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New Technology of Library and Information Service  2016, Vol. 32 Issue (3): 1-7    DOI: 10.11925/infotech.1003-3513.2016.03.01
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Multi-task Session Identification and Analysis in Product Search
Zhang Pengyi,Zhou Xiang(),Wang Jun
Department of Information Management, Peking University, Beijing 100871, China
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[Objective] This research aims to identify shopping tasks from product search, and then analyze the characteristic of multi-task sessions. [Methods] Using the product classification of Taobao, and a list of manually selected product terms, we identified online shopping tasks based on query terms from 19 704 search sessions by 2 754 users. [Results] First, factors influence the number of queries per shopping task: product characteristics, the amount of available products, and the difficulty in describing product category with query terms. Second, we found that in sessions with a major task, the relationship among the shopping tasks is closer. [Limitations] The task identification method based on query terms cannot completely describe the complex consumer shopping behaviors. [Conclusions] This study provides an exploratory understanding of the relationships among various shopping tasks, and may be used to improve product recommendation algorithm, as well as predict shopping behaviors.

Key wordsProduct search      Shopping task identification      Shopping task analysis      Multi-task session     
Received: 19 October 2015      Published: 12 April 2016

Cite this article:

Zhang Pengyi,Zhou Xiang,Wang Jun. Multi-task Session Identification and Analysis in Product Search. New Technology of Library and Information Service, 2016, 32(3): 1-7.

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