Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system and method for classifying documents via propagation are provided. Text highlighted by a user within at least one document is identified. The document is associated with a classification code based on the highlighted text. At least a portion of the highlighted text is compared with one or more unclassified documents. Those unclassified documents with text that is the same as the compared portion of the highlighted text in the document are identified. The classification code of the document is automatically assigned to the identified unclassified documents with text that is the same. Further, those unclassified documents with text that is similar to the compared portion of the highlighted text in the document are identified. The unclassified documents with similar text are provided to the user for review and classification.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system and method for harvesting electronically stored content by custodian is provided. Content associated with user names for one or more custodians is maintained in a collaboration environment. A custodian list with names of at least a portion of the custodians is received. Access reports each having user names and associated unique identifiers for the custodians with access to the content within a collaboration environment are obtained. One or more of the user names are mapped with at least one of the custodians by comparing the list of custodians to the access reports and by determining a selected user name for the at least one custodian. The content associated with the at least one custodian is identified using the selected user name.

Abstract: A system and method for propagating classification decisions is provided. Text marked within one or more unclassified documents that is determined to be responsive to a predetermined issue is received from a user. The unclassified documents are selected from a corpus. A search query is generated from the responsive text. Same result documents are identified by applying inclusive search parameters to the query, applying the search query to the corpus, and identifying the documents that satisfy the query. Similar result documents are identified by adjusting a breadth of the query by applying less inclusive search parameters and identifying documents from the corpus that satisfy the query. A responsive classification code is automatically assigned to each same result document for classification as responsive documents. The similar documents are provided to the user. A responsive classification decision is received form the user for classification as the responsive documents.

Abstract: 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.

Abstract: 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 uncoded documents is obtained. One or more of the coded reference documents are combined with a plurality of uncoded 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.

Abstract: A computer-implemented system and method for providing visual classification suggestions for inclusion-based concept clusters are provided. Reference concepts each associated with a classification code are designated. One or more of the reference concepts are grouped with a plurality of uncoded concepts into a grouped concept set. Clusters are generated, each including a portion of the uncoded concepts and the reference concepts of the grouped concept set. A visual suggestion for assigning one of the classification codes to one of the clusters including visually representing each of the reference concepts in that cluster is provided.

Abstract: A computer-implemented system and method for providing concept classification suggestions based on concept similarity are provided. One or more uncoded concepts and a plurality of reference concepts, each reference concept associated with a classification code, are obtained. At least one of the uncoded concepts is compared to the reference concepts and reference concepts similar to the at least one uncoded concept are identified based on the comparison. One of the classification codes is suggested for the at least one uncoded concept, which includes providing a number of the classification codes associated with the similar reference concepts and a number of the similar reference concepts for each of the classification codes.

Abstract: 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.