… Thus we have a disjoint partitioning of our training documents into a labeled set and an …
The sum of class memberships of a document over all classes is assumed to be one. Possible …

… text from unlabelled documents. Specifically, our objective is to separate a set of unlabelled
documents in two classes: … Then, it proceeds making the clusters disjoint. To this extent a …

… documents, with means other than a search function or a handful of metadata elements. The
type of tool we develop is a text … The result is a complete segmentation into disjoint thematic …

… -label TC; the former involves disjoint categories (ie, each document is assigned to a single
… • For every class, we compare the document graph with the corresponding class graph to …

… Keyword extraction enables us to represent text documents … Text classification is an important
subfield of text mining which assigns a text document into one or more predefined classes …

… separate the textual corpus into disjoint document groups. … Owing to imbalanced and
overlapping classes, we … those documents belonging to only one of the largest classes. …

… through overlapping and disjointed clustering solutions. … sub-documents related to similar
classes in each text unit [25]. First, a text unit includes same number of clusters as to classes, …

… sort information included in the text documents.It is known that … that these classes are not
disjoint (equivalence classes), but … tolerance classes of terms and document clusters when new …

… (disjoint) contours. If these two pixels are separated by a black pixel q between them, the two
disjoint … , since hand-written documents belonging to the same script class may show wide …

… multi-class classification. In multilabel case each document can belong to several classes, ie
… In this subproblem all samples from the multi-label training set are divided into two disjoint …