A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena

Word reordering is one of the most difficult aspects of statistical machine translation (SMT), and an important factor of its quality and efficiency. Despite the vast amount of research published to date, the interest of the community in this problem has not decreased, and no single method appears to be strongly dominant across language pairs. Instead, the choice of the optimal approach for a new translation task still seems to be mostly driven by empirical trials. To orientate the reader in this vast and complex research area, we present a comprehensive survey of word reordering viewed as a statistical modeling challenge and as a natural language phenomenon. The survey describes in detail how word reordering is modeled within different string-based and tree-based SMT frameworks and as a stand-alone task, including systematic overviews of the literature in advanced reordering modeling. We then question why some approaches are more successful than others in different language pairs. We argue that, besides measuring the amount of reordering, it is important to understand which kinds of reordering occur in a given language pair. To this end, we conduct a qualitative analysis of word reordering phenomena in a diverse sample of language pairs, based on a large collection of linguistic knowledge. Empirical results in the SMT literature are shown to support the hypothesis that a few linguistic facts can be very useful to anticipate the reordering characteristics of a language pair and to select the SMT framework that best suits them.Comment: 44 pages, to appear in Computational Linguistic

A comparison framework and review of service brokerage solutions for cloud architectures

Cloud service brokerage has been identified as a key concern for future cloud technology development and research. We compare service brokerage solutions. A range of specific concerns like architecture, programming and quality will be looked at. We apply a 2-pronged classification and comparison framework.We will identify challenges and wider research objectives based on an identification of cloud broker architecture concerns and technical requirements for service brokerage solutions. We will discuss complex cloud architecture concerns such as commoditisation and federation of integrated, vertical cloud stacks

Disambiguation strategies for cross-language information retrieval

This paper gives an overview of tools and methods for Cross-Language Information Retrieval (CLIR) that are developed within the Twenty-One project. The tools and methods are evaluated with the TREC CLIR task document collection using Dutch queries on the English document base. The main issue addressed here is an evaluation of two approaches to disambiguation. The underlying question is whether a lot of effort should be put in finding the correct translation for each query term before searching, or whether searching with more than one possible translation leads to better results? The experimental study suggests that the quality of search methods is more important than the quality of disambiguation methods. Good retrieval methods are able to disambiguate translated queries implicitly during searching

Designing a Software Platform for Evaluating Cyber-Attacks on The Electric PowerGrid

abstract: Energy management system (EMS) is at the heart of the operation and control of a modern electrical grid. Because of economic, safety, and security reasons, access to industrial grade EMS and real-world power system data is extremely limited. Therefore, the ability to simulate an EMS is invaluable in researching the EMS in normal and anomalous operating conditions. I first lay the groundwork for a basic EMS loop simulation in modern power grids and review a class of cybersecurity threats called false data injection (FDI) attacks. Then I propose a software architecture as the basis of software simulation of the EMS loop and explain an actual software platform built using the proposed architecture. I also explain in detail the power analysis libraries used for building the platform with examples and illustrations from the implemented application. Finally, I will use the platform to simulate FDI attacks on two synthetic power system test cases and analyze and visualize the consequences using the capabilities built into the platform.Dissertation/ThesisMasters Thesis Computer Science 201

Treebank-based acquisition of Chinese LFG resources for parsing and generation

This thesis describes a treebank-based approach to automatically acquire robust,wide-coverage Lexical-Functional Grammar (LFG) resources for Chinese parsing and generation, which is part of a larger project on the rapid construction of deep, large-scale, constraint-based, multilingual grammatical resources. I present an application-oriented LFG analysis for Chinese core linguistic phenomena and (in cooperation with PARC) develop a gold-standard dependency-bank of Chinese f-structures for evaluation. Based on the Penn Chinese Treebank, I design and implement two architectures for inducing Chinese LFG resources, one annotation-based and the other dependency conversion-based. I then apply the f-structure acquisition algorithm together with external, state-of-the-art parsers to parsing new text into "proto" f-structures. In order to convert "proto" f-structures into "proper" f-structures or deep dependencies, I present a novel Non-Local Dependency (NLD) recovery algorithm using subcategorisation frames and f-structure paths linking antecedents and traces in NLDs extracted from the automatically-built LFG f-structure treebank. Based on the grammars extracted from the f-structure annotated treebank, I develop a PCFG-based chart generator and a new n-gram based pure dependency generator to realise Chinese sentences from LFG f-structures. The work reported in this thesis is the first effort to scale treebank-based, probabilistic Chinese LFG resources from proof-of-concept research to unrestricted, real text. Although this thesis concentrates on Chinese and LFG, many of the methodologies, e.g. the acquisition of predicate-argument structures, NLD resolution and the PCFG- and dependency n-gram-based generation models, are largely language and formalism independent and should generalise to diverse languages as well as to labelled bilexical dependency representations other than LFG