Cloud Computing provides a appropriate on-demand network access to a shared pool of configurable computing resources which could be rapidly deployed with much more great efficiency and with minimal overhead to management. This paper deals with the secure outsourcing of nonlinear programming. It provides a practical mechanism design which fulfils input/output privacy, cheating resilience, and ef...

We are currently observing a plethora of Natural Language Processing tools and services being made available. Each of the tools and services has its particular strengths and weaknesses, but exploiting the strengths and synergistically combining different tools is currently an extremely cumbersome and time consuming task. Also, once a particular set of tools is integrated this integration is not...

Natural Language Processing (NLP) has been active in the medical domain for more than thirty years, with pioneering projects such as the Linguistic String Project. ‘BioNLP’, the application of Natural Language Processing methods to the analysis of the biological literature in the genomics era, has undergone a fast development in little over ten years.1 It rapidly attracted Medical NLP and Compu...

Research within a larger, multi-faceted risk assessment project for the Intelligence Community (IC) combines Natural Language Processing (NLP) and Machine Learning techniques to detect potentially malicious shifts in the semantic content of information either accessed or produced by insiders within an organization. Our hypothesis is that the use of fewer, more discriminative linguistic features...

Joint inference approaches such as Integer Linear Programming (ILP) and Markov Logic Networks (MLNs) have recently been successfully applied to many natural language processing (NLP) tasks, often outperforming their pipeline counterparts. However, MLNs are arguably much less popular among NLP researchers than ILP. While NLP researchers who desire to employ these joint inference frameworks do no...

The purpose of this paper is to outline the requirements that the eld of Natural Language Processing (NLP) has for a declarative successor to Prolog. Logic programming approaches play a major role in NLP, and likewise considerations of NLP have had a strong in uence on logic programming ([Colmerauer, 1978], [Pereira and Warren, 1980], [Smolka, 1992]). We will review the state of the art in NL g...

Many natural language processing (NLP) tools exhibit a decrease in performance when they are applied to data that is linguistically different from the corpus used during development. This makes it hard to develop NLP tools for domains for which annotated corpora are not available. This paper explores a number of metrics that attempt to predict the cross-domain performance of an NLP tool through...

The goal of this contribution is to systematically investigate the possibilities of integrating concepts related to natural language processing (NLP) in Ambient Intelligence (AmI). Both research fields have been rapidly growing and evolving over recent years, substantially influencing the development of Computer Science as a whole. However, they are far from being sufficiently integrated yet. U...

Neuropeptides have central roles in the regulation of homoeostatic behaviours such as sleep and feeding. Caenorhabditis elegans displays sleep-like quiescence of locomotion and feeding during a larval transition stage called lethargus and feeds during active larval and adult stages. Here we show that the neuropeptide NLP-22 is a regulator of Caenorhabditis elegans sleep-like quiescence observed...

Language learning is a relatively new application for natural language processing (NLP) and for intelligent tutoring and learning environments (ITLEs). NLP has a crucial role to play in foreign language ITLEs, whether they are designed for explicit or implicit learning of the vocabulary and grammar. FLUENT is an implicit approach, in which NLP and sharedcontrol animation support a two-medium co...