Relevance Criteria for E-Commerce: A Crowdsourcing-based Experimental Analysis

被引：11

作者：

Alonso, Omar ^{[1
]}

Mizzaro, Stefano ^{[1
]}

机构：

[1] A9 Com, Palo Alto, CA USA

来源：

PROCEEDINGS 32ND ANNUAL INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL | 2009年

关键词：

IR evaluation; relevance; relevance criteria; user study; OF-THE-LITERATURE; INFORMATION-SCIENCE; FRAMEWORK; THINKING; NOTION;

D O I：

10.1145/1571941.1572115

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 discuss the concept of relevance criteria in the context of e-Commerce search. A vast body of research literature describes the beyond-topical criteria used to determine the relevance of the document to the need. We argue that in an e-Commerce scenario there are some differences, and novel and different criteria can be used to determine relevance. We experimentally validate this hypothesis by means of Amazon Mechanical Turk using a crowdsourcing approach.

引用

页码：760 / 761

页数：2

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