DARE: Domain analysis and reuse environment
Annals of Software Engineering
Concepts and Guidelines of Feature Modeling for Product Line Software Engineering
ICSR-7 Proceedings of the 7th International Conference on Software Reuse: Methods, Techniques, and Tools
The Journal of Machine Learning Research
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Fast maximum margin matrix factorization for collaborative prediction
ICML '05 Proceedings of the 22nd international conference on Machine learning
Top 10 algorithms in data mining
Knowledge and Information Systems
On-Demand Cluster Analysis for Product Line Functional Requirements
SPLC '08 Proceedings of the 2008 12th International Software Product Line Conference
An Exploratory Study of Information Retrieval Techniques in Domain Analysis
SPLC '08 Proceedings of the 2008 12th International Software Product Line Conference
Using Latent Dirichlet Allocation for automatic categorization of software
MSR '09 Proceedings of the 2009 6th IEEE International Working Conference on Mining Software Repositories
Towards ontology learning from folksonomies
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Software traceability with topic modeling
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Mining software engineering data
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 2
Recommender systems with social regularization
Proceedings of the fourth ACM international conference on Web search and data mining
On-demand feature recommendations derived from mining public product descriptions
Proceedings of the 33rd International Conference on Software Engineering
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
On extracting feature models from product descriptions
Proceedings of the Sixth International Workshop on Variability Modeling of Software-Intensive Systems
Decision support for the software product line domain engineering lifecycle
Automated Software Engineering
Recommending source code for use in rapid software prototypes
Proceedings of the 34th International Conference on Software Engineering
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The "Internetware" paradigm is fundamentally changing the traditional way of software development. More and more software projects are developed, maintained and shared on the Internet. However, a large quantity of heterogeneous software resources have not been organized in a reasonable and efficient way. Software feature is an ideal material to characterize software resources. The effectiveness of feature-related tasks will be greatly improved, if a multi-grained feature repository is available. In this paper, we propose a novel approach for organizing, analyzing and recommending software features. Firstly, we construct a Hierarchical rEpository of Software feAture (HESA). Then, we mine the hidden affinities among the features and recommend relevant and high-quality features to stakeholders based on HESA. Finally, we conduct a user study to evaluate our approach quantitatively. The results show that HESA can organize software features in a more reasonable way compared to the traditional and the state-of-the-art approaches. The result of feature recommendation is effective and interesting.