Vector search is a method used in information retrieval and machine learning to find similar items based on their mathematical representations as vectors. In this approach, each item is represented as a high-dimensional vector, with each dimension corresponding to a feature or characteristic of the item. Vector search algorithms then compare these vectors to find similar items, such as having similar features or being close together in the vector space. Read more here.
My group and I are currently doing a research project on natural language processing and iKnow plays a big role in this project. I am aware that the algorithms iKnow use aren't public, and I respect that.
My question is, are there any public documents/research that explains, at least part of, the algorthims iKnow uses and the motivations for using them?
By update