Abstract: Disclosed herein are systems and methods for graph-based dynamic information retrieval and synthesis, particularly for enhancing the response generation of chatbot applications using large language models (LLMs). The methods involve receiving a user query, generating a query embedding, and accessing a knowledge graph comprising nodes representing documents with associated document embeddings. A set of documents is retrieved based on similarity scores, and a distance matrix is constructed to calculate shortest-path distances between nodes. Documents are clustered to identify a largest cluster from which content is retrieved to formulate a response. The disclosed embodiments improve upon retrieval augmented generation (RAG) by leveraging the hierarchical relationships of a knowledge graph and node interconnectedness to provide contextually coherent information and mitigate the inclusion of information from irrelevant or superficially related documents in LLM responses.

Abstract: The present invention provides for a system and a method for improved representation of classical data on quantum systems. Input classical data is received and a feature set is created from the classical data. A functional transformation is performed on the created feature set to reduce high dimensional data associated with the feature set and a low dimensional feature space dataset is generated. A feature space transformation is performed on the low-dimensional feature space dataset to obtain a new feature space dataset with enhanced feature representation of the low-dimensional feature space dataset in a multi-dimensional space. The new feature space dataset results in optimal mapping of the input classical data into a quantum format. The new feature space dataset is sampled and batches of the sampled dataset are selected. The sampled dataset is mapped into an optimized quantum format for loading the sampled dataset into quantum states.

Abstract: The present invention provides for a system and a method for improved representation of classical data on quantum systems. Input classical data is received and a feature set is created from the classical data. A functional transformation is performed on the created feature set to reduce high dimensional data associated with the feature set and a low dimensional feature space dataset is generated. A feature space transformation is performed on the low-dimensional feature space dataset to obtain a new feature space dataset with enhanced feature representation of the low-dimensional feature space dataset in a multi-dimensional space. The new feature space dataset results in optimal mapping of the input classical data into a quantum format. The new feature space dataset is sampled and batches of the sampled dataset are selected. The sampled dataset is mapped into an optimized quantum format for loading the sampled dataset into quantum states.

Abstract: A system and method for optimizing aggregation and analysis of data across multiple data sources of multiple enterprises is provided. Data extraction rules are generated by invoking an automatic rule generation rule. Automatic rule generation rule is invoked if a predefined set of rules is not applicable for extracting data. Further, data adaptation rules is generated if data extracted by applying data extraction rules and a predefined set of rules does not correspond to a predetermined output. The data adaptation rules is encapsulated in a feedback loop for transmitting to the data acquisition unit. Data optimization rules s generated based on data extraction rules and data adaptation rules. One or more metrics is generated based on data optimization rules. The metrics specify characteristics relevant to one or more enterprises.

Abstract: A system and method for optimizing aggregation and analysis of data across multiple data sources of multiple enterprises is provided. Data extraction rules are generated by invoking an automatic rule generation rule. Automatic rule generation rule is invoked if a predefined set of rules is not applicable for extracting data. Further, data adaptation rules is generated if data extracted by applying data extraction rules and a predefined set of rules does not correspond to a predetermined output. The data adaptation rules is encapsulated in a feedback loop for transmitting to the data acquisition unit. Data optimization rules s generated based on data extraction rules and data adaptation rules. One or more metrics is generated based on data optimization rules. The metrics specify characteristics relevant to one or more enterprises.

Abstract: A method, computer and system for the backup and recovery of a converged infrastructure computer system is provided. The method and system provides backup and recovery of the data and applications on the servers themselves, but further provides backup and recovery of the configuration and mapping information of the converged infrastructure computer system itself.

Abstract: A method and system are provided for inserting access control rules into an access control list. The access control list may be configured to contain independent rule blocks having ordered access rules. In one example, the method includes creating a new independent rule block and inserting a new access rule into the block if the list is empty. If the list is not empty, a set of mapped independent rule blocks may be created from the list. For each block in the set, the method may attempt to determine a position for the new access rule. Those blocks for which a position cannot be determined may be removed from the set, and the blocks in the set may be merged to form a new independent rule block with the new access rule.