In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

Example Input: In many combinatorial problems one may need to model the diversity or similarity of sets of assignments. For example, one may wish to maximise or minimise the number of distinct values in a solution. To formulate problems of this type we can use soft variants of the well known AllDifferent and AllEqual constraints. We present a taxonomy of six soft global constraints, generated by combining the two latter ones and the two standard cost functions, which are either maximised or minimised. We characterise the complexity of achieving arc and bounds consistency on these constraints, resolving those cases for which NP-hardness was neither proven nor disproven. In particular, we explore in depth the constraint ensuring that at least k pairs of variables have a common value. We show that achieving arc consistency is NP-hard, however bounds consistency can be achieved in polynomial time through dynamic programming. Moreover, we show that the maximum number of pairs of equal variables can be approximated by a factor of 12 with a linear time greedy algorithm. Finally, we provide a fixed parameter tractable algorithm with respect to the number of values appearing in more than two distinct domains. Interestingly, this taxonomy shows that enforcing equality is harder than enforcing difference.
Example Output: Soft Constraints of Difference and Equality

Example Input: Summit work of the Spanish Golden Age and forefather of the so-called picaresque novel, The Life of Lazarillo de Tormes and of His Fortunes and Adversities still remains an anonymous text. Although distinguished scholars have tried to attribute it to different authors based on a variety of criteria, a consensus has yet to be reached. The list of candidates is long and not all of them enjoy the same support within the scholarly community. Analyzing their works from a data-driven perspective and applying machine learning techniques for style and text fingerprinting, we shed light on the authorship of the Lazarillo. As in a state-of-the-art survey, we discuss the methods used and how they perform in our specific case. According to our methodology, the most likely author seems to be Juan Arce de Otálora, closely followed by Alfonso de Valdés. The method states that not certain attribution can be made with the given corpus.
Example Output: The Life of Lazarillo de Tormes and of His Machine Learning Adversities

Example Input: The work presented here involves the design of a Multi Layer Perceptron (MLP) based pattern classifier for recognition of handwritten Bangla digits using a 76 element feature vector. Bangla is the second most popular script and language in the Indian subcontinent and the fifth most popular language in the world. The feature set developed for representing handwritten Bangla numerals here includes 24 shadow features, 16 centroid features and 36 longest-run features. On experimentation with a database of 6000 samples, the technique yields an average recognition rate of 96.67% evaluated after three-fold cross validation of results. It is useful for applications related to OCR of handwritten Bangla Digit and can also be extended to include OCR of handwritten characters of Bangla alphabet.
Example Output:
An MLP based Approach for Recognition of Handwritten ‘Bangla’ Numerals