AI mission: Optimizing search results

Artificial Intelligence (AI) serves as an umbrella term for a number of technologies, machine learning being one of them. The latter comprises a number of learning approaches based on applied statistics. Such approaches may take the form of supervised and unsupervised learning — depending on the availability of training data.

Advancements in this field enable — for instance — Enterprise Search to go far beyond the commonly known keyword-based search.

First of all, state-of-the-art search technology supports natural language (Natural Language Processing, NLP). To do so, linguistic science methods and knowledge are combined with the alike from the informatics and AI fields.

Second, it considers not only a search term but also additional information which might be relevant for a user — similar to the human habitual way of communication which comprises the ability of asking and answering questions or the ability of detecting names, locations or products.

And thirdly, AI-based search applications list results in an order that focuses on the relevancy of a document to the user. To do so it may take various information sources into account, for instance pre-defined search profiles or data from which it learned what colleagues in the same department clicked.

AI mission for optimizing searches completed? This field will certainly evolve even further in future. However, it is able to support us already today to really find what we are looking for in a massive, ever-growing mountain of data.