Providing Definitive Learning Direction for Relation Classification System

Deep neural network has adequately revealed its superiority of solving various tasks in Natural Language Processing, especially for relation classification. However, unlike traditional feature-engineering methods that targetedly extract well-designed features for specific task, the diversity of input format for deep learning is limited; word sequence as input is the frequently used setting. Therefore, the input of neural network, to some extent, lacks pertinence. For relation classification task, it is not uncommon that, without specific entity pair, a sentence contains various relation types; therefore, entity pair indicates the distribution of the crucial information in input sentence for recognizing specific relation. Aiming at this characteristic, in this paper, several strategies are proposed to integrate entity pair information into the application of deep learning in relation classification task, in a way to provide definitive learning direction for neural network. Experimental results on the SemEval-2010 Task 8 dataset show that our method outperforms most of the state-of-the-art models, without external linguistic features

Increasing the value of research: a comparison of the literature on critical success factors for projects, IT projects and enterprise resource planning projects

Since the beginning of modern project management in the 1960s, academic researchers have sought to identify a definitive list of Critical Success Factors (CSFs), the key things that project managers must get right in order to deliver a successful product. With the advent of Information Technology (IT) projects and, more recently, projects to deliver Enterprise Resource Planning (ERP) systems, attention has turned to identifying definitive lists of CSFs for these more specific project types. The purpose of this paper is to take stock of this research effort by examining how thinking about each type of project has evolved over time, before producing a consolidated list of CSFs for each as a basis for comparison. This process reveals a high degree of similarity, leading to the conclusion that the goal of identifying a generic list of CSFs for project management has been achieved. Therefore, rather than continuing to describe lists of CSFs, researchers could increase the value of their contribution by taking a step forward and focusing on why, despite this apparent knowledge of how to ensure their success, ERP projects continue to fai

The Pragmatic Turn in Explainable Artificial Intelligence (XAI)

In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will lack a well-defined goal. Aside from providing a clearer objective for XAI, focusing on understanding also allows us to relax the factivity condition on explanation, which is impossible to fulfill in many machine learning models, and to focus instead on the pragmatic conditions that determine the best fit between a model and the methods and devices deployed to understand it. After an examination of the different types of understanding discussed in the philosophical and psychological literature, I conclude that interpretative or approximation models not only provide the best way to achieve the objectual understanding of a machine learning model, but are also a necessary condition to achieve post hoc interpretability. This conclusion is partly based on the shortcomings of the purely functionalist approach to post hoc interpretability that seems to be predominant in most recent literature

AVA licensing criteria : criteria for the licensing and relicensing of Access Validating Agencies

"QAA recognition scheme for access to higher education" -- front cover

Knowledge Extraction from Natural Language Requirements into a Semantic Relation Graph

Knowledge extraction and representation aims to identify information and to transform it into a machine-readable format. Knowledge representations support Information Retrieval tasks such as searching for single statements, documents, or metadata. Requirements specifications of complex systems such as automotive software systems are usually divided into different subsystem specifications. Nevertheless, there are semantic relations between individual documents of the separated subsystems, which have to be considered in further processes (e.g. dependencies). If requirements engineers or other developers are not aware of these relations, this can lead to inconsistencies or malfunctions of the overall system. Therefore, there is a strong need for tool support in order to detects semantic relations in a set of large natural language requirements specifications. In this work we present a knowledge extraction approach based on an explicit knowledge representation of the content of natural language requirements as a semantic relation graph. Our approach is fully automated and includes an NLP pipeline to transform unrestricted natural language requirements into a graph. We split the natural language into different parts and relate them to each other based on their semantic relation. In addition to semantic relations, other relationships can also be included in the graph. We envision to use a semantic search algorithm like spreading activation to allow users to search different semantic relations in the graph

Geometrical Product Specification and Verification as toolbox to meet up-to-date technical requirements

The ISO standards for the Geometrical Product Specification and Verification (GPS) define an internationally uniform description language, that allows expressing unambiguously and completely all requirements for the geometry of a product with the corresponding requirements for the inspection process in technical drawings, taking into account current possibilities of measurement and testing technology. The practice shows that the university curricula of the mechanical engineering faculties often include only limited classes on the GPS, mostly as part of curriculum of subjects like Metrology or Fundamentals of Machine Design. This does not allow students to gain enough knowledge on the subject. Currently there is no coherent EU-wide provision for vocational training (VET) in this area. Consortium, members of which are the authors of this paper, is preparing a proposal of an EU project aiming to develop appropriate course

Visual cue training to improve walking and turning after stroke:a study protocol for a multi-centre, single blind randomised pilot trial

Visual information comprises one of the most salient sources of information used to control walking and the dependence on vision to maintain dynamic stability increases following a stroke. We hypothesize, therefore, that rehabilitation efforts incorporating visual cues may be effective in triggering recovery and adaptability of gait following stroke. This feasibility trial aims to estimate probable recruitment rate, effect size, treatment adherence and response to gait training with visual cues in contrast to conventional overground walking practice following stroke.Methods/design: A 3-arm, parallel group, multi-centre, single blind, randomised control feasibility trial will compare overground visual cue training (O-VCT), treadmill visual cue training (T-VCT), and usual care (UC). Participants (n = 60) will be randomly assigned to one of three treatments by a central randomisation centre using computer generated tables to allocate treatment groups. The research assessor will remain blind to allocation. Treatment, delivered by physiotherapists, will be twice weekly for 8 weeks at participating outpatient hospital sites for the O-VCT or UC and in a University setting for T-VCT participants.Individuals with gait impairment due to stroke, with restricted community ambulation (gait spee

Poor Philanthropist II: New approaches to sustainable development

The second title in the Poor Philanthropist Series, this monograph represents the culmination of a six-year journey; a journey characterised in the first three years by in-depth qualitative research which resulted in an understanding of philanthropic traditions among people who are poor in southern Africa and gave rise to new and innovative concepts which formed the focus of the research monograph The Poor Philanthropist: How and Why the Poor Help Each Other, published by the Southern Africa-United States Centre for Leadership and Public Values in 2005