Abstract: An example method for reviewing documents includes scoring documents using an artificial intelligence model, and selecting a subset of highest scoring documents. The method further includes inserting a number of randomly-selected documents into the subset of highest scoring documents to form a set of documents for review, wherein a reviewer cannot differentiate between the randomly-selected documents and the subset of highest scoring documents included in the set of documents for review, and presenting the set of documents for review by the reviewer.

Abstract: An example method for reviewing documents includes scoring documents using an artificial intelligence model, and selecting a subset of highest scoring documents. The method further includes inserting a number of randomly-selected documents into the subset of highest scoring documents to form a set of documents for review, wherein a reviewer cannot differentiate between the randomly-selected documents and the subset of highest scoring documents included in the set of documents for review, and presenting the set of documents for review by the reviewer.

Abstract: Disclosed information exploration system and method embodiments operate on a document set to determine a document cluster hierarchy. An exclusionary phrase index is determined for each cluster, and representative phrases are selected from the indexes. The selection process may enforce pathwise uniqueness and balanced sub-cluster representation. The representative phrases may be used as cluster labels in an interactive information exploration interface.

Abstract: A term-by-document matrix is compiled from a corpus of documents representative of a particular subject matter that represents the frequency of occurrence of each term per document. A weighted term dictionary is created using a global weighting algorithm and then applied to the term-by-document matrix forming a weighted term-by-document matrix. A term vector matrix and a singular value concept matrix are computed by singular value decomposition of the weighted term-document index. The k largest singular concept values are kept and all others are set to zero thereby reducing to the concept dimensions in the term vector matrix and a singular value concept matrix. The reduced term vector matrix, reduced singular value concept matrix and weighted term-document dictionary can be used to project pseudo-document vectors representing documents not appearing in the original document corpus in a representative semantic space.

Abstract: An automated data management system and method for logging, processing, and reporting a large volume of data having different file types, stored on different media, and/or run by different operating systems, includes a first server processor for restoring a plurality of received data files, the data files being capable of being different file types; a file organizing/categorizing processor for organizing the received data files, based on a predetermined user list, into a source directory structure and a destination directory structure; a file logging processor for logging the received data files into a database formed by the source and destination directory structures and identifying a file type of the received data files; a de-duplicate processor for calculating a SHA value of the received data files to determine whether the received data files have duplicates and flagging duplicated data files in the database; an image conversion processor for converting the remaining data files into image files, respective

Abstract: Disclosed are an apparatus and a method for remote recovery of inaccessible data on computer storage devices. The method comprises the steps of (1) establishing a communications link from the local computer containing the storage device requiring recovery of data to a remote data recovery computer operated by a technician; (2) allowing the remote technician to interact as though seated in front of the local computer yet having access to all software programs which are resident at the technician's computer, and (3) enabling the remote technician to diagnose and rectify the data loss.