Abstract: A processing configuration for adaptive data ingestion and mapping receives and parses data from heterogeneous sources without requiring predefined schemas, processing structured, semi-structured, and unstructured formats. The configuration identifies entities, attributes, and relationships within parsed data and aligns them with an ontological structure using rule-based processing, machine learning, and natural language processing to resolve semantic variations. The aligned data is refined and standardized based on historical patterns, domain-specific rules, and real-time operational context, with transformations adjusted dynamically in response to data changes. Changes in incoming data are detected and differential updates are applied to previously processed data, modifying only affected portions while maintaining computational efficiency.

Abstract: A method of automated negotiation is provided. The method is implemented using at least one computer, and includes receiving, from a seller, an ask price for an item and a accept price for the item. The method also includes storing the ask price for the item and the accept price for the item in a memory element provided by the at least one computer. The method also includes providing the ask price for the item to a buyer and receiving, from the buyer, an offer price and a max price. The method also includes storing the offer price for the item and the max price for the item in the memory element. The method also includes calculating a final transaction price using the at least one computer and assessing a penalty to the buyer based at least on the offer price.