Dataset of Natural Language Queries for E-Commerce

被引：3
|
作者：
Papenmeier, Andrea [1 ]
Kern, Dagmar [1 ]
Hienert, Daniel [1 ]
Sliwa, Alfred [2 ]
Aker, Ahmet [2 ]
Fuhr, Norbert [2 ]
机构：
[1] GESIS Leibniz Inst Social Sci, Cologne, Germany
[2] Univ Duisburg Essen, Duisburg, Germany
来源：
CHIIR '21: PROCEEDINGS OF THE 2021 CONFERENCE ON HUMAN INFORMATION INTERACTION AND RETRIEVAL | 2021年
关键词：
Dataset; Natural Language Query; User Intent; E-Commerce; BOOK;
D O I：
10.1145/3406522.3446043
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Shopping online is more and more frequent in our everyday life. For e-commerce search systems, understanding natural language coming through voice assistants, chatbots or from conversational search is an essential ability to understand what the user really wants. However, evaluation datasets with natural and detailed information needs of product-seekers which could be used for research do not exist. Due to privacy issues and competitive consequences, only few datasets with real user search queries from logs are openly available. In this paper, we present a dataset of 3,540 natural language queries in two domains that describe what users want when searching for a laptop or a jacket of their choice. The dataset contains annotations of vague terms and key facts of 1,754 laptop queries. This dataset opens up a range of research opportunities in the fields of natural language processing and (interactive) information retrieval for product search.
引用
收藏
页码：307 / 311
页数：5
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