Entity Retrieval via Type Taxonomy Aware Smoothing
Refereed conference paper presented and published in conference proceedings

替代計量分析
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其它資訊
摘要We investigate the task of ad-hoc entity retrieval from a knowledge base. We propose a type taxonomy aware smoothing method that exploits the hierarchical type information of a knowledge base and integrates into an existing language modelling framework. Unlike most existing type-aware retrieval models, our approach does not require an explicit inference of query type. Instead, it directly encodes the type information into a term-based retrieval model by considering the occurrence of query terms in multi-fielded pseudo documents of entities whose types have connections in the type taxonomy. We conduct experiments on a recent public benchmark dataset with the Wikipedia category information. Preliminary experiment results show that our framework improves the performance of existing models.
出版社接受日期01.03.2018
著者Xinshi LIN, Wai LAM
會議名稱40th European Conference on Information Retrieval (ECIR 2018)
會議開始日26.03.2018
會議完結日29.03.2018
會議地點Grenoble
會議國家/地區法國
會議論文集題名Advances in Information Retrieval (ECIR 2018)
出版年份2018
卷號10772
出版社Springer
頁次773 - 779
國際標準書號978-3-319-76940-0
電子國際標準書號978-3-319-76941-7
國際標準期刊號0302-9743
電子國際標準期刊號1611-3349
語言美式英語

上次更新時間 2021-18-01 於 01:17