Exploring the Importance of Entities in Semantic Ranking

@article{Li2019ExploringTI,
  title={Exploring the Importance of Entities in Semantic Ranking},
  author={Zhenyang Li and Guangluan Xu and Xiao Liang and Feng Li and Lei Wang and Daobing Zhang},
  journal={Information},
  year={2019},
  volume={10},
  pages={39}
}
In recent years, entity-based ranking models have led to exciting breakthroughs in the research of information retrieval. Compared with traditional retrieval models, entity-based representation enables a better understanding of queries and documents. However, the existing entity-based models neglect the importance of entities in a document. This paper attempts to explore the effects of the importance of entities in a document. Specifically, the dataset analysis is conducted which verifies the… CONTINUE READING

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Key Quantitative Results

  • Experimental results show that the enhanced toy model and ESR can outperform the two baselines by as much as 4.57% and 2.74% on NDCG@20 respectively, and further experiments reveal that the strength of the enhanced models is more evident on long queries and the queries where ESR fails, confirming the effectiveness of taking the importance of entities into account.

References

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