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.

Input: Consider Input: So-called combined approaches answer a conjunctive query over a description logic ontology in three steps: first, they materialise certain consequences of the ontology and the data; second, they evaluate the query over the data; and third, they filter the result of the second phase to eliminate unsound answers. Such approaches were developed for various members of the DL-Lite and the EL families of languages, but none of them can handle ontologies containing nominals. In our work, we bridge this gap and present a combined query answering approach for ELHO a logic that contains all features of the OWL 2 EL standard apart from transitive roles and complex role inclusions. This extension is nontrivial because nominals require equality reasoning, which introduces complexity into the first and the third step. Our empirical evaluation suggests that our technique is suitable for practical application, and so it provides a practical basis for conjunctive query answering in a large fragment of OWL 2 EL.

Output: Introducing Nominals to the Combined Query Answering Approaches for EL

Input: Consider 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 Otalora, closely followed by Alfonso de Valdes. The method states that not certain attribution can be made with the given corpus.

Output: The Life of Lazarillo de Tormes and of His Machine Learning Adversities

Input: Consider Input: The goal of semi-supervised learning methods is to effectively combine labeled and unlabeled data to arrive at a better model. Many methods rely on graph-based approaches, where labels are propagated through a graph over the input examples. In most current methods, the propagation mechanism underlying the learning objective is based on random walks. While theoretically elegant, random walks suffer from several drawbacks which can hurt predictive performance. In this work, we explore dynamic infection processes as an alternative propagation mechanism. In these, unlabeled nodes can be "infected" with the label of their already infected neighbors. We provide an efficient, scalable, and parallelizable algorithm for estimating the expected infection outcomes. We also describe an optimization view of the method, relating it to Laplacian approaches. Finally, experiments demonstrate that the method is highly competitive across multiple benchmarks and for various learning settings.
Output: Semi-Supervised Learning with Competitive Infection Models