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.

Ex Input:
Levels are a key component of many different video games, and a large body of work has been produced on how to procedurally generate game levels. Recently, Machine Learning techniques have been applied to video game level generation towards the purpose of automatically generating levels that have the properties of the training corpus. Towards that end we have made available a corpora of video game levels in an easy to parse format ideal for different machine learning and other game AI research purposes.

Ex Output:
The VGLC: The Video Game Level Corpus


Ex Input:
The genetic selection of keywords set, the text frequencies of which are considered as attributes in text classification analysis, has been analyzed. The genetic optimization was performed on a set of words, which is the fraction of the frequency dictionary with given frequency limits. The frequency dictionary was formed on the basis of analyzed text array of texts of English fiction. As the fitness function which is minimized by the genetic algorithm, the error of nearest k neighbors classifier was used. The obtained results show high precision and recall of texts classification by authorship categories on the basis of attributes of keywords set which were selected by the genetic algorithm from the frequency dictionary.

Ex Output:
Genetic Optimization of Keywords Subset in the Classification Analysis of Texts Authorship


Ex Input:
This paper discusses a method for im­ plementing a probabilistic inference system based on an extended relational data model. This model provides a unified approach for a variety of applications such as dynamic pro­ gramming, solving sparse linear equations, and constraint propagation. In this frame­ work, the probability model is represented as a generalized relational database. Subse­ quent probabilistic requests can be processed as standard relational queries. Conventional database management systems can be easily adopted for implementing such an approxi­ mate reasoning system.

Ex Output:

A Method for Implementing a Probabilistic Model as a Relational Database