Using contexts similarity to predict relationships between tasks
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Summary
This work investigates the extent to which the similarity of the contexts predicts whether and how the respective tasks are related, and shows that context similarity is roughly as accurate to predict task relationships as comparing the textual content of the task descriptions.
- Type
- article
- Published
- 2017-06-01
- Cited by
- 27
- References
- 56
- Access
- Open access
- OpenAlex
- https://openalex.org/W2559177344
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:33644795
Keywords
Similarity (geometry), Computer science, Natural language processing, Artificial intelligence, Data mining
References
- Software Framework for Topic Modelling with Large Corpora
- Getting Things Done: The Art of Stress-Free Productivity
- Noises in Interaction Traces Data and Their Impact on Previous Research Studies
- Can development work describe itself?
- A contextual approach towards more accurate duplicate bug report detection
- NextBug: a Bugzilla extension for recommending similar bugs
- From documents to tasks: deriving user tasks from document usage patterns
- Work tasks and socio-cognitive relevance: A specific example
- Measuring Retrieval Effectiveness Based on User Preference of Documents
- An empirical study of work fragmentation in software evolution tasks
- Mylar: a degree-of-interest model for IDEs
- Towards understanding programs through wear-based filtering
- An empirical study of required dimensionality for large-scale latent semantic indexing applications
- Resumption strategies for interrupted programming tasks
- Assisting engineers in switching artifacts by using task semantic and interaction history
- A hybrid learning system for recognizing user tasks from desktop activities and email messages
- Detecting and correcting user activity switches: algorithms and interfaces
- Do all task dependencies require coordination? the role of task properties in identifying critical coordination needs in software projects
- Disruption and recovery of computing tasks: field study, analysis, and directions
- Information Needs in Collocated Software Development Teams
Cited by
- Find, understand, and extend development screencasts on YouTube
- On the similarity of software development documentation
- Context-Aware Conversational Developer Assistants
- Problem-based Projects in Computer Programming: Students’ Cooperation, Responsibilities and Dependencies
- Natural language processing (NLP) applied on issue trackers
- A personalized clustering-based and reliable trust-aware QoS prediction approach for cloud service recommendation in cloud manufacturing
- Same-Same But Different: On Understanding Duplicates in Stack Overflow
- A reuse recommendation framework of artifacts based on task similarity to improve R&D performance
- An Intelligently-Focused Crawling for Filtering the e-Learning Documents Using Optimized Hidden Na ̈ıve Bayes Classifier,
- Detecting Developers’ Task Switches and Types
- Automatic identification and description of software developers tasks
- MylynSDP — Process - aware artifact filtering based on interest
- Fernlehren und Fernlernen von Objektorientierter Programmierung (OOP)
- Recognizing Developer Activity Based on Joint Modeling of Code and Command Interactions
- A scheduling-driven approach to efficiently assign bug fixing tasks to developers
- Umschulung zum IHK-Fachinformatiker in Anwendungsentwicklung und Systemintegration
- Task estimation for software company employees based on computer interaction logs
- Issue Link Label Recovery and Prediction for Open Source Software
- Quantifying effectiveness of team recommendation for collaborative software development
- Development iterations based on web augmentation and context tasks
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