Ripple Down Rules for Question Answering

Recent years have witnessed a new trend of building ontology-based question answering systems. These systems use semantic web information to produce more precise answers to users' queries. However, these systems are mostly designed for English. In this paper, we introduce an ontology-based question answering system named KbQAS which, to the best of our knowledge, is the first one made for Vietnamese. KbQAS employs our question analysis approach that systematically constructs a knowledge base of grammar rules to convert each input question into an intermediate representation element. KbQAS then takes the intermediate representation element with respect to a target ontology and applies concept-matching techniques to return an answer. On a wide range of Vietnamese questions, experimental results show that the performance of KbQAS is promising with accuracies of 84.1% and 82.4% for analyzing input questions and retrieving output answers, respectively. Furthermore, our question analysis approach can easily be applied to new domains and new languages, thus saving time and human effort.Comment: V1: 21 pages, 7 figures, 10 tables. V2: 8 figures, 10 tables; shorten section 2; change sections 4.3 and 5.1.2. V3: Accepted for publication in the Semantic Web journal. V4 (Author's manuscript): camera ready version, available from the Semantic Web journal at http://www.semantic-web-journal.ne

A Factoid Question Answering System for Vietnamese

In this paper, we describe the development of an end-to-end factoid question answering system for the Vietnamese language. This system combines both statistical models and ontology-based methods in a chain of processing modules to provide high-quality mappings from natural language text to entities. We present the challenges in the development of such an intelligent user interface for an isolating language like Vietnamese and show that techniques developed for inflectional languages cannot be applied "as is". Our question answering system can answer a wide range of general knowledge questions with promising accuracy on a test set.Comment: In the proceedings of the HQA'18 workshop, The Web Conference Companion, Lyon, Franc

A Robust Transformation-Based Learning Approach Using Ripple Down Rules for Part-of-Speech Tagging

In this paper, we propose a new approach to construct a system of transformation rules for the Part-of-Speech (POS) tagging task. Our approach is based on an incremental knowledge acquisition method where rules are stored in an exception structure and new rules are only added to correct the errors of existing rules; thus allowing systematic control of the interaction between the rules. Experimental results on 13 languages show that our approach is fast in terms of training time and tagging speed. Furthermore, our approach obtains very competitive accuracy in comparison to state-of-the-art POS and morphological taggers.Comment: Version 1: 13 pages. Version 2: Submitted to AI Communications - the European Journal on Artificial Intelligence. Version 3: Resubmitted after major revisions. Version 4: Resubmitted after minor revisions. Version 5: to appear in AI Communications (accepted for publication on 3/12/2015

Improved Chinese Language Processing for an Open Source Search Engine

Natural Language Processing (NLP) is the process of computers analyzing on human languages. There are also many areas in NLP. Some of the areas include speech recognition, natural language understanding, and natural language generation. Information retrieval and natural language processing for Asians languages has its own unique set of challenges not present for Indo-European languages. Some of these are text segmentation, named entity recognition in unsegmented text, and part of speech tagging. In this report, we describe our implementation of and experiments with improving the Chinese language processing sub-component of an open source search engine, Yioop. In particular, we rewrote and improved the following sub-systems of Yioop to try to make them as state-of-the-art as possible: Chinese text segmentation, Part-of-speech (POS) tagging, Named Entity Recognition (NER), and Question and Answering System. Compared to the previous system we had a 9% improvement on Chinese words Segmentation accuracy. We built POS tagging with 89% accuracy. And We implement NER System with 76% accuracy

Social media in the english classroom: a study on the use of whatsapp messenger by english teaching training program students of Universidad Andrés Bello Casona de Las Condes campus

Tesis (Profesor de Inglés para la Enseñanza Básica y Media y al grado académico de Licenciado en Educación)The reason behind the use of WhatsApp Messenger (WM) by the English Teaching Training Program (ETTP) students and its possible effects on their engagement is a problem that has not been addressed in the Chilean context. The present study was designed to fill this gap. The purpose of this study was to examine the dynamics of the English class regarding the use of mobile devices. Moreover, this study aimed at examining the reasons behind the use of WM by ETTP students of UNAB Casona Las Condes Campus and its possible effects on their engagement in the English class. The method used in this investigation followed the characteristics of a sequential explanatory design. The results were obtained through two observations, a questionnaire, and a focus group. This research study concluded that the use of smartphones and specifically WM has grown exponentially as it is constantly affecting our daily routine and habits, and also what happens inside the classroom. The results revealed there were several themes attributed to disengagement that might trigger students to use WM in the English class, such as boredom, short attention span, and demotivation.Las razones de los estudiantes de Pedagogía en Inglés para usar WhatsApp Messenger (WM) y sus posibles efectos sobre el involucramiento que estos tienen en las clases de inglés es un problema que aún no ha sido tratado en el contexto chileno. El presente estudio fue diseñado para suplir esta falencia. El propósito de esta investigación fue examinar las dinámicas de la clase de inglés en relación con el uso de dispositivos móviles. Además, este estudio tenía el propósito de examinar las razones de los estudiantes de Pedagogía en Inglés de UNAB Campus Casona de Las Condes para usar WM y los posibles efectos que su involucramiento pudiera tener en la sala de inglés. El método usado en esta investigación siguió las características de un diseño secuencial explanatorio. Los resultados se obtuvieron a través de dos observaciones, un cuestionario y un grupo focal. Este estudio de investigación nos permitió concluir que el uso de smartphones y específicamente el uso de WM han crecido de forma exponencial de manera que este afecta constantemente nuestras rutinas diarias y hábitos. Los resultados revelaron que existen varios temas que se pueden atribuir al desenganche y que pueden causar que los estudiantes usen WM en la clase de inglés, como el aburrimiento, el corto periodo de concentración y la desmotivación

Socio-Technical Perspective on Managing Type II Diabetes

Social attributes such as education level, family history or place of residence all place a strong role in the probability of a person developing type II diabetes later in life. The aim of this paper is to develop a knowledge system based to use social attributes to estimate the prevalence of type II diabetes in a given area in Australia to support public health policymaking. The focus of this paper is towards answering the research question How can social determinants associated with type II diabetes, be used to incrementally develop a supporting knowledge-based system (KBS)? The contribution of this paper is two folds: 1. The problem domain is analysed and a suitable KBS development framework is chosen 2. A prototype is developed and presented. Initial results with preliminary data confirm the validity of the approach