scholarly journals Requirements-level language and tools for capturing software system essence

2013 ◽  
Vol 10 (4) ◽  
pp. 1499-1524 ◽  
Author(s):  
Wiktor Nowakowski ◽  
Michał Śmiałek ◽  
Albert Ambroziewicz ◽  
Tomasz Straszak
Keyword(s):  
Natural Language ◽  
Domain Knowledge ◽  
Comprehensive Treatment ◽  
Software System ◽  
Problem Domain ◽  
Behavioural Characteristics ◽  
Software Specifications ◽  
Application Logic ◽  
Imperative Subject ◽  
New System

Creation of an unambiguous requirements specification with precise domain vocabulary is crucial for capturing the essence of any software system, either when developing a new system or when recovering knowledge from a legacy one. Software specifications usually maintain noun notions and include them in central vocabularies. Verb or adjective phrases are easily forgotten and their definitions buried inside imprecise paragraphs of text. This paper proposes a model-based language for comprehensive treatment of domain knowledge, expressed through constrained natural language phrases that are grouped by nouns and include verbs, adjectives and prepositions. In this language, vocabularies can be formulated to describe behavioural characteristics of a given problem domain. What is important, these characteristics can be linked from within other specifications similarly to a wiki. The application logic can be formulated through sequences of imperative subject-predicate sentences containing only links to the phrases in the vocabulary. The paper presents an advanced tooling framework to capture application logic specifications making them available for automated transformations down to code. The tools were validated through a controlled experiment.

DARR: A Free-text Analysis System for the Automatic Documentation of Radiological Reports

1977 ◽  
Vol 16 (03) ◽  
pp. 144-153 ◽  
Author(s):  
E. Vaccari ◽  
W. Delaney ◽  
A. Chiesa
Keyword(s):  
Natural Language ◽  
Text Analysis ◽  
Automatic Documentation ◽  
Free Text ◽  
Software System ◽  
Automatic Translation ◽  
Radiological Report ◽  
Analysis System ◽  
Content Processing

A software system for the automatic free-text analysis and retrieval of radiological reports is presented. Such software involves: (1) automatic translation of the specific natural language in a formalized metalanguage in order to transform the radiological report in a »normalized report« analyzable by computer; (2) content processing of the normalized report to select desired information. The approach used to accomplish point (1) is described in detail referring to a specific application.

scholarly journals Natural language processing methods for knowledge management—Applying document clustering for fast search and grouping of engineering documents

2021 ◽  
pp. 1063293X2098297
Author(s):  
Ivar Örn Arnarsson ◽  
Otto Frost ◽  
Emil Gustavsson ◽  
Mats Jirstrand ◽  
Johan Malmqvist
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Domain Knowledge ◽  
Clustering Algorithms ◽  
Document Clustering ◽  
Unstructured Data ◽  
Free Text ◽  
Engineering Change ◽  
Engineering Documents

Product development companies collect data in form of Engineering Change Requests for logged design issues, tests, and product iterations. These documents are rich in unstructured data (e.g. free text). Previous research affirms that product developers find that current IT systems lack capabilities to accurately retrieve relevant documents with unstructured data. In this research, we demonstrate a method using Natural Language Processing and document clustering algorithms to find structurally or contextually related documents from databases containing Engineering Change Request documents. The aim is to radically decrease the time needed to effectively search for related engineering documents, organize search results, and create labeled clusters from these documents by utilizing Natural Language Processing algorithms. A domain knowledge expert at the case company evaluated the results and confirmed that the algorithms we applied managed to find relevant document clusters given the queries tested.

An Experimental Analysis of the Effectiveness and Efficiency of Teams with Partial Problem Domain Knowledge

2011 ◽  
pp. 104-114
Author(s):  
Dinesh A. Mirchandani ◽  
Jaideep Motwani
Keyword(s):  
Knowledge Management ◽  
Experimental Analysis ◽  
Domain Knowledge ◽  
Specific Problem ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Problem Domain ◽  
Effectiveness And Efficiency ◽  
Knowledge Content ◽  
Area Of Application

Knowledge Management Systems are increasingly becoming important to both practitioners and researchers. One area of application of such systems is the formation of organizational teams with appropriate knowledge content to solve complex and novel problems. A common predicament, however, is that teams are often formed with only partial problem domain knowledge. This study examines if teams that have partial problem domain knowledge are more effective and efficient than teams that do not have specific problem domain knowledge. It finds that partial problem domain knowledge may in fact be worse than no problem domain knowledge. Several implications for researchers and practitioners are derived from this result.

Second Order Interactive End User Development Appropriation in the Public Sector

2018 ◽  
Vol 30 (1) ◽  
pp. 82-106 ◽  
Author(s):  
Anders Avdic
Keyword(s):  
Public Sector ◽  
Domain Knowledge ◽  
Research Question ◽  
Primary User ◽  
Second Order ◽  
End User ◽  
Problem Domain ◽  
Public Servants ◽  
The Public ◽  
Problem Solving Process

This paper seeks to respond to the research question: How does appropriation take place in the public sector in the development of end user applications by civil servants? Appropriation is defined as taking advantage of opportunities related to the development and use of applications, when the developer has in-depth knowledge of the problem domain and is also the primary user of the application. The author's results showed that public servants who have deep problem domain knowledge can take advantage of end user tools (e.g. spreadsheet programs) in the problem- solving process to solve vaguely defined problems. Appropriation is manifested in the continuous development of various ICT applications. In this paper, the author differentiates between first- and second-order appropriation. First-order appropriation takes place when the potential of the development tool is appropriated by the end user. Second-order appropriation takes place when an application is continuously developed and refined in parallel with the end user's learning process and the development of organizational requirements.

scholarly journals Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and Food

2021 ◽  
Vol 3 ◽  
Author(s):  
Marieke van Erp ◽  
Christian Reynolds ◽  
Diana Maynard ◽  
Alain Starke ◽  
Rebeca Ibáñez Martín ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Domain Knowledge ◽  
State Of The Art ◽  
Interdisciplinary Approach ◽  
Comprehensive Analysis ◽  
The State ◽  
Use Cases

In this paper, we discuss the use of natural language processing and artificial intelligence to analyze nutritional and sustainability aspects of recipes and food. We present the state-of-the-art and some use cases, followed by a discussion of challenges. Our perspective on addressing these is that while they typically have a technical nature, they nevertheless require an interdisciplinary approach combining natural language processing and artificial intelligence with expert domain knowledge to create practical tools and comprehensive analysis for the food domain.

Natural Language Processing

1996 ◽  
Vol 16 ◽  
pp. 70-85 ◽  
Author(s):  
Thomas C. Rindflesch
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Computational Linguistics ◽  
Language Processing ◽  
Domain Knowledge ◽  
The State ◽  
Point Of View ◽  
Computer Applications ◽  
Significant Progress ◽  
Future Directions

Work in computational linguistics began very soon after the development of the first computers (Booth, Brandwood and Cleave 1958), yet in the intervening four decades there has been a pervasive feeling that progress in computer understanding of natural language has not been commensurate with progress in other computer applications. Recently, a number of prominent researchers in natural language processing met to assess the state of the discipline and discuss future directions (Bates and Weischedel 1993). The consensus of this meeting was that increased attention to large amounts of lexical and domain knowledge was essential for significant progress, and current research efforts in the field reflect this point of view.

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