Following this tradition, many researchers recognize their usefulness in the description of language - - even if they do not agree on their significance . However, a weak or strong commitment to this notion does not elude the fact that it proves to be very difficult to settle on a finite set of labels along with their formal definitions. The dilemma resulting from this challenge is well known: to require a univocal identification by each role results in an increase in their number while to abstract their semantic content gives rise to an inconsistent set. ...
Since it’s standardization by the OMG (Object Management Group) in November 1997,
the Unified Modeling Language (UML) has had a tremendous impact on how software
systems are developed. The role of modeling in specifying and documenting complex
software systems is being accepted, and an industrial approach to software engineering
is on its way to becoming reality.
This module provides students with an introduction to the Microsoft Solutions
Framework (MSF) Team Model, including the team goals for success, team
roles of the model, how to scale the model for small or large projects, principles
of a successful team, and how to apply the model to different types of projects.
.Advance Praise for Pricing, Risk, and Performance Measurement in Practice
“The book represents a fresh and innovative departure from ‘traditional’ approaches to modelling of securities data. Subsequently, it also presents much more flexible ways to analyze and process the data. Even if you are not involved with re-architecting an organization’s master data handling, there are numerous ideas, principles, and nuggets that make it a worthwhile read.” –Dr.
This book demonstrates applications and case studies performed by experts for professionals and students in the field of technology, engineering, materials, decision making management and other industries in which mathematical modelling plays a role. Each chapter discusses an example and these are ranging from well-known standards to novelty applications. Models are developed and analysed in details, authors carefully consider the procedure for constructing a mathematical replacement of phenomenon under consideration. ...
AUDITING IN THE DATA PROCESSING ENVIRONMENT — THE EVOLVING ROLE OF THE INTERNAL AUDITOR The final panel leaves the NELS data, reporting models for high school completion
rates of the cohort entering 9th grade in the fall of 1993. Data on this outcome come from a
district-level compilation of four years of CCD data.
While wood and to some extent charcoal are the most common solid fuels used in
developing countries, China and Mongolia have high household prevalence of coal,
especially for heating in open portable space heaters, some with and some without
chimney. Mestl et al. (2006), based on data from the China 2000 Population Census,
report that about 60 percent of rural households used biomass as primary cooking fuel.
Nearly 30 percent of rural households used coal as the primary fuel. Mestl et al model
annual average population weighted exposure (PWE) to indoor air pollution by...
Modelling methods are now well established in physical, biomedical and engineering sciences; and are widely used in assisting the interpretation of experimental data and increasingly in a predictive mode. Applications to inorganic materials are widespread, and indeed, such methods now play a major role in modelling structures, properties and reactivities of these materials.
Experience idea "Using and managing role play in classroom" is to give the students an opportunity to work with others in determining how an individual or group might behave in response to a particular situation. Role playing is often used primarily to promote classroom discussion. The use of role playing as a cooperative learning model also includes class discussion as a vital step, but in this approach the entire class is involved in preparing and presenting role plays through group activity.
In the method of creating digital terrain model (DTM) by using digital photogrammetry, the picket sampling interval (PSI) plays an important role since it strongly influences on the production effectiveness and on the accuracy of created DTMs. The optimal value of PSI must be balanced between requirements of effectiveness and of accuracy. This research is focused on the influence of PSI on root mean square error (RMSE) of created DTM and on the number of error pickets (caused by limitation of image matching technique) that must be checked and corrected manually.
In predicate-argument structure analysis, it is important to capture non-local dependencies among arguments and interdependencies between the sense of a predicate and the semantic roles of its arguments. However, no existing approach explicitly handles both non-local dependencies and semantic dependencies between predicates and arguments.
We study the issue of porting a known NLP method to a language with little existing NLP resources, speciﬁcally Hebrew SVM-based chunking. We introduce two SVM-based methods – Model Tampering and Anchored Learning. These allow ﬁne grained analysis of the learned SVM models, which provides guidance to identify errors in the training corpus, distinguish the role and interaction of lexical features and eventually construct a model with ∼10% error reduction.
We introduce two Bayesian models for unsupervised semantic role labeling (SRL) task. The models treat SRL as clustering of syntactic signatures of arguments with clusters corresponding to semantic roles. The ﬁrst model induces these clusterings independently for each predicate, exploiting the Chinese Restaurant Process (CRP) as a prior. In a more reﬁned hierarchical model, we inject the intuition that the clusterings are similar across different predicates, even though they are not necessarily identical.
The mammalian natriuretic peptide system, consisting of at least three
ligands and three receptors, plays critical roles in health and disease. Exam-ination of genetically engineered animal models has suggested the signifi-cance of the natriuretic peptide system in cardiovascular, renal and skeletal
One goal of natural language generation is to produce coherent text that presents information in a logical order. In this paper, we show that topological ﬁelds, which model high-level clausal structure, are an important component of local coherence in German. First, we show in a sentence ordering experiment that topological ﬁeld information improves the entity grid model of Barzilay and Lapata (2008) more than grammatical role and simple clausal order information do, particularly when manual annotations of this information are not available. ...
Most supervised language processing systems show a signiﬁcant drop-off in performance when they are tested on text that comes from a domain signiﬁcantly different from the domain of the training data. Semantic role labeling techniques are typically trained on newswire text, and in tests their performance on ﬁction is as much as 19% worse than their performance on newswire text. We investigate techniques for building open-domain semantic role labeling systems that approach the ideal of a train-once, use-anywhere system. ...
Lexicalized reordering models play a crucial role in phrase-based translation systems. They are usually learned from the word-aligned bilingual corpus by examining the reordering relations of adjacent phrases. Instead of just checking whether there is one phrase adjacent to a given phrase, we argue that it is important to take the number of adjacent phrases into account for better estimations of reordering models. We propose to use a structure named reordering graph, which represents all phrase segmentations of a sentence pair, to learn lexicalized reordering models efﬁciently. ...
We investigate hierarchical graphical models (HGMs) for automatically detecting decisions in multi-party discussions. Several types of dialogue act (DA) are distinguished on the basis of their roles in formulating decisions. HGMs enable us to model dependencies between observed features of discussions, decision DAs, and subdialogues that result in a decision. For the task of detecting decision regions, an HGM classiﬁer was found to outperform non-hierarchical graphical models and support vector machines, raising the F1-score to 0.80 from 0.55.