Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Recovering Traceability Links between Code and Documentation
IEEE Transactions on Software Engineering
ICTAI '00 Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence
Supporting Software Evolution through Dynamically Retrieving Traces to UML Artifacts
IWPSE '04 Proceedings of the Principles of Software Evolution, 7th International Workshop
Helping Analysts Trace Requirements: An Objective Look
RE '04 Proceedings of the Requirements Engineering Conference, 12th IEEE International
Utilizing Supporting Evidence to Improve Dynamic Requirements Traceability
RE '05 Proceedings of the 13th IEEE International Conference on Requirements Engineering
Advancing Candidate Link Generation for Requirements Tracing: The Study of Methods
IEEE Transactions on Software Engineering
Building bridges for web query classification
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Robust classification of rare queries using web knowledge
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Classifying search queries using the Web as a source of knowledge
ACM Transactions on the Web (TWEB)
Understanding user's query intent with wikipedia
Proceedings of the 18th international conference on World wide web
ASE '08 Proceedings of the 2008 23rd IEEE/ACM International Conference on Automated Software Engineering
Guided Navigation Using Query Log Mining through Query Expansion
NSS '09 Proceedings of the 2009 Third International Conference on Network and System Security
Improving automated requirements trace retrieval: a study of term-based enhancement methods
Empirical Software Engineering
A machine learning approach for tracing regulatory codes to product specific requirements
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Traceclipse: an eclipse plug-in for traceability link recovery and management
Proceedings of the 6th International Workshop on Traceability in Emerging Forms of Software Engineering
Automatically detecting the quality of the query and its implications in IR-based concept location
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
Evaluating the specificity of text retrieval queries to support software engineering tasks
Proceedings of the 34th International Conference on Software Engineering
Automatic query performance assessment during the retrieval of software artifacts
Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering
Mining textual requirements to assist architectural software design: a state of the art review
Artificial Intelligence Review
Information and Software Technology
Automatic query reformulations for text retrieval in software engineering
Proceedings of the 2013 International Conference on Software Engineering
Query quality prediction and reformulation for source code search: the refoqus tool
Proceedings of the 2013 International Conference on Software Engineering
Query quality prediction and reformulation for source code search: the refoqus tool
Proceedings of the 2013 International Conference on Software Engineering
Enhancing software artefact traceability recovery processes with link count information
Information and Software Technology
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Automated trace retrieval methods can significantly reduce the cost and effort needed to create and maintain requirements traces. However, the set of generated traces is generally quite imprecise and must be manually evaluated by analysts. In applied settings when the retrieval algorithm is unable to find the relevant links for a given query, a human user can improve the trace results by manually adding additional search terms and filtering out unhelpful ones. However, the effectiveness of this approach is largely dependent upon the knowledge of the user. In this paper we present an automated technique for replacing the original query with a new set of query terms. These query terms are learned through seeding a web-based search with the original query and then processing the results to identify a set of domain-specific terms. The query-mining algorithm was evaluated and fine-tuned using security regulations from the USA government's Health Insurance Privacy and Portability Act (HIPAA) traced against ten healthcare related requirements specifications.