Information Retrieval Model using Generalized Pareto Distribution and Its Application to Instance Search

被引：0

作者：

Murata, Masaya ^{[1
]}

Hiramatsu, Kaoru ^{[1
]}

Satoh, Shin'ichi ^{[2
]}

机构：

[1] NTT Commun Sci Labs, 3-1 Morinosato Wakamiya, Atsugi, Kanagawa, Japan

[2] Natl Inst Informat, Chiyoda Ku, 2-1-2 Hitotsubashi, Tokyo, Japan

来源：

SIGIR'17: PROCEEDINGS OF THE 40TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL | 2017年

关键词：

Information retrieval; information-based model; divergence from independence; extreme value statistics; generalized Pareto distribution; video retrieval; instance search;

D O I：

10.1145/3077136.3080736

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We. adopt the generalized Pareto distribution for the information-based model and show that the parameters can be estimated based on the mean excess function. The proposed information retrieval model corresponds to the extension of the divergence from independence and is designed to be data-driven. The proposed model is then applied to the specific object search called the instance search and the effectiveness is experimentally confirmed.

引用

页码：1117 / 1120

页数：4

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