Fti Consulting, Inc.

Nuix North America Inc.

William C Knight

Nicholas I Nussbaum

Sean M McNee

John W Conwell

Steve Antoch

Sean M Mcnee

A computer-implemented system and method for generating document training sets is provided. Unclassified documents are provided to two or more classifiers. A classification code assigned to each unclassified document is received. A determination is made as to whether a disagreement exists between classification codes assigned to a common unclassified document via different classifiers. The common unclassified document with a disagreement in classification codes are provided for further review. Results of the further review include one of a new classification code and confirmation of one of the assigned classification codes. The unclassified documents for which a disagreement exists are grouped as a training set.

Computer-implemented system and method for generating document training sets

A computer-implemented system and method for assigning concept classification suggestions is provided. One or more clusters of concepts is accessed. The concepts include uncoded concepts and one or more reference concepts selected from a set of reference concepts. Each reference concept is associated with a classification code. One of the uncoded concepts is selected for classification in one such cluster. At least one of the reference concepts located closest to the selected uncoded concept is identified. The classification code of the closest located reference concept is assigned to the selected uncoded concept as a suggested classification code.

Computer-implemented system and method for assigning concept classification suggestions

A computer-implemented system and method for inclusion-based electronically stored information item cluster visual representation is provided. A set of reference electronically stored information items is maintained. A subset of the electronically stored information items is selected from the set, each associated with a classification code, each of the classification codes associated with a visual representation different from the visual representations of the remaining classification codes. The subset is combined with a set of uncoded electronically stored information items, each associated with a visual representation different from the visual representations of the classification codes. The combined electronically stored information items are grouped into clusters. Each of the clusters is visually represented, including displaying the visual representation associated with the code of each of the reference electronically stored information items in that cluster and the visual representation associated with each of the uncoded electronically stored information item in that cluster.

Computer-implemented system and method for inclusion-based electronically stored information item cluster visual representation

A computer-implemented system and method for identifying near duplicate documents is provided. A set of documents is obtained and each document is divided into segments. Each of the segments is hashed. A segment identification and sequence order is assigned to each of the hashed segments. The sequence order is based on an order in which the segments occur in one such document. The segments are compared based on the segment identification and those documents with at least two matching segments are identified. The sequence orders of the matching segments are compared and based on the comparison, a determination is made that the identified documents share a relative sequence of the matching segments. The identified documents are designated as near duplicate documents.

Computer-implemented system and method for identifying near duplicate documents

A system and method for providing visual suggestions for document classification via injection are provided. Clusters of unclassified documents and a set of reference documents, each associated with a classification code, are obtained. One or more of the unclassified documents within one such cluster are compared to the reference documents. The reference documents that are similar to the compared unclassified documents are identified for the cluster. The similar reference documents are then injected into the cluster. Each of the similar reference documents in the cluster are displayed with a visual indicator representative of the associated classification code. The unclassified documents of the cluster are also displayed. A suggestion for classification for one of the unclassified documents within each cluster is provided based on the visual indicators of the similar reference documents.

System and method for providing visual suggestions for document classification via injection

A computer-implemented system and method for visually suggesting classification for inclusion-based document cluster spines are provided. A set of reference documents each associated with a classification code is designated. A different set of un-coded documents is obtained. One or more of the coded reference documents are combined with a plurality of un-coded documents into a combined document set. The documents in the combined document set are grouped into clusters. The clusters are organized along one or more spines, each spine including a vector. A visual suggestion for assigning one of the classification codes to one of the spines is provided, including visually representing each of the reference concepts in the clusters along that spine.

Computer-implemented system and method for visually suggesting classification for inclusion-based cluster spines

A computer-implemented system and method for generating a training set for use during document review is provided. Classification codes are assigned to a set of documents. Further classification codes are assigned to the same set of documents. The classification code for at least one document is compared with the further classification code for that document. A determination regarding whether a disagreement exists between the assigned classification code and the further classification code for at least one document is made. Those documents with disagreeing classification codes are identified as training set candidates. A stop threshold is applied to the training set candidates and the training set candidates are grouped as a training set when the stop threshold is satisfied.

