On Cross-Domain Transfer in Venue Recommendation

Jarana Manotumruksa*, Dimitrios Rafailidis, Craig Macdonald, Iadh Ounis

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic


Venue recommendation strategies are built upon collaborative filtering techniques that rely on matrix factorisation (mf), to model users’ preferences. Various cross-domain strategies have been proposed to enhance the effectiveness of mf-based models on a target domain, by transferring knowledge from a source domain. Such cross-domain recommendation strategies often require user overlap, that is common users on the different domains. However, in practice, common users across different domains may not be available. To tackle this problem, recently, several cross-domains strategies without users’ overlaps have been introduced. In this paper, we investigate the performance of state-of-the-art cross-domain recommendation that do not require overlap of users for the venue recommendation task on three large location-based social networks (lbsn) datasets. Moreover, in the context of cross-domain recommendation we extend a state-of-the-art sequential-based deep learning model to boost the recommendation accuracy. Our experimental results demonstrate that state-of-the-art cross-domain recommendation does not clearly contribute to the improvements of venue recommendation systems, and, further we validate this result on the latest sequential deep learning-based venue recommendation approach. Finally, for reproduction purposes we make our implementations publicly available.keywordscross-domain recommendationvenue suggestiontransfer learning.
Original languageEnglish
Title of host publicationAdvances in Information Retrieval
Subtitle of host publicationECIR 2019. Lecture Notes in Computer Science
EditorsL. Azzopardi, B. Stein, N. Fuhr, P. Mayr, C. Hauff, D. Hiemstra
PublisherSpringer, Cham
ISBN (Electronic)978-3-030-15712-8
ISBN (Print)978-3-030-15711-1
Publication statusPublished - 2019
EventEuropean Conference on Information Retrieval Research - Cologne, Germany
Duration: 14 Apr 201918 Apr 2019

Publication series

SeriesLecture Notes in Computer Science


ConferenceEuropean Conference on Information Retrieval Research
Abbreviated titleECIR 2019


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