What is Content Intelligence?

Approximately 80% of the information available in an enterprise is dispersed throughout the organization and the volume is growing at a rate of 50 to 60% each year. No matter how powerful, computers aren't capable of deriving meaningful information from unstructured data and the diversity, volume and velocity at which it's flowing into businesses makes it difficult for individuals to manage, so they don't. As a result, the vast majority of human intelligence isn't used in decision-making processes. Content Intelligence - the combination of semantic technology and information science - is the solution to this problem.

Semantic technologies make meaning in information explicit, for purposes of human and/or machine interpretation and communication (Gartner). When semantic technologies combine with information science, machines can model, interpret, describe, analyze and visualize the content of an enterprise in order to leverage the human intelligence within that content.

The process begins with a model that defines what's important to the business; the topics, resources, concepts and the relationships between them. Smartlogic’s Text Miner tool makes it easy to enhance your model by searching a set of documents to identify the most frequent terms found within your content so you can add them to your model. The model is interpreted by extracting the vocabulary and relationships so the content can be put in the context of the business and the vocabulary and relationships are used to classify and tag the content across multiple dimensions of interest. Automated analysis using Natural Language Processing (NLP) and entity, fact and relationship extraction methods are applied to visualize the results; displaying the relationships between different components of content in the corpus.

Intelligent content is good for businessWhy Content Intelligence?

There are organizational costs and increased risk when your content isn’t well described; wasted time and money, regulatory sanctions and decreased reputation. The ability to manage operational, regulatory, customer, productivity and rework imperatives within the enterprise can result in improved business outcomes and increase ROI.

  • Operational – There's an organizational cost to not having access to human intelligence. Imagine an oil company sending an engineer to repair a malfunctioning oil well. The engineer doesn't have access to the most recent schematics and as a result doesn't provision the parts and tools he needs. He's wasted time and money traveling to the job site and the well still needs repair.
  • Regulatory – The increasing regulatory pressures on organizations today can result in increased costs and risk when content intelligence is not available. Drug companies must report to regulators all observed side effects for drugs that are available for as long as the drug is sold. Without content intelligence they may not find a way to extract this information from doctors, nurses and health care practitioners notes leaving them open to sanctions.
  • Customer – Finding new customers, retaining existing customers and maximizing revenue per customer are challenges faced by every organization. A large retailer increased online orders by 10% by analyzing customer comments from social media forums and on their website to drive product and category popularity scores. They used these scores with their search engine to ensure that customers found products they would be interested in buying.
  • Productivity - A recent survey reported that knowledge workers spend, on average, 38 minutes searching for each document they need. The IDC estimates that the productivity of the average knowledge worker is reduced by 21% because they spend too much time searching for information, which means for every 1,000 employees, an organization would need to hire an additional 210 employees to compensate for lost time.
  • Rework – It's bad enough that people can't find the information they need. When a critical document or piece of information is missing and needs to be recreated the organization loses time and money. And often the results are not the same, which leads to inconsistencies in the way business is conducted.

Despite the obvious benefits, most organizations struggle to extract the human intelligence in content. While many organizations invest in content management solutions, the ability to expose and use the human intelligence buried in the content is compromised. In isolation, content management systems are inadequate as they provide a single organizing construct of folders and file cabinets that mimic the paper constructs that preceded them. Enterprise search adds a needed, but insufficient, capability where words are indexed and retrieval is based on the appearance of specific words in a document. While a start, search engines lack an understanding of the context in which a word or phrase is used as well as the relationships between concepts. This lack of context means that the human intelligence is poorly communicated, or worse - wrongly communicated.

Content Intelligence Revolution

Content intelligence is the starting point for an explosion of innovation in the information space. An examination of history says that in the beginning, there was paper and business was manual. In the 1970s, transactions lived in hierarchical data structures and businesses became automated. In the 1980s, data was organized into relational databases, which were self-describing, in the sense that you could query the database to understand its structure and the data was available to multiple programs and systems. That one change – the ability of the data to self-describe –led to an explosion of innovation in the structured data space. Data warehouses, data marts, business intelligence platforms and even big data analytics are all innovations that evolved from that one significant change.

Semaphore Drives Content Intelligence

Semaphore, Smartlogic’s Content Intelligence platform, is a sophisticated semantic software technology that turns content into a self-describing resource. Semaphore leverages Linked Data standards and graph database technology to unify all information within the enterprise to be used for analysis, to manage information governance, to drive business processes and to gain insight at a fraction of the cost and time without the restrictions of traditional methods. Thirty years after the self-describing revolution in structured data, content can be unified and self-described in a way that allows for true innovation and exploitation. Content becomes Intelligent.


Semaphore Rulebase Generator (SRG) creates model-driven rulebases by extracting the concepts, labels and relationships from within your taxonomy or ontology. We pass these rulebases to Semaphore Classification Server to result in a precise, consistent and complete set of rules that drive content classification.

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With Semaphore you begin with a model that defines what is important to your business; the concepts, topics, resources, vocabulary and the relationships among them. Semaphore leverages the model and creates rulebases which are used to analyze and classify content with sophisticated metadata tagging processes making it available to other applications, such as search engines, content management systems and data stores.

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Semaphore Advanced Language Packs help you extract the vocabulary and relationships from your classification model so content can be put in the context of the business. Using text analytics and natural language processing strategies such as stemming, tokenization, lemmatization and part of speech tagging, you can identify the sentiment and context within unstructured information and use it to improve your organization.

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Semaphore’s visualization tools let you quickly see how information within your enterprise is related; the topics, concepts and relationships between them. Our easy-to-use tools let you explore your model and immediately access information using classification output to drive search and information discovery. 

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