Abstract: A computer-implemented system and method for identifying relevant documents is provided. A set of documents each associated with one or more concepts is identified. At least a portion of the documents in the set are clustered based on the concepts. A matrix that provides a summary of the documents most relevant to one such concept is generated by determining for each document a measure of similarity between a concept frequency occurrence and concept weights of each cluster. The matrix is populated with the calculated measures of similarity. Those documents associated with a threshold measure of similarity are identified as the most relevant documents to one such concept.

Abstract: A computer-implemented system and method for forming document clusters for display is provided. Concepts are identified from a set of documents and a subset of the documents that include those concepts with frequencies of occurrence that occur within a range of concept frequencies are selected from the set. The documents in the subset are assigned to clusters. Each cluster includes a center and a radius, and is placed into a display with the center of that cluster at a fixed distance from the common origin. A portion of the placed clusters are further placed along a common vector.

Abstract: A computer-implemented system and method for generating document groupings is provided. A lexicon of terms extracted from a set of documents is generated. The lexicon includes a frequency of each extracted term within each document in the set. Concepts each having two or more of the extracted terms are generated. A subset of the documents in the set is selected based on the term frequencies. The subset of documents is grouped into clusters based on the concepts. A similarity of each document cluster is calculated with one or more documents based on a distance by summing the frequency of each term in that document and a weight of the cluster for each of the terms. The weights are updated until a rate of change for each cluster becomes constant.

Abstract: A computer-implemented system and method for generating clusters for placement into a display is provided. A set of clusters is generated from a document set. A single cluster of related documents from the document set is obtained and at least one new cluster is added. One such document in the set is compared to the cluster. A difference in distance between the document and a common origin and the cluster and the common origin is determined. The document is designated as the new cluster when the difference fails to satisfy a predetermined threshold. One or more cluster spines each having two or more clusters placed along a vector are placed into a display. The clusters along each spine are identified as similar and the clusters of one such spine are also similar to further clusters located along a further spine having a small cosine rotation from that cluster spine.

Abstract: A computer-implemented system and method for generating clusters for placement into a display is provided. A set of clusters is generated from a document set. A single cluster of related documents from the document set is obtained and at least one new cluster is added. One such document in the set is compared to the cluster. A difference in distance between the document and a common origin and the cluster and the common origin is determined. The document is designated as the new cluster when the difference fails to satisfy a predetermined threshold. One or more cluster spines each having two or more clusters placed along a vector are placed into a display. The clusters along each spine are identified as similar and the clusters of one such spine are also similar to further clusters located along a further spine having a small cosine rotation from that cluster spine.

Abstract: A computer-implemented system and method for generating document groupings is provided. A lexicon of terms extracted from a set of documents is generated. The lexicon includes a frequency of each extracted term within each document in the set. Concepts each having two or more of the extracted terms are generated. A subset of the documents in the set is selected based on the term frequencies. The subset of documents is grouped into clusters based on the concepts. A similarity of each document cluster is calculated with one or more documents based on a distance by summing the frequency of each term in that document and a weight of the cluster for each of the terms. The weights are updated until a rate of change for each cluster becomes constant.

Abstract: A computer-implemented system and method for populating clusters of documents is provided. A set of clusters is placed in a display in relation to a common origin. One of a plurality of unclustered documents in the display is selected and an angle ? of the document from the common origin is determined. An angle ? of the cluster relative to the common origin is computed for each cluster. A difference is determined between the document angle ? and one such cluster angle ?. A predetermined variance is applied to the difference. The document is placed into the cluster when the difference is less than the variance.

Abstract: A computer-implemented system and method for identifying relevant documents for display are provided. Themes for a set of documents are generated. The documents are clustered based on the themes. A matrix including an inner product of document frequency occurrences and cluster concept weightings for each theme is generated for the documents. From the matrix, documents most relevant to a particular theme are identified, and the relevant documents are displayed.

Abstract: A computer-implemented system and method for identifying relevant documents for display are provided. Themes for a set of documents are generated. The documents are clustered based on the themes. A matrix including an inner product of document frequency occurrences and cluster concept weightings for each theme is generated for the documents. From the matrix, documents most relevant to a particular theme are identified, and the relevant documents are displayed.

Abstract: A computer-implemented system and method for correcting a rendering of clusters is provided. A pair of clusters is selected within a representation. A span between centers of the clusters is determined. Radii for each of the clusters in the pair is identified. The radii are summed and at least one of the clusters in the pair is moved within the representation when the span exceeds the sum.

