On-demand feature recommendations derived from mining public product descriptions

@article{Dumitru2011OndemandFR,
  title={On-demand feature recommendations derived from mining public product descriptions},
  author={Horatiu Dumitru and Marek Gibiec and Negar Hariri and Jane Cleland-Huang and Bamshad Mobasher and Carlos Castro-Herrera and Mehdi Mirakhorli},
  journal={2011 33rd International Conference on Software Engineering (ICSE)},
  year={2011},
  pages={181-190}
}
We present a recommender system that models and recommends product features for a given domain. Our approach mines product descriptions from publicly available online specifications, utilizes text mining and a novel incremental diffusive clustering algorithm to discover domain-specific features, generates a probabilistic feature model that represents commonalities, variants, and cross-category features, and then uses association rule mining and the k-Nearest-Neighbor machine learning strategy… 

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