Despite much recent progress on accurate semantic role labeling, previous work has largely used independent classifiers, possibly combined with separate label sequence models via Viterbi decoding. This stands in stark contrast to the linguistic observation that a core argument frame is a joint structure, with strong dependencies between arguments. We show how to build a joint model of argument ...

We present the methodology that underlies new metrics for semantic machine translation evaluation that we are developing. Unlike widely-used lexical and n-gram based MT evaluation metrics, the aim of semantic MT evaluation is to measure the utility of translations. We discuss the design of empirical studies to evaluate the utility of machine translation output by assessing the accuracy for key ...

Modern information systems interact with a wide variety of users ranging from people with specific roles in business processes to end-users who access information in various ways and in different environments. Therefore, an application has to adhere to a well defined security policy on one hand and be highly adaptable to context on the other. We have extended the OM data model, with its rich su...

Semantic Role Labeling (SRL) has been used successfully in several stages of automated Question Answering (QA) systems but its inherent slow procedures make it difficult to use at the indexing stage of the document retrieval component. In this paper we confirm the intuition that SRL at indexing stage improves the performance of QA and propose a simplified technique named the Question Prediction...

After the RBAC model formalized in 1992 by David Ferraiolo and Rick Kuhn, the models of organization authorization have been developing fast. Among these models, the one based on position network will be used widely and has a prospective future. Algorithms for single-layer model and multi-layer model based on position network were cited in this article. Meanwhile an algorithm example was given ...

One of the most widespread framework for the management of access-control policies is Administrative Role Based Access Control (ARBAC). Several automated analysis techniques have been proposed to help maintaining desirable security properties of ARBAC policies. One limitation of many available techniques is that the sets of users and roles are bounded. In this paper, we propose a symbolic frame...

Access control technology protects the cloud from being accessed illegally. However, traditional access control method cannot meet the new demands of the cloud environment. In order to improve the deficiency of the current multi domain access control method in timeliness and flexibility. This paper puts forward a dynamic access control policy on the basis of task driving mechanism. The new meth...

Semantic Role Labeling is a task in Natural Language Processing often carried out through annotated corpus. So far, there is no available corpus of Portuguese annotated with semantic role labels. This paper reports the annotation of a Brazilian Portuguese corpus following Propbank guidelines. This is the first step of a larger annotation effort and aims to pave the way for a distributed annotat...

What is the impact of surprise and anticipated policy changes when agents form expectations using adaptive learning rather than rational expectations? We examine this issue using the standard stochastic real business cycle model with lump-sum taxes. Agents combine knowledge about future policy with econometric forecasts of future wages and interest rates. Both permanent and temporary policy cha...

Modality inconsistency is one of the security policy evaluation challenges, which arises because of the existence of both positive and negative authorizations for a given subject-object pair. An inconsistency analysis model is needed to discover inconsistency based on the inheritance relationship between concepts and resolved it by using predefined resolution rules. Previous studies handle moda...