Abstract: A method of implementing a graphical user interface to collect information from a user is provided. The method includes (i) dynamically displaying, by the graphical user interface, K>1 groupings of M>1 documents from a catalog of documents in an embedding space, wherein a distance between each pair of the documents in the embedding space corresponds to a predetermined measure of dissimilarity between the pair of documents, and the K groupings are formed using K-medoid clustering analysis, (ii) receiving a user selection of one grouping of the K groupings, (iii) dynamically displaying a predetermined number P>0 documents of the cluster which corresponds to the selected grouping, (iv) receiving user feedback with respect to one of the Pk documents of the selected grouping, (v) and dynamically displaying an identified subsequent document from the selected grouping in dependence on the set of liked documents and the set of disliked documents.

Abstract: A method for identifying a desired document is provided to include forming K clusters of documents and, for each cluster: for each respective document of the cluster determining a sum of distances between (i) the respective document and (ii) each of the other documents of the cluster; and identifying a medoid document of the cluster as the document of the cluster having the smallest sum of determined distances of all of the documents of the cluster. The method also includes selecting M representative documents for each cluster, identifying for dynamic display toward the user K groupings of documents, wherein each of the K groupings of documents identifies the selected M representative documents of a corresponding cluster, and, in response to user selection of one of the K groupings of documents, identifying for dynamic display toward the user P documents of the cluster that corresponds to the selected grouping.

Abstract: A method for identifying a desired document is provided to include forming K clusters of documents and, for each cluster: for each respective document of the cluster determining a sum of distances between (i) the respective document and (ii) each of the other documents of the cluster; and identifying a medoid document of the cluster as the document of the cluster having the smallest sum of determined distances of all of the documents of the cluster. The method also includes selecting M representative documents for each cluster, identifying for dynamic display toward the user K groupings of documents, wherein each of the K groupings of documents identifies the selected M representative documents of a corresponding cluster, and, in response to user selection of one of the K groupings of documents, identifying for dynamic display toward the user P documents of the cluster that corresponds to the selected grouping.