A Bag-of-Features Algorithm for Applications Using a NoSQL Database

In this paper we present a Bag-of-Words (also known as a Bag-of-Features) method developed for the use of its implementation in NoSQL databases. When working with this algorithm special attention was brought to facilitating its implementation and reducing the number of computations to a minimum so as to use what the database engine has to offer to its maximum. The algorithm is presented using an example of image storing and retrieving. In this case it proves necessary to use an additional step of preprocessing, during which image characteristic features are retrieved and to use a clustering algorithm in order to create a dictionary. We present our own k-means algorithm which automatically selects the number of clusters. This algorithm does not comprise any computationally complicated classification algorithms, but it uses the majority vote method. This makes it possible to significantly simplify computations and use the Javascript language used in a common NoSQL database.