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

Subject: Human Resource Management

Compiled by Susan LaCette.HumanResourceManagement.pdf: 5527 downloads, before Oct. 1, 2020

Requirements analysis for decision-support system design: evidence from the automotive industry

The purpose of this paper is to outline the requirements analysis that was carried out to support the development of a system that allows engineers to view real-time data integrated from multiple silos such as Product Lifecycle Management (PLM) and Warranty systems, in a single and visual environment. The outcome of this study provides a clear understanding of how engineers working in different phases of the product-lifecycle could utilise such information to improve the decision making process and as a result design better products. This study uses data collected via in-depth semi-structured interviews and workshops that includes people working in various roles within the automotive sector. In order to demonstrate the applicability this approach, SysML diagrams are also provided

Misaligned Values in Software Engineering Organizations

The values of software organizations are crucial for achieving high performance; in particular, agile development approaches emphasize their importance. Researchers have thus far often assumed that a specific set of values, compatible with the development methodologies, must be adopted homogeneously throughout the company. It is not clear, however, to what extent such assumptions are accurate. Preliminary findings have highlighted the misalignment of values between groups as a source of problems when engineers discuss their challenges. Therefore, in this study, we examine how discrepancies in values between groups affect software companies' performance. To meet our objectives, we chose a mixed method research design. First, we collected qualitative data by interviewing fourteen (\textit{N} = 14) employees working in four different organizations and processed it using thematic analysis. We then surveyed seven organizations (\textit{N} = 184). Our analysis indicated that value misalignment between groups is related to organizational performance. The aligned companies were more effective, more satisfied, had higher trust, and fewer conflicts. Our efforts provide encouraging findings in a critical software engineering research area. They can help to explain why some companies are more efficient than others and, thus, point the way to interventions to address organizational challenges.Comment: accepted for publication in Journal of Software: Evolution and Proces

Motivation: A selected bibliography

A bibliography is presented of books, periodicals, and documents concerning managerial motivation

Text mining techniques for patent analysis.

Abstract Patent documents contain important research results. However, they are lengthy and rich in technical terminology such that it takes a lot of human efforts for analyses. Automatic tools for assisting patent engineers or decision makers in patent analysis are in great demand. This paper describes a series of text mining techniques that conforms to the analytical process used by patent analysts. These techniques include text segmentation, summary extraction, feature selection, term association, cluster generation, topic identification, and information mapping. The issues of efficiency and effectiveness are considered in the design of these techniques. Some important features of the proposed methodology include a rigorous approach to verify the usefulness of segment extracts as the document surrogates, a corpus-and dictionary-free algorithm for keyphrase extraction, an efficient co-word analysis method that can be applied to large volume of patents, and an automatic procedure to create generic cluster titles for ease of result interpretation. Evaluation of these techniques was conducted. The results confirm that the machine-generated summaries do preserve more important content words than some other sections for classification. To demonstrate the feasibility, the proposed methodology was applied to a realworld patent set for domain analysis and mapping, which shows that our approach is more effective than existing classification systems. The attempt in this paper to automate the whole process not only helps create final patent maps for topic analyses, but also facilitates or improves other patent analysis tasks such as patent classification, organization, knowledge sharing, and prior art searches