of opinionated content has a positive or a negative connotation. Research on determining whether a term is indeed a marker of opinionated content (a subjective term) or not (an objective term) has been, instead, much more scarce. In this work we describe SENTIWORDNET, a lexical resource in which each WORDNET

-to-end reliability definitions and solutions are inapplicable in the WSN regime and would only lead to a waste of scarce sensor resources. Hence, the WSN paradigm necessitates a collective event-to-sink reliability notion rather than the traditional end-to-end notion. To the best of our knowledge, reliable transport

protocol for sensor networks where the resources of each node are scarce. Theoretical analysis, simulation experiments and a real implementation on Berkeley motes are provided to validate our claims.

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Discriminative learning methods are widely used in natural language processing. These methods work best when their training and test data are drawn from the same distribution. For many NLP tasks, however, we are confronted with new domains in which labeled data is scarce or non

suitable mixture of individualistic and collective behaviour. Up to now, panics as a particular form of collective behaviour occuring in situations of scarce or dwindling resources1,6 has been mainly studied from the perspective of social psychology. 7−9 Panicking individuals tend to show maladaptive

Current corpus-based machine translation techniques do not work very well when given scarce linguistic resources. To examine the gap between human and machine translators, we created an experiment in which human beings were asked to translate an unknown language into English on the sole basis of a

on semantically typed data, tailoring content to the specific constraints of the client. We instantiate our design principles in a proxy architecture that further exploits typed data to enable application-level management of scarce network resources. Our proxy architecture generalizes previous work addressing all

The “tragedy of the commons ” metaphor helps explain why people overuse shared resources. However, the recent proliferation of intellectual property rights in biomedical research suggests a different tragedy, an “anticommons ” in which people underuse scarce resources because too many owners can

This paper concerns the problem of optimally allocating a scarce indivisible resource among a target population based on experimental data for a sample drawn from this population. For a wide class of social welfare functions, the problem can be set up as a mathematical program with estimated