[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.
张鹏翼,周翔,王军. 商品检索中的多任务识别与分析*[J]. 现代图书情报技术, 2016, 32(3): 1-7.
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.
(CNNIC. The Research Report of Online Shopping Market in China, 2014 [EB/OL]. [2015-06-30].
[3]
Spink A, Ozmutlu H C, Ozmutlu S.Multitasking Information Seeking and Searching Processes[J]. Journal of the American Society for Information Science and Technology, 2002, 53(8): 639-652.
[4]
Spink A, Park M, Jansen B J.Information Task Switching and Multitasking Web Search[J]. Proceedings of the American Society for Information Science and Technology, 2004, 41(1): 213-217.
(Zhang Wenjun, Wang Jun, Xu Shanchuan.The Probing of E-commerce User Need States by Page Cluster Analysis—— An Empirical Study on Women’s Clothes from Taobao.com[J]. New Technology of Library and Information Service, 2015(3):67-74.)
(Yuan Xingfu, Zhang Pengyi, Liu Honglian, et al.Modeling E-commerce User Session Behaviors Based on Click-through Sequences[J]. Library and Information Service, 2015, 59(1): 119-126.)
[7]
Glance N S.Community Search Assistant [C]. In: Proceedings of the 6th International Conference on Intelligent User Interfaces. New York: ACM, 2001: 91-96.
[8]
Raghavan V V, Sever H.On the Reuse of Past Optimal Queries[C]. In: Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM, 1995:344-350.
[9]
J?rvelin A, J?rvelin A, J?rvelin K.S-grams: Defining Generalized N-grams for Information Retrieval[J]. Information Processing & Management, 2007, 43(4): 1005-1019.
[10]
Jones R, Klinkner K L.Beyond the Session Timeout: Automatic Hierarchical Segmentation of Search Topics in Query Logs [C]. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management. New York: ACM, 2008: 699-708.
[11]
Salton G, McGill M J. Introduction to Modern Information Retrieval[M]. McGraw-Hill Book Company, 1983.
[12]
Lucchese C, Orlando S, Perego R, et al.Identifying Task-based Sessions in Search Engine Query Logs[C]. In: Proceedings of the 4th ACM International Conference on Web Search and Data Mining. New York: ACM, 2011: 277-286.
[13]
Spink A, Park M, Jansen B J, et al.Multitasking During Web Search Sessions[J]. Information Processing & Management, 2006, 42(1): 264-275.
[14]
Ozmutlu S, Ozmutlu H C, Spink A.Multitasking Web Searching and Implications for Design[J]. Proceedings of the American Society for Information Science and Technology, 2003, 40(1): 416-421.
[15]
Ozmutlu S, Ozmutlu H C, Spink A.A Study of Multitasking Web Search [C]. In: Proceedings of International Conference on Information Technology: Coding and Computing (ITCC 2003). Washington DC: IEEE, 2003: 145-148.
[16]
Lin S, Belkin N.Validation of a Model of Information Seeking over Multiple Search Sessions[J]. Journal of the American Society for Information Science and Technology, 2005, 56(4): 393-415.
[17]
Wang H, Song Y, Chang M W, et al.Learning to Extract Cross-session Search Tasks [C]. In: Proceedings of the 22nd International Conference on World Wide Web. Geneva: International World Wide Web Conferences Steering Committee, 2013: 1353-1364.
