Abstract: Systems and methods for indexing information and for performing searches are disclosed. In these systems and methods information is “ingested” into the system by clustering the information using a clustering algorithm such as k-means or k-medoids clustering. During the clustering process, a hybrid distance measurement is used that allows the systems and methods to determine similarity across a number of different types of information. Once the information is clustered, it is stored and “mirrored” both in a structured (e.g., relational) data repository and in an unstructured data repository. Methods according to the invention allow the retrieval of both direct search results and search results including related concepts. After clustered information is stored, future searches can be performed by searching the stored results in whichever data repository is most appropriate for the context.

Abstract: Systems and methods for indexing information and for performing searches are disclosed. In these systems and methods information is “ingested” into the system by clustering the information using a clustering algorithm such as k-means or k-medoids clustering. During the clustering process, a hybrid distance measurement is used that allows the systems and methods to determine similarity across a number of different types of information. Once the information is clustered, it is stored and “mirrored” both in a structured (e.g., relational) data repository and in an unstructured data repository. Methods according to the invention allow the retrieval of both direct search results and search results including related concepts. After clustered information is stored, future searches can be performed by searching the stored results in whichever data repository is most appropriate for the context.

Abstract: Systems and methods for indexing information and for performing searches are disclosed. In these systems and methods information is “ingested” into the system by clustering the information using a clustering algorithm such as k-means or k-medoids clustering. During the clustering process, a hybrid distance measurement is used that allows the systems and methods to determine similarity across a number of different types of information. Once the information is clustered, it is stored and “mirrored” both in a structured (e.g., relational) data repository and in an unstructured data repository. Methods according to the invention allow the retrieval of both direct search results and search results including related concepts. After clustered information is stored, future searches can be performed by searching the stored results in whichever data repository is most appropriate for the context.