Module: InterRed ContentAgents
AI & intelligent Knowledge Management
The amount of information that we have to deal with on a daily basis has risen constantly for some years now. But information itself is initially useless. Only information that is linked to a meaningful context can become knowledge, and thus one of the most important competitive factors of our age.
Knowledge is information that is useful in a given context. Examples are the CV of a person named in an article, other products that "match" a product, or recommendations based on a user's behaviours. Many companies have huge stores of information that lie dormant and unused in their IT systems. With intelligent software such as InterRed ContentAgents, this data can be transformed into thematically coherent knowledge that can be exploited.
InterRed ContentAgents as an AI component are both an innovative recommendation system and a smart search tool.
It first analyses the basis of the information. This can consist of the contents of the InterRed multi-channel publishing system, but can also include, for example, documents from the database or the content of “foreign” sources of information. The analysis is completely autonomous based on the predefined sources. InterRed ContentAgents identifies the topics using the contexts of the various texts. It autonomously learns to distinguish between issues related to the court (as in the royal family), courts (as in the justice system) and courts (as in places where certain sports are played). So, in our example, items related to the Queen would be assigned to "the court" (royal family), but not to the courts of justice or courts used in sport.
The result is a content-based, semantic knowledge web that is further refined and adjusted as new content is added. This web then provides the basis for a wide range of ContentAgents applications. The fact that it learns on its own, constantly adjust its knowledge webs and automatically pick up and integrates new topics makes ContentAgents clearly superior to manual, hierarchical systems such as ontologies, categorisations or keyword lists. In day-to-day practice, one quickly realizes that its automation delivers significantly better results than classification systems that are manually maintained and updated. The lack of manual effort very quickly amortises the cost of Content Agents.
What benefits does InterRed ContentAgents offer InterRed users?
InterRed ContentAgents learns, among other things, the relationships between texts and associated concepts. The benefit is extremely versatile allowing us to constantly discover new fields which we research and develop new agents for. The system is thus able, for example, to identify on its own which texts are related and offer them to the user. This is of tremendous help in all relevant editorial processes, for example, in planning the topics to be covered on the day, content research related to a new product, or simply writing an article. InterRed ContentAgents also recognise people and places and can draw attention to other relevant persons or places in their environment. It can also automatically recognise products and existing information from sources as varied as the news to operating manuals or related products, just to name just a few examples.
And what benefits does InterRed ContentAgents offer end users?
End users often reach our clients' online offers via search engines or visit their websites looking for individual topics relevant to them. They can interact with the day's events in a particular section, but can also conduct subject-specific research, product research, etc. In all cases, InterRed Content Agents automatically recognises the end user's interests because of the search terms they use or the information they read and use this information to offer further, relevant information. This then frequently extends the user's stay on the site and their click-through rate, thus adding significant attention to our clients' portfolios. Our client is perceived as individually significant, paving the way to a business transaction with the end user.
These are just a few examples of the many possibilities offered by InterRed ContentAgents technology. The system is based on the latest information technology. Innovative approaches such as genetic algorithms, fuzzy logic and SNLP turn bits and bytes into intelligent behaviours.