Use cases and domains of application

AI-based search is often overwhelming for a majority of users to get started with, mainly, we believe, because of the lack of standardization – there are a lot of options to get started. In this book, we believe that it would be useful for practitioners to understand where to start by targeting the more mature and adopted techniques, use cases, and domains of application.

We will directly address the scope of possibilities for search, navigating around the jargon carried by the complex space of ML, NLP, and deep learning.

In addition, there is something to keep in mind before jumping into such a project: maintaining a balance between complexity, effort, and cost. By knowing how rapidly the field evolves with new research techniques, the initial investment can be short-lived. In this section, we are going to look at what AI-based search is and also explore the different techniques, such as named entity recognition (NER), sentiment analysis...