Textual entailment recognition plays a fundamental role in tasks that require indepth natural language understanding. In order to use entailment recognition technologies for real-world applications, a large-scale entailment knowledge base is indispensable. This paper proposes a conditional

There have been major advances on automatically constructing large knowledge bases by extracting relational facts from Web and text sources. However, the world is dynamic: periodic events like sports competitions need to be interpreted with their respective timepoints, and facts such as coaching a

April 29, 2011Für UnsShe had never before seen a rabbit with either a waistcoat-pocket, or a watch to take out of it, and burning with curiosity, she ran across the field after it Lewis CarrollThe following document, written under the supervision of Dr. reviewed by:

of all the items were examined qualitatively based on their actual occurrences in context. A single linguistic form such as above, for example, can express meaning in the real world and for research activities not for navigating readers in the research articles. Such an ambiguity leads to the difficulty

) different query formulation methods for retrieving contextualization candidates and (2) ranking methods taking into account topical and temporal relevance as well as complementarity with respect to the original text. We evaluate our proposed approaches through extensive ex-periments using real-world

Abstract—Socially aware services often have a large user base and data of users have to be partitioned and replicated over multiple geographically distributed clouds. Choosing in which cloud to place data, however, is difficult. Effective data placements entail meeting multiple system objectives

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parameters will affect the brake time-points in each test case as well as the residual velocity in case of a collision with a target vehicle. Method: A formal model using a graph-based representation of the allowed variances based on relevant time-points allows the selection of relevant trajectories as test

There is a growing need for methods that can represent and query uncertain graphs. These uncertain graphs are often the result of an information extraction and integration system that attempts to extract an entity graph or a knowledge graph from multiple unstructured sources [25], [7

of scalability and maintainability. Hence, different approaches are based on Peer-to-Peer (P2P) technology. In particular, fast-paced NVEs stress these systems and most likely cause high overlay maintenance overhead. This Master’s Thesis presents a novel approach to spatial Publish/Subscribe (Pub/Sub) in P2P