USEing Transfer Learning in Retrieval of Statistical Data

Firsov, Anton; Bugay, Vladimir; Karpenko, Anton

doi:10.1145/3331184.3331427

Cited by 1 publication

(1 citation statement)

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“…There have been a variety of TLA studies in the Web searching field (Bai and Cambazoglu, 2019;Hirsch et al, 2020;Song et al, 2013). Also, substantial click through research studies have been conducted in the field of computer science (Firsov et al, 2019;Huynh et al, 2020). In the e-commerce field, clickstream data analysis has been applied to predict online shopping behaviours including purchasing behaviours (Koehn et al, 2020;Mokryn et al, 2019;Nishimura et al, 2018).…”

Section: Comparison Of Mobile and Desktop Search Behavioursmentioning

confidence: 99%

Mobile vs desktop user search behaviours of the 1300K site, a Korean shopping search engine

Park

Cho

2021

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Purpose This study aims to investigate and compare mobile and desktop user search behaviours of the 1300K site, a Korean shopping search engine, by using transaction log analysis. Design/methodology/approach Transaction logs of 1300K site were collected over a three months’ period, from 1 January to 31 March 2018. The data set of this study consists of 1,149,690 desktop queries, 2,346,938 mobile queries, 2,481,747 desktop browsing activities and 2,550,309 mobile browsing activities. This study quantitatively analyses transaction log of 1300K site. Findings The results of this study show that mobile usage is higher than desktop usage: there are more mobile sessions than desktop sessions and the number of mobile queries is more than double of desktop queries. Overall, mobile query search behaviours are more simple, targeted and focused than desktop query search behaviours. Also, mobile browsing behaviours are more simple and passive than desktop browsing behaviours. However, mobile click behaviours are more active than desktop click behaviours. Originality/value To the best of the authors’ knowledge, this study appears to be the first of its type in Korea that compared search behaviours of a large number of users on desktop computers and mobile phones. To identify various characteristics of user search behaviours, this study analyses users’ directory browsing behaviour and click behaviour as well as query search behaviour. The results of this study can be implemented to address the effective improvement and development of search services and interfaces for different devices.

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Section: Comparison Of Mobile and Desktop Search Behavioursmentioning

confidence: 99%

Mobile vs desktop user search behaviours of the 1300K site, a Korean shopping search engine

Park

Cho

2021

View full text Add to dashboard Cite

show abstract

USEing Transfer Learning in Retrieval of Statistical Data

Cited by 1 publication

References 2 publications

Mobile vs desktop user search behaviours of the 1300K site, a Korean shopping search engine

Mobile vs desktop user search behaviours of the 1300K site, a Korean shopping search engine

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