Abstract: Presented are systems and methods for identifying information about a particular entity including acquiring electronic documents having unstructured text, that are selected based on one or more search terms from a plurality of terms related to the particular entity. Tokenizing the acquired documents to form a data matrix and then calculating a plurality of eigenvectors, using the data matrix and the transpose of the data matrix. The variance is then acquired for determining the amount of intra-clustering between the documents and then the acquired documents are clustered using some of the eigenvectors and the variance.

Abstract: Presented are systems and methods for identifying information about a particular entity including acquiring electronic documents having unstructured text, that are selected based on one or more search terms from a plurality of terms related to the particular entity. Tokenizing the acquired documents to form a data matrix and then calculating a plurality of eigenvectors, using the data matrix and the transpose of the data matrix. The variance is then acquired for determining the amount of intra-clustering between the documents and then the acquired documents are clustered using some of the eigenvectors and the variance.

Abstract: Presented are systems and methods for identifying information about a particular entity including acquiring electronic documents having unstructured text, that are selected based on one or more search terms from a plurality of terms related to the particular entity. Tokenizing the acquired documents to form a data matrix and then calculating a plurality of eigenvectors, using the data matrix and the transpose of the data matrix. The variance is then acquired for determining the amount of intra-clustering between the documents and then the acquired documents are clustered using some of the eigenvectors and the variance.

Abstract: Presented are systems and methods for identifying information about a particular entity including acquiring electronic documents having unstructured text, that are selected based on one or more search terms from a plurality of terms related to the particular entity. Tokenizing the acquired documents to form a data matrix and then calculating a plurality of eigenvectors, using the data matrix and the transpose of the data matrix. The variance is then acquired for determining the amount of intra-clustering between the documents and then the acquired documents are clustered using some of the eigenvectors and the variance.

Abstract: Presented are systems and methods for identifying information about a particular entity including acquiring electronic documents having unstructured text, that are selected based on one or more search terms from a plurality of terms related to the particular entity. Tokenizing the acquired documents to form a data matrix and then calculating a plurality of eigenvectors, using the data matrix and the transpose of the data matrix. The variance is then acquired for determining the amount of intra-clustering between the documents and then the acquired documents are clustered using some of the eigenvectors and the variance.