Linguistic Analysis of Crowd Requirements: An Experimental Study

Javed Ali Khan, Lin Liu, Yidi Jia, Lijie Wen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Users of today's online software services are often diversified and distributed, whose needs are hard to elicit using conventional RE approaches. As a consequence, crowd-based, data intensive requirements engineering approaches are considered important. In this paper, we have conducted an experimental study on a dataset of 2,966 requirements statements to evaluate the performance of three text clustering algorithms. The purpose of the study is to aggregate similar requirement statements suggested by the crowd users, and also to identify domain objects and operations, as well as required features from the given requirements statements dataset. The experimental results are then cross-checked with original tags provided by data providers for validation.

Original languageEnglish
Title of host publicationProceedings - 2018 7th Workshop on Empirical Requirements Engineering, EmpiRE 2018
EditorsEric Knauss, Sabrina Marczak, Nazim Madhavji, Maya Daneva
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages24-31
Number of pages8
ISBN (Electronic)9781538683590
DOIs
Publication statusPublished - 19 Oct 2018
Externally publishedYes
Event7th Workshop on Empirical Requirements Engineering, EmpiRE 2018 - Banff, Canada
Duration: 21 Aug 2018 → …

Publication series

NameProceedings - 2018 7th Workshop on Empirical Requirements Engineering, EmpiRE 2018

Conference

Conference7th Workshop on Empirical Requirements Engineering, EmpiRE 2018
Country/TerritoryCanada
CityBanff
Period21/08/18 → …

Keywords

  • Crowd-based RE
  • experiment
  • requirement clustering
  • Smart home
  • Summarization

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