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Enhancing Software Feature Extraction Results Using Sentiment Analysis to Aid Requirements Reuse
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-28244-0_2openalex-snapshot
Requirements Elicitation: A Survey of Techniques, Approaches, and Tools
inferredcites →https://doi.org/10.1007/978-3-319-06605-9_48openalex-snapshot
For User-Driven Software Evolution: Requirements Elicitation Derived from Mining Online Reviews
inferredcites →https://doi.org/10.1007/978-94-010-0201-1_1openalex-snapshot
The Penn Treebank: An Overview
inferredcites →https://doi.org/10.1007/s00766-016-0249-3openalex-snapshot
Ambiguity and tacit knowledge in requirements elicitation interviews
inferredcites →https://doi.org/10.1007/s10664-018-9601-1openalex-snapshot
App store mining is not enough for app improvement
inferredcites →https://doi.org/10.1016/j.asoc.2016.07.048openalex-snapshot
Extracting features from online software reviews to aid requirements reuse
inferredcites →https://doi.org/10.1016/j.infsof.2014.01.009openalex-snapshot
Systematizing requirements elicitation technique selection
inferredcites →https://doi.org/10.1016/j.jss.2015.12.030openalex-snapshot
Requirements cybernetics: Elicitation based on user behavioral data
inferredcites →https://doi.org/10.1016/j.procs.2014.07.013openalex-snapshot
Sentiment Analysis on Reviews of Mobile Users
inferredcites →https://doi.org/10.1063/5.0042134openalex-snapshot
Crowdsourcing as a tool to elicit software requirements
inferredcites →https://doi.org/10.1109/access.2020.2982837openalex-snapshot
Extended Rationale-Based Model for Tacit Knowledge Elicitation in Requirements Elicitation Context
inferredcites →https://doi.org/10.1109/access.2021.3070606openalex-snapshot
User Stories and Natural Language Processing: A Systematic Literature Review
inferredcites →https://doi.org/10.1109/eecsi.2018.8752792openalex-snapshot
Incident and Service Request Management for Academic Information System based on COBIT
inferredcites →https://doi.org/10.1109/iciteed.2018.8534785openalex-snapshot
Mobile App Review Labeling Using LDA Similarity and Term Frequency-Inverse Cluster Frequency (TF-ICF)
inferredcites →https://doi.org/10.1109/icsm.2015.7332474openalex-snapshot
How can i improve my app? Classifying user reviews for software maintenance and evolution
inferredcites →https://doi.org/10.1109/inaes.2016.7821927openalex-snapshot
Software feature extraction using infrequent feature extraction
inferredcites →https://doi.org/10.1109/jcsse.2019.8864199openalex-snapshot
User Story Extraction from Online News for Software Requirements Elicitation: A Conceptual Model
inferredcites →https://doi.org/10.1109/re.2013.6636712openalex-snapshot
User feedback in the appstore: An empirical study
inferredcites →https://doi.org/10.1109/re.2014.6912257openalex-snapshot
How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews
inferredcites →https://doi.org/10.1109/re.2016.67openalex-snapshot
A Needle in a Haystack: What Do Twitter Users Say about Software?
inferredcites →https://doi.org/10.1109/re.2017.71openalex-snapshot
SAFE: A Simple Approach for Feature Extraction from App Descriptions and App Reviews
inferredcites →https://doi.org/10.1145/2110147.2110153openalex-snapshot
On extracting feature models from product descriptions
inferredcites →https://doi.org/10.1145/2491411.2491455openalex-snapshot
Feature model extraction from large collections of informal product descriptions
inferredcites →https://doi.org/10.1145/2568225.2568263openalex-snapshot
AR-miner: mining informative reviews for developers from mobile app marketplace
inferredcites →https://doi.org/10.1145/2915970.2916003openalex-snapshot
Approaches for prioritizing feature improvements extracted from app reviews
inferredcites →https://doi.org/10.1145/3457784.3457796openalex-snapshot
Software Requirement-Related Information Extraction from Online News using Domain Specificity for Requirements Elicitation
inferredcites →https://doi.org/10.20473/jisebi.6.1.27-36openalex-snapshot
Tool for Generating Behavior-Driven Development Test-Cases
inferredcites →https://doi.org/10.20473/jisebi.6.2.112-122openalex-snapshot
Tweets Responding to the Indonesian Government’s Handling of COVID-19: Sentiment Analysis Using SVM with Normalized Poly Kernel
inferredcites →https://doi.org/10.3390/computers8030055openalex-snapshot
Semantic Features for Optimizing Supervised Approach of Sentiment Analysis on Product Reviews
inferredcites →https://doi.org/10.3390/e22091057openalex-snapshot
Software Requirements Classification Using Machine Learning Algorithms
inferredcites →https://doi.org/10.3390/mca23010011openalex-snapshot
Machine Learning-Based Sentiment Analysis for Twitter Accounts
inferredcites →https://doi.org/10.5381/jot.2006.5.6.a1openalex-snapshot
A Classification Framework for Software Reuse.
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s10115-026-02747-9openalex-snapshot
Mining conflicting opinions from user reviews: a semantic rule-based framework for software requirements engineering
inferred← citeshttps://doi.org/10.1016/j.infsof.2023.107195openalex-snapshot
User story extraction from natural language for requirements elicitation: Identify software-related information from online news
inferred← citeshttps://doi.org/10.1016/j.jenvman.2024.122228openalex-snapshot
A deep learning classification framework for research methods of marine protected area management
inferred← citeshttps://doi.org/10.1063/5.0103679openalex-snapshot
An investigation of class diagram builder system from the translation of BPMN and database
inferred← citeshttps://doi.org/10.1063/5.0103685openalex-snapshot
BPMN2 user story: Web application for generate user story from BPMN
inferred← citeshttps://doi.org/10.1063/5.0195320openalex-snapshot
Capturing emotion in user requirement through emotion map for solo software developer
inferred← citeshttps://doi.org/10.1063/5.0308679openalex-snapshot
Generating user story scenario from SALT GUI
inferred← citeshttps://doi.org/10.1109/iccsce58721.2023.10237097openalex-snapshot
A Comparison of Deep Learning for Software Features Extraction in Forensic Online News
inferred← citeshttps://doi.org/10.1109/icitce65255.2025.11210802openalex-snapshot
Statistical Regression Model: Factors that Influence the Classification of Informative App User Reviews
inferred← citeshttps://doi.org/10.1109/iscit63075.2024.10793700openalex-snapshot
Imbalanced Dataset Handling in Forensic Software Features Extraction
inferred← citeshttps://doi.org/10.12962/j20882033.v32i3.13003openalex-snapshot
A Semantic Comparison of Feature Requirements Extraction Methods
inferred← citeshttps://doi.org/10.18421/tem114-27openalex-snapshot
Influences of Social Learning on Customer’s Intention to Download an Application from a Start-up Company
inferred← citeshttps://doi.org/10.18421/tem121-39openalex-snapshot
Conversion of User Story Scenarios to Python-Based Selenium Source Code for Automated Testing
inferred← citeshttps://doi.org/10.20895/infotel.v15i3.950openalex-snapshot
Extracting software requirements-related information from online news using DomText-WMDS
inferred← citeshttps://doi.org/10.3390/computers14090374openalex-snapshot
Bridging Domains: Advances in Explainable, Automated, and Privacy-Preserving AI for Computer Science and Cybersecurity
inferred← citeshttps://doi.org/10.7717/peerj-cs.2401openalex-snapshot
Mobile app review analysis for crowdsourcing of software requirements: a mapping study of automated and semi-automated tools
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