Abstract: A computer-implemented system and method for populating clusters of documents is provided. A set of clusters is placed in a display in relation to a common origin. One of a plurality of unclustered documents in the display is selected and an angle ? of the document from the common origin is determined. An angle ? of the cluster relative to the common origin is computed for each cluster. A difference is determined between the document angle ? and one such cluster angle ?. A predetermined variance is applied to the difference. The document is placed into the cluster when the difference is less than the variance.

Abstract: A computer-implemented system and method for clustering similar documents is provided. Concepts are identified for a set of documents and occurrence frequencies are determined for each concept in the documents set. A distance quantifying a similarity for each of the documents in the set with one or more clusters of documents is calculated. Each document is mapped to at least one of the one or more document clusters.

Abstract: A computer-implemented system and method for generating a display of document clusters is described. Clusters of documents are presented in a multi-dimensional concept space. At least one document is selected from a collection of documents to be clusters. An angle ? of the document relative to a common origin of the multi-dimensional concept space is computed. The selected document is compared with each of the clusters. An angle ? from the common origin is determined for each cluster. A difference between the angle ? for the document and the angle ? for the cluster is determined. The difference is compared to the variance, and a new cluster is created when the difference exceeds the variance for all the clusters.

Abstract: A system and method for reorienting a display of clusters is provided. Clusters are maintained within a display. Each cluster includes a center located at a distance relative to a common origin for the display. A location of each cluster is compared to each other cluster. Two or more clusters that overlap are identified. At least one of the overlapping clusters is reoriented until no overlap occurs.

Abstract: A system and method for efficiently generating cluster groupings in a multi-dimensional concept space is described. A plurality of terms is extracted from each document in a collection of stored unstructured documents. A concept space is built over the document collection. Terms substantially correlated between a plurality of documents within the document collection are identified. Each correlated term is expressed as a vector mapped along an angle ? originating from a common axis in the concept space. A difference between the angle ? for each document and an angle ? for each cluster within the concept space is determined. Each such cluster is populated with those documents having such difference between the angle ? for each such document and the angle ? for each such cluster falling within a predetermined variance.

Abstract: A system and method for grouping similar documents is provided. Frequencies of occurrences are determined for terms and noun phrases within a set of documents. A subset of the documents is selected by removing those documents having terms and noun phrases that fall outside a bounded range of upper and lower conditions for frequency of occurrence. Each of the documents in the subset is mapped to a cluster of documents based on a similarity of the documents to the cluster documents.

Abstract: A system and method for grouping similar documents is provided. Frequencies of occurrences are determined for terms and noun phrases within a set of documents. A subset of the documents is selected by removing those documents having terms and noun phrases that fall outside a bounded range of upper and lower conditions for frequency of occurrence. Each of the documents in the subset is mapped to a cluster of documents based on a similarity of the documents to the cluster documents.

Abstract: A system and method for reorienting a display of clusters is provided. Clusters are maintained within a display. Each cluster includes a center located at a distance relative to a common origin for the display. A location of each cluster is compared to each other cluster. Two or more clusters that overlap are identified. At least one of the overlapping clusters is reoriented until no overlap occurs.

Abstract: A system and method for thematically grouping documents into clusters is provided. Concepts are extracted from a plurality of documents. The concepts include nouns or noun phrases. A number of occurrences for each concept are determined within each document. A bounded range is applied to the concepts and a subset of the concepts is selected by removing the concepts that fall outside the bounded range. The bounded range includes upper edge conditions and lower edge conditions. Themes are generated from the subset of concepts by identifying two or more concepts with common semantic meaning. Clusters of the documents are generated based on the themes.

Abstract: A system and method for reorienting clusters within a display is provided. Clusters are maintained within a display. Each cluster includes a center located at a distance relative to a common origin for the display and a radius measured from the center. A pair of the clusters is selected and a bounding region is determined for each cluster in the pair by forming a pair of tangent vectors about the cluster and originating at the common origin. The bounding regions of the clusters in the pair are compared. The distance from the common origin of one of the clusters in the pair is increased upon overlap of the bounding regions as a perspective-corrected distance, which is determined as a function of the distances, the radii, and an angle between tangent vectors. The one cluster is moved to reorient the cluster's center at the perspective-corrected distance in the display.