Abstract: A data store associated with one or more entities of a graph database hosted at a knowledge base hosting network maintains a respective one or more records of a plurality of mutation operations performed on the one or more entities. One or more of the plurality of mutation operations performed on the one or more entities is obtained from the data store. One or more documents of a document storage are then generated or updated based on the one or more of the plurality of mutation operations performed on the one or more entities obtained from the data store.

Abstract: A documentation generation engine coupled to a mutation handler are provided, configured to traverse a knowledge base to derive selective views. Organizations may configure a documentation generator application running on generator hosts to summarize records of a knowledge base storing institutional knowledge, and relationships therebetween, as human-readable reference documents. It is undesired for the documentation generator to query the knowledge base on a naive basis in response to updates in order to derive views required to generate updated documentation.

Abstract: Techniques for searching an inverted index associating byte sequences of a fixed length and files that contain those byte sequences are described herein. Byte sequences comprising a search query are determined and searched in the inverted index. In some examples, training data for training machine learning (ML) model(s) may be created using pre-featured data from the inverted index. In various examples, training data may be used to retrain the ML model until the ML model meets a criterion. In some examples, the trained ML model may be used to perform searches on the inverted index and classify files.

Abstract: A documentation generation engine coupled to a mutation handler are provided, configured to traverse a knowledge base to derive selective views. Organizations may configure a documentation generator application running on generator hosts to summarize records of a knowledge base storing institutional knowledge, and relationships therebetween, as human-readable reference documents. It is undesired for the documentation generator to query the knowledge base on a naive basis in response to updates in order to derive views required to generate updated documentation.