Do structural patterns tell us something about the text content? In order to give a preliminary answer to this question, an experiment in automatic text classification is performed using only surface-structural features. The features extracted – as, e.g., the complexity, length or depth of text constituents (Köhler, 1999), – produced surprisingly good classification results. This finding argues...

We propose an objective, comprehensive, and complexity independent metric for performance evaluation of graphics/text separation (text segmentation) algorithms. The metric includes a positive set and a negative set of indices, at both the character and the character string (text) levels, and it evaluates the detection accuracy of the location, width, height, orientation, skew, string length, an...

Often we encounter documents with text printed on complex color background. Readability of textual contents in such documents is very poor due to complexity of the background and mix up of color(s) of foreground text with colors of background. Automatic segmentation of foreground text in such document images is very much essential for smooth reading of the document contents either by human or b...

The main text for the course is: Computational Complexity. Christos H. Papadimitriou. Introduction to the Theory of Computation. Michael Sipser. Other useful references include: Computers and Intractability: A guide to the theory of NP-completeness. Michael R. Garey and David S. Johnson. Structural Complexity. Vols I and II. J.L. Balcázar, J. Dı́az and J. Gabarró. Computability and Complexity fr...

Automatic Text Complexity Evaluation (ATE) is a research field that aims at creating new methodologies to make autonomous the process of text complexity evaluation, study text-linguistic features (e.g., lexical, syntactical, morphological) measure grade comprehensibility text. ATE can affect positively several different contexts such as Finance, Health, and Education. Moreover, it support on Si...

Finding a match of an M item pattern against an N item text is a common computing task, useful in string matching and image matching. The best classical (i.e., non-quantum) string matching algorithms, which are Θ(N +M) time and query complexity, are improved in many cases in this paper using Grover’s quantum searching algorithm. Specifically, given quantum oracles that return the j symbol in th...

Text Complexity Analysis is an useful task in Education. For example, it can help teachers select appropriate texts for their students according to their educational level. This task requires the analysis of several text features that people do mostly manually (e.g. syntactic complexity, words variety, etc.). In this paper, we present a tool useful for Complexity Analysis, called Coh-Metrix-Esp...

Across many disciplines, interest is increasing in the use of computational text analysis in the service of social science questions. We survey the spectrum of current methods, which lie on two dimensions: (1) computational and statistical model complexity; and (2) domain assumptions. This comparative perspective suggests directions of research to better align new methods with the goals of soci...