Learning Maximal Marginal Relevance Model via Directly Optimizing Diversity Evaluation Measures

@inproceedings{Xia2015LearningMM,
  title={Learning Maximal Marginal Relevance Model via Directly Optimizing Diversity Evaluation Measures},
  author={Long Xia and Jun Xu and Yanyan Lan and Jiafeng Guo and Xueqi Cheng},
  booktitle={SIGIR},
  year={2015}
}
In this paper we address the issue of learning a ranking model for search result diversification. In the task, a model concerns with both query-document relevance and document diversity is automatically created with training data. Ideally a diverse ranking model would be designed to meet the criterion of maximal marginal relevance, for selecting documents that have the least similarity to previously selected documents. Also, an ideal learning algorithm for diverse ranking would train a ranking… CONTINUE READING

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