n addition to the MicrosoftÆ Solutions Framework (MSF) Process Model for
Application Development, the MSF Application Model is used when designing
business solutions. As you will learn in this module, the application model
provides for a layered, services-based approach to designing applications.Microsoft Official Curriculum (MOC), available to IT Academies at a discounted price, is professional courseware intended for IT professionals and developers who build, support, and implement solutions by using Microsoft products and technologies.
For the task of automatic treebank conversion, this paper presents a feature-based approach which encodes bracketing structures in a treebank into features to guide the conversion of this treebank to a different standard. Experiments on two Chinese treebanks show that our approach improves conversion accuracy by 1.31% over a strong baseline.
For each of the sentences in the text, they provided a ranking of how important that sentence is with respect to the content of the text, on an integer scale from 1 (not important) to 7 (very important). The approaches we evaluated are a simple paragraph-based approach that serves as a baseline, two word-based algorithms, and two coherencebased approaches1.
Taking this route sets up a dual goal: (a) from the generic paraphrasing perspective - an objective evaluation of paraphrase acquisition performance on a concrete application dataset, as well as identifying the additional mechanisms needed to match paraphrases in texts; (b) from the RE perspective investigating the feasibility and performance of a generic paraphrase-based approach for RE. Our conﬁguration assumes a set of entailing templates (non-symmetric “paraphrases”) for the target relation.
Based on the theoretical and practical research, the dissertation recommends the solutions to develop the teaching staff of Hung Yen University in a competency-based approach in order to improve the professional competence for them, aiming at “standardizing and modernizing” the teaching staff at universities of technical education to meet the requirement of basic and comprehensive renovation of those universities.
On a multi-dimensional text categorization task, we compare the effectiveness of a feature based approach with the use of a stateof-the-art sequential learning technique that has proven successful for tasks such as “email act classification”. Our evaluation demonstrates for the three separate dimensions of a well established annotation scheme that novel thread based features have a greater and more consistent impact on classification performance.
Importance evaluation is one of the most challenging problems in the field of text processing. In the paper we focus on the notion of importance from a computational standpoint, and we propose a procedural, rule-based approach to importance evaluation. T h i s novel approach is supported by a prototype experimental system, called importance evaluator, that can deal with descriptive texts taken from computer science l i t e r a t u r e on operating systems. The evaluator relies on a set of importance rules that are used to assign importance values to the different parts...
This paper focuses on risk analysis and safety aspects of coastal flood defences in Vietnam. The sea dike system has been actually designed by a 20 to 25 years return period. From the current situation it seems that the dike system is not sufficient to withstand the actual sea boundary condition. Risk based approach for safety standard of coastal flood defences in Vietnam
This book provides physiotherapists and exercise professionals with a comprehensive resource on the exercise components and skills of constructing and teaching CR exercise. It addresses the scope of knowledge and skills required by exercise specialists developing, delivering and teaching exercise based CR programmes. It has an evidence-based framework, a
Long distance word reordering is a major challenge in statistical machine translation research. Previous work has shown using source syntactic trees is an effective way to tackle this problem between two languages with substantial word order difference. In this work, we further extend this line of exploration and propose a novel but simple approach, which utilizes a ranking model based on word order precedence in the target language to reposition nodes in the syntactic parse tree of a source sentence....
We propose a novel approach to translating from a morphologically complex language. Unlike previous research, which has targeted word inﬂections and concatenations, we focus on the pairwise relationship between morphologically related words, which we treat as potential paraphrases and handle using paraphrasing techniques at the word, phrase, and sentence level.
We propose a new method for query-oriented extractive multi-document summarization. To enrich the information need representation of a given query, we build a co-occurrence graph to obtain words that augment the original query terms. We then formulate the summarization problem as a Maximum Coverage Problem with Knapsack Constraints based on word pairs rather than single words.
This paper considers the problem of automatic assessment of local coherence. We present a novel entity-based representation of discourse which is inspired by Centering Theory and can be computed automatically from raw text. We view coherence assessment as a ranking learning problem and show that the proposed discourse representation supports the effective learning of a ranking function. Our experiments demonstrate that the induced model achieves signiﬁcantly higher accuracy than a state-of-the-art coherence model. ...
Update summarization is a new challenge in multi-document summarization focusing on summarizing a set of recent documents relatively to another set of earlier documents. We present an unsupervised probabilistic approach to model novelty in a document collection and apply it to the generation of update summaries. The new model, called D UAL S UM, results in the second or third position in terms of the ROUGE metrics when tuned for previous TAC competitions and tested on TAC-2011, being statistically indistinguishable from the winning system.
Relation extraction is the task of finding semantic relations between two entities from text. In this paper, we propose a novel feature-based Chinese relation extraction approach that explicitly defines and explores nine positional structures between two entities. We also suggest some correction and inference mechanisms based on relation hierarchy and co-reference information etc. The approach is effective when evaluated on the ACE 2005 Chinese data set.
While the generative view of language processing builds bigger units out of smaller ones by means of rewriting steps, the axiomatic view eliminates invalid linguistic structures out of a set of possible structures by means of wellformedness principles. We present a generator based on the axiomatic view and argue that when combined with a TAG-like grammar and a ﬂat semantics, this axiomatic view permits avoiding drawbacks known to hold either of top-down or of bottom-up generators.
We present conditions under which verb phrases are elided based on a corpus of positive and negative examples. Factor that affect verb phrase ellipsis include: the distance between antecedent and ellipsis site, the syntactic relation between antecedent and ellipsis site, and the presence or absence of adjuncts. Building on these results, we examine where in the generation architecture a trainable algorithm for VP ellipsis should be located.
In this paper, we present a new approach for word sense disambiguation (WSD) using an exemplar-based learning algorithm. This approach integrates a diverse set of knowledge sources to disambiguate word sense, including part of speech of neighboring words, morphological form, the unordered set of surrounding words, local collocations, and verb-object syntactic relation. We tested our WSD program, named LEXAS, on both a common data set used in previous work, as well as on a large sense-tagged corpus that we separately constructed. ...