Information 2019, 10(2), 39; https://doi.org/10.3390/info10020039
Exploring the Importance of Entities in Semantic Ranking
1
Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
2
Key Laboratory of Network Information System Technology (NIST), Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Received: 16 November 2018 / Revised: 7 January 2019 / Accepted: 17 January 2019 / Published: 24 January 2019
Abstract
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 correlation between the importance of entities in a document and document ranking. Then, this paper enhances two entity-based models—toy model and Explicit Semantic Ranking model (ESR)—by considering the importance of entities. In contrast to the existing models, the enhanced models assign the weights of entities according to their importance. 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 [email protected] 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. View Full-Text
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Li, Z.; Xu, G.; Liang, X.; Li, F.; Wang, L.; Zhang, D. Exploring the Importance of Entities in Semantic Ranking. Information 2019, 10, 39.
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