Computer-implemented system and method for generating a training set for use during document review

A system and method for displaying relationships between concepts to provide classification suggestions via injection is provided. A reference set of concepts each associated with a classification code is designated. Clusters of uncoded concepts are designated. One or more of the uncoded concepts from at least one cluster are compared to the reference set. At least one of the concepts in the reference set that is similar to the one or more uncoded concepts is identified. The similar concepts are injected into the at least one cluster. Relationships between the uncoded concepts and the similar concepts in the at least one cluster are visually depicted as suggestions for classifying the uncoded concepts.

System and method for displaying relationships between concepts to provide classification suggestions via injection

A computer-implemented system and method for generating a reference set via clustering is provided. A collection of unclassified documents is obtained and grouped into clusters. N-documents are selected from each cluster and are combined as reference set candidates. One of the n-documents from each cluster is located closest to a center of that cluster. A classification code is assigned to each of the reference set candidates. Two or more of the reference set candidates are grouped as a reference set of classified documents.

Computer-implemented system and method for generating a reference set via clustering

An embodiment provides a computer-implemented system and method for providing visual suggestions for cluster classification. One or more clusters comprising uncoded documents from a set are obtained. A different set of reference documents that are each classified with a code is designated. A cluster center in one of the clusters is identified. The cluster center is compared to one or more of the reference documents. Those of the reference documents that are similar to the cluster are identified based on the comparison. The classification codes of each of the similar reference documents are visually represented as a suggestion for assigning one of the classification codes to the cluster.

Computer-implemented system and method for providing visual suggestions for cluster classification

A computer-implemented system and method for generating a reference set via seed documents is provided. A collection of documents is obtained. One or more seed documents are identified. The seed documents are compared with the document collection and those documents that are similar to the seed documents are identified as reference set candidates. A size threshold is applied to the reference set candidates, which are grouped as the reference set when the size threshold is satisfied.

Computer-implemented system and method for generating a reference set via seed documents

A computer-implemented system and method for visual document classification are provided. One or more uncoded documents, each associated with a visual representation, are obtained. Reference documents, each associated with a classification code and a visual representation of that classification code, are obtained. At least one of the uncoded documents is compared to the reference documents and the reference documents similar to the uncoded document are identified based on the comparison. A suggestion for assigning one of the classification codes to the uncoded document based on the classification codes of the similar reference documents is provided, including displaying the visual representation of the suggested classification code placed on a portion of the visual representation associated with the at least one uncoded document. An acceptance of the suggested classification code is received and a size of the displayed visual representation of the accepted classification code is increased.

Computer-implemented system and method for visual document classification

A computer-implemented system and method for displaying visual classification suggestions for concepts is provided. At least one cluster is provided, the cluster including one or more uncoded concepts, each associated with a visual representation that includes a geometric shape, and one or more reference concepts, each associated with a visual representation of an assigned classification code. For at least one of the uncoded concepts, a neighborhood that includes at least one of the reference concepts is determined. A classification code for the neighborhood is determined based on the at least one of the reference concepts. The classification code of the neighborhood is suggested as a classification code for the uncoded concept, which includes displaying the visual representation of the suggested classification code placed on a portion of the geometric shape associated with the uncoded concept.

Computer-implemented system and method for displaying visual classification suggestions for concepts

A system and method for providing classification suggestions using document injection is provided. Clusters of uncoded documents are accessed. A set of reference documents is obtained. Each reference document is associated with a classification code. A set of the uncoded documents selected from one or more of the clusters is identified and compared with the set of reference documents. Those reference documents that are similar to the set of uncoded documents are identified and injected into one or more of the clusters from which the set of uncoded documents is selected. The clusters and a visual suggestion for classification of at least one of the uncoded documents within one of the clusters are displayed.

System and method for providing classification suggestions using document injection

A system and for providing reference documents as a suggestion for classifying uncoded documents is provided. A set of reference electronically stored information items, each associated with a classification code, is designated. One or more of the reference electronically stored information items is combined with a set of uncoded electronically stored information items. Clusters of the uncoded electronically stored information items and the one or more reference electronically stored information items are generated. Relationships between the uncoded electronically stored information items and the one or more reference electronically stored information items in at least one cluster are visually depicted as suggestions for classifying the uncoded electronically stored information items in that cluster.

Growing community of inventors

Bainbridge Island, WA, United States of America

William C Knight