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Semi-automatically extracting FAQs to improve accessibility of software development knowledge

Henß, Stefan ; Monperrus, Martin ; Mezini, Mira :
Semi-automatically extracting FAQs to improve accessibility of software development knowledge.
In: ICSE '12 . IEEE Press
[Konferenz- oder Workshop-Beitrag], (2012)

Kurzbeschreibung (Abstract)

Frequently asked questions (FAQs) are a popular way to document software development knowledge. As creating such documents is expensive, this paper presents an approach for automatically extracting FAQs from sources of software development discussion, such as mailing lists and Internet forums, by combining techniques of text mining and natural language processing. We apply the approach to popular mailing lists and carry out a survey among software developers to show that it is able to extract high-quality FAQs that may be further improved by experts.

Typ des Eintrags: Konferenz- oder Workshop-Beitrag (Keine Angabe)
Erschienen: 2012
Autor(en): Henß, Stefan ; Monperrus, Martin ; Mezini, Mira
Titel: Semi-automatically extracting FAQs to improve accessibility of software development knowledge
Sprache: Deutsch
Kurzbeschreibung (Abstract):

Frequently asked questions (FAQs) are a popular way to document software development knowledge. As creating such documents is expensive, this paper presents an approach for automatically extracting FAQs from sources of software development discussion, such as mailing lists and Internet forums, by combining techniques of text mining and natural language processing. We apply the approach to popular mailing lists and carry out a survey among software developers to show that it is able to extract high-quality FAQs that may be further improved by experts.

Buchtitel: Proceedings of the 34th International Conference on Software Engineering
Reihe: ICSE '12
Verlag: IEEE Press
Freie Schlagworte: text mining, natural language processing, NLP, software developement management, knowledge management
Fachbereich(e)/-gebiet(e): Profilbereiche > Cybersicherheit (CYSEC)
Profilbereiche
Veranstaltungsort: Zurich, Switzerland
Hinterlegungsdatum: 28 Aug 2017 13:34
ID-Nummer: TUD-CS-2012-0381
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