Question Terminology and Representation for Question Type Classification

Question terminology is a set of terms which appear in keywords, idioms and fixed expressions commonly observed in questions. This paper investigates ways to automatically extract question terminology from a corpus of questions and represent them for the purpose of classifying by question type. Our key interest is to see whether or not semantic features can enhance the representation of strongly lexical nature of question sentences. We compare two feature sets: one with lexical features only, and another with a mixture of lexical and semantic features. For evaluation, we measure the classification accuracy made by two machine learning algorithms, C5.0 and PEBLS, by using a procedure called domain cross-validation, which effectively measures the domain transferability of features

Steps Toward Real-time Natural Language Processing

Understanding language is a seemingly effortless task for people. Not only can they understand the meaning of sentences with great accuracy, they do so quickly: in most cases, people understand language in linear time. In constrast, understanding language is not so easy for computers. Even ignoring problems of accuracy, natural language processing systems ane much slower than people aje. All current NL P systems that fully analyze both the syntactic structure and semantic meaning of text fall short of human performance in this respect. In this paper, we present an attempt to develop a linear time algorithm for parsing natural language using unification grammcirs. While the computational complexity of the algorithm is, in the worst case, no better than that of many other algorithms, empirical testing indicates improved average-case performance. Although linear performance has not yet been achieved, we will discuss possible improvements that may result in an average-case linear time algorithm

How Effective the Students' Interaction Opportunities Have Been in the Education Program toward Adults!: A Case Study on the Instruction Course to Train "Facilitators on Agriculture and Food" Authorized by Utsunomiya University

text紀要論文 / Departmental Bulletin Paperdepartmental bulletin pape

Natural language processing in the faq finder system: Results and prospects

Abstract This paper describes some recent results regarding the employment of natural language processing techniques in the FAQ FINDER system. FAQ FINDER is a natural language question-answering system that uses files of frequently-asked questions as its knowledge base. Unlike AI questionanswering systems that focus on the generation of new answers, FAQ FINDER retrieves existing ones found in frequently-asked question files. FAQ FINDER uses a combination of statistical and natural language techniques to match user questions against known question/answer pairs from FAQ files. We strove in our experiments to identify the contribution of these techniques to the overall success of the system. One unexpected result was that our parsing technique was not contributing as much to the system's performance as we expected. We discuss some of the reasons why this may have been the case, and describe further natural language processing research designed to address the system's current needs

As Essay on the Function of Cultivating Human Resources as Universities' Contribution to Society

text紀要論文 / Departmental Bulletin Paperdepartmental bulletin pape

対話的雰囲気を活用したグループ学習の手法-引き出しあい、つなぎあって、まとめあげる手順-

text紀要論文 / Departmental Bulletin Paperdepartmental bulletin pape

The role of hydrogen and fuel cells in the global energy system

Hydrogen technologies have experienced cycles of excessive expectations followed by disillusion. Nonetheless, a growing body of evidence suggests these technologies form an attractive option for the deep decarb onisation of global energy systems, and that recent improvements in their cost and performance point towards economic viability as well. This paper is a comprehensive review of the potential role that hydrogen could play in the provision of electricity, h eat, industry, transport and energy storage in a low - carbon energy system, and an assessment of the status of hydrogen in being able to fulfil that potential. The picture that emerges is one of qualified promise: hydrogen is well established in certain nic hes such as forklift trucks, while mainstream applications are now forthcoming. Hydrogen vehicles are available commercially in several countries, and 225,000 fuel cell home heating systems have been sold. This represents a step change from the situation of only five years ago. This review shows that challenges around cost and performance remain, and considerable improvements are still required for hydrogen to become truly competitive. But such competitiveness in the medium - term future no longer seems an unrealistic prospect, which fully justifies the growing interest and policy support for these technologies around the world