the Customer. Semantic technologies support the implementation of advanced listening platforms, streamlining access to support, whether it is delivered directly to customers, or to support staff to help customers who need additional assistance. The key to providing efficient automated customer support is understanding the customer’s request and ensuring access to the information they need at the right time.
Semantics for Knowledge Management
External and internal sources are important resources that contain insight valuable for identifying risks and mitigating threats. To minimize operational risks and threats hiding in the supply chain and within an organization’s ecosystem, semantics can be used to support analysts in making the vast amount of content they acquire available to fuel the risk assessment process with actionable insight and intelligence. Semantic technology allows organizations to minimize their exposure to risks, and provides early identification and analysis of consumer sentiment, market trends and competitor information.