Highly focused document retrieval in aerospace engineering : user interaction design and evaluation

Purpose – This paper seeks to describe the preliminary studies (on both users and data), the design and evaluation of the K-Search system for searching legacy documents in aerospace engineering. Real-world reports of jet engine maintenance challenge the current indexing practice, while real users’ tasks require retrieving the information in the proper context. K-Search is currently in use in Rolls-Royce plc and has evolved to include other tools for knowledge capture and management. Design/methodology/approach – Semantic Web techniques have been used to automatically extract information from the reports while maintaining the original context, allowing a more focused retrieval than with more traditional techniques. The paper combines semantic search with classical information retrieval to increase search effectiveness. An innovative user interface has been designed to take advantage of this hybrid search technique. The interface is designed to allow a flexible and personal approach to searching legacy data. Findings – The user evaluation showed that the system is effective and well received by users. It also shows that different people look at the same data in different ways and make different use of the same system depending on their individual needs, influenced by their job profile and personal attitude. Research limitations/implications – This study focuses on a specific case of an enterprise working in aerospace engineering. Although the findings are likely to be shared with other engineering domains (e.g. mechanical, electronic), the study does not expand the evaluation to different settings. Originality/value – The study shows how real context of use can provide new and unexpected challenges to researchers and how effective solutions can then be adopted and used in organizations.</p

Applying semantic web technologies to knowledge sharing in aerospace engineering

This paper details an integrated methodology to optimise Knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses Ontologies as a central modelling strategy for the Capture of Knowledge from legacy docu-ments via automated means, or directly in systems interfacing with Knowledge workers, via user-defined, web-based forms. The domain ontologies used for Knowledge Capture also guide the retrieval of the Knowledge extracted from the data using a Semantic Search System that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale

Facilitating design learning through faceted classification of in-service information

The maintenance and service records collected and maintained by engineering companies are a useful resource for the ongoing support of products. Such records are typically semi-structured and contain key information such as a description of the issue and the product affected. It is suggested that further value can be realised from the collection of these records for indicating recurrent and systemic issues which may not have been apparent previously. This paper presents a faceted classification approach to organise the information collection that might enhance retrieval and also facilitate learning from in-service experiences. The faceted classification may help to expedite responses to urgent in-service issues as well as to allow for patterns and trends in the records to be analysed, either automatically using suitable data mining algorithms or by manually browsing the classification tree. The paper describes the application of the approach to aerospace in-service records, where the potential for knowledge discovery is demonstrated

Automatic abstracting: a review and an empirical evaluation

The abstract is a fundamental tool in information retrieval. As condensed representations, they facilitate conservation of the increasingly precious search time and space of scholars, allowing them to manage more effectively an ever-growing deluge of documentation. Traditionally the product of human intellectual effort, attempts to automate the abstracting process began in 1958. Two identifiable automatic abstracting techniques emerged which reflect differing levels of ambition regarding simulation of the human abstracting process, namely sentence extraction and text summarisation. This research paradigm has recently diversified further, with a cross-fertilisation of methods. Commercial systems are beginning to appear, but automatic abstracting is still mainly confined to an experimental arena. The purpose of this study is firstly to chart the historical development and current state of both manual and automatic abstracting; and secondly, to devise and implement an empirical user-based evaluation to assess the adequacy of automatic abstracts derived from sentence extraction techniques according to a set of utility criteria. [Continues.

