Abstract: A system and for displaying relationships between concepts to provide classification suggestions via inclusion is provided. A set of reference concepts each associated with a classification code is designated. One or more of the reference concepts are combined with a set of uncoded concepts. Clusters of the uncoded concepts and the one or more reference concepts are generated. Relationships between the uncoded concepts and the one or more reference concepts in at least one cluster are visually depicted as suggestions for classifying the uncoded concepts in that cluster.

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: 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 system and method for displaying relationships between concepts to provide classification suggestions via nearest neighbor is provided. Reference concepts previously classified and a set of uncoded concepts are provided. At least one uncoded concept is compared with the reference concepts. One or more of the reference concepts that are similar to the at least one uncoded concept are identified. Relationships between the at least one uncoded concept and the similar reference concept are depicted on a display for classifying the at least one uncoded concept.

Abstract: A system and method for providing a classification suggestion for electronically stored information is provided. A corpus of electronically stored information including reference electronically stored information items each associated with a classification and uncoded electronically stored information items are maintained. A cluster of uncoded electronically stored information items and reference electronically stored information items is provided. A neighborhood of reference electronically stored information items in the cluster is determined for at least one of the uncoded electronically stored information items. A classification of the neighborhood is determined using a classifier. The classification of the neighborhood is suggested as a classification for the at least one uncoded electronically stored information item.

Abstract: A system and method for providing generating reference sets for use during document review is provided. A collection of unclassified documents is obtained. Selection criteria are applied to the document collection and those unclassified documents that satisfy the selection criteria are selected as reference set candidates. A classification code is assigned to each reference set candidate. A reference set is formed from the classified reference set candidates. The reference set is quality controlled and shared between one or more users.

Abstract: A system and for providing reference documents as a suggestion for classifying uncoded documents is provided. Reference electronically stored information items and a set of uncoded electronically stored information items are designated. Each of the reference information items are previously classified. At least one uncoded electronically stored information item is compared with the reference electronically stored information items. One or more of the reference electronically stored information items similar to the at least one uncoded electronically stored information items are identified. Relationships are depicted between the at least one uncoded electronically stored information item and the similar reference electronically stored information items for classifying the at least one uncoded electronically stored information item.

Abstract: A system and for providing reference documents as a suggestion for classifying uncoded documents is provided. A reference set of electronically stored information items, each associated with a classification code, is designated. Clusters of uncoded electronically stored information items are designated. One or more of the uncoded electronically stored information items from at least one cluster is compared to the reference set. At least one of the electronically stored information items in the reference set is identified as similar to the one or more uncoded electronically stored information items. The similar electronically stored information items are injected into the at least one cluster. Relationships are visually depicted between the uncoded electronically stored information items and the similar electronically stored information items in the at least one cluster as suggestions for classifying the uncoded electronically stored information items.

Abstract: A system and method for providing a classification suggestion for concepts is provided. A corpus of concepts including reference concepts each associated with a classification and uncoded concepts are maintained. A cluster of uncoded concepts and reference concepts is provided. A neighborhood of reference concepts in the cluster is determined for at least one of the uncoded concepts. A classification of the neighborhood is determined using a classifier. The classification of the neighborhood is suggested as a classification for the at least one uncoded concept.

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 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 from the user for classification as the responsive documents.