Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Improving the translation environment for professional translators

When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project

The Most Influential Paper Gerard Salton Never Wrote

Gerard Salton is often credited with developing the vector space model (VSM) for information retrieval (IR). Citations to Salton give the impression that the VSM must have been articulated as an IR model sometime between 1970 and 1975. However, the VSM as it is understood today evolved over a longer time period than is usually acknowledged, and an articulation of the model and its assumptions did not appear in print until several years after those assumptions had been criticized and alternative models proposed. An often cited overview paper titled ???A Vector Space Model for Information Retrieval??? (alleged to have been published in 1975) does not exist, and citations to it represent a confusion of two 1975 articles, neither of which were overviews of the VSM as a model of information retrieval. Until the late 1970s, Salton did not present vector spaces as models of IR generally but rather as models of specifi c computations. Citations to the phantom paper refl ect an apparently widely held misconception that the operational features and explanatory devices now associated with the VSM must have been introduced at the same time it was fi rst proposed as an IR model.published or submitted for publicatio

Supporting Interview Analysis with Autocoding

Interview analysis is a technique employed in qualitative research. Researchers annotate (code) interview transcriptions, often with the help of Computer-Assisted Qualitative Data Analysis Software (CAQDAS). The tools available today largely replicate the manual process of annotation. In this article, we demonstrate how to use natural language processing (NLP) to increase the reproducibility and traceability of the process of applying codes to text data. We integrated an existing commercial machine--learning (ML) based concept extraction service into an NLP pipeline independent of domain specific rules. We applied our prototype in three qualitative studies to evaluate its capabilities of supporting researchers by providing recommendations consistent with their initial work. Unlike rule based approaches, our process can be applied to interviews from any domain, without additional burden to the researcher for creating a new ruleset. Our work using three example data sets shows that this approach shows promise for a real--life application, but further research is needed

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Intelligent tutoring systems for systems engineering methodologies

The general goal is to provide the technology required to build systems that can provide intelligent tutoring in IDEF (Integrated Computer Aided Manufacturing Definition Method) modeling. The following subject areas are covered: intelligent tutoring systems for systems analysis methodologies; IDEF tutor architecture and components; developing cognitive skills for IDEF modeling; experimental software; and PC based prototype

Translation Studies from the Perspective of Corpus Translation Studies and Digital Humanities

As a translation research method and paradigm, corpus translation studies have gradually gained attention from the translation community since their introduction to China in the 1970s. With the rapid development of information technology and artificial intelligence, corpus translation studies have continuously made new progress. With the support of digital humanities technologies such as Big data, artificial intelligence and cloud computing, the development of corpus translatology presents new features and trends. This article explores the application of corpus translation studies in translation studies from both theoretical and practical perspectives. At the theoretical level, this article believes that corpus translation studies have significant implications for the paradigm shift, theoretical innovation, and disciplinary development of translation studies. At the practical level, this article points out that corpus translation studies have strong data support, which can improve the efficiency and accuracy of translation research. Based on this, this article proposes that future translation research should focus on data-driven research paradigms, attach importance to the important role of data in translation, and build a theoretical model of translation studies on this basis, in order to provide theoretical guidance for comprehensively improving the quality of translation research