Towards semantic interpretation of clinical narratives with ontology-based text mining

In the realm of knee pathology, magnetic resonance imaging (MRI) has the advantage of visualising all structures within the knee joint, which makes it a valuable tool for increasing diagnostic accuracy and planning surgical treatments. Therefore, clinical narratives found in MRI reports convey valuable diagnostic information. A range of studies have proven the feasibility of natural language processing for information extraction from clinical narratives. However, no study focused specifically on MRI reports in relation to knee pathology, possibly due to the complexity of knee anatomy and a wide range of conditions that may be associated with different anatomical entities. In this thesis, we describe KneeTex, an information extraction system that operates in this domain. As an ontology-driven information extraction system, KneeTex makes active use of an ontology to strongly guide and constrain text analysis. We used automatic term recognition to facilitate the development of a domain-specific ontology with sufficient detail and coverage for text mining applications. In combination with the ontology, high regularity of the sublanguage used in knee MRI reports allowed us to model its processing by a set of sophisticated lexico-semantic rules with minimal syntactic analysis. The main processing steps involve named entity recognition combined with coordination, enumeration, ambiguity and co-reference resolution, followed by text segmentation. Ontology-based semantic typing is then used to drive the template filling process. We adopted an existing ontology, TRAK (Taxonomy for RehAbilitation of Knee conditions), for use within KneeTex. The original TRAK ontology expanded from 1,292 concepts, 1,720 synonyms and 518 relationship instances to 1,621 concepts, 2,550 synonyms and 560 relationship instances. This provided KneeTex with a very fine-grained lexicosemantic knowledge base, which is highly attuned to the given sublanguage. Information extraction results were evaluated on a test set of 100 MRI reports. A gold standard consisted of 1,259 filled template records with the following slots: finding, finding qualifier, negation, certainty, anatomy and anatomy qualifier. KneeTex extracted information with precision of 98.00%, recall of 97.63% and F-measure of 97.81%, the values of which are in line with human-like performance. To demonstrate the utility of formally structuring clinical narratives and possible applications in epidemiology, we describe an implementation of KneeBase, a web-based information retrieval system that supports complex searches over the results obtained via KneeTex. It is the structured nature of extracted information that allows queries that encode not only search terms, but also relationships between them (e.g. between clinical findings and anatomical locations). This is of particular value for large-scale epidemiology studies based on qualitative evidence, whose main bottleneck involves manual inspection of many text documents. The two systems presented in this dissertation, KneeTex and KneeBase, operate in a specific domain, but illustrate generic principles for rapid development of clinical text mining systems. The key enabler of such systems is the existence of an appropriate ontology. To tackle this issue, we proposed a strategy for ontology expansion, which proved effective in fast–tracking the development of our information extraction and retrieval systems

Use and Evaluation of Controlled Languages in Industrial Environments and Feasibility Study for the Implementation of Machine Translation

El presente trabajo de investigación se enmarca en los estudios de doctorado en traducción y la sociedad del conocimiento de la Universidad de Valencia y, en concreto, en la línea de investigación en tecnologías de la traducción, terminología y localización. En este sentido, esta disertación surge por la necesidad de establecer una metodología de investigación y ofrecer resultados empíricos sobre el desarrollo, implementación y evaluación de lenguajes controlados en la documentación técnica y su efecto tanto en los textos originales como en las traducciones de estos documentos. Así pues, el objetivo ha sido desarrollar una metodología para evaluar el impacto de los lenguajes controlados en la producción de documentación técnica dentro de contextos industriales y, más en concreto, en la elaboración de documentación técnica para el vehículo. El impacto se ha concretado en la mejora de la traducibilidad automática, un concepto que hemos discutido ampliamente en el capítulo 4, así como de la calidad de los textos meta.This research is part of the doctoral studies program "La traducción y la sociedad del conocimiento" at the University of Valencia. In particular the area of ​​research is translation technology, terminology and localisation. In this sense, this dissertation arises from the need to establish a research methodology and to provide empirical results on the development, implementation and evaluation of controlled languages ​​in the technical documentation and its effect on both original texts and the translations of these documents. Thus, the aim has been to develop a methodology to assess the impact of controlled languages ​​in the production of technical documentation in industrial contexts, and more specifically in the technical documentation for the vehicle. The impact has resulted in improved automatic translatability, a concept we have discussed at length in Chapter 4, as well as in the quality of the target texts