OpenSiteRec: An Open Dataset for Site Recommendation

TL;DR

OpenSiteRec introduces a comprehensive open dataset for site recommendation, enabling research and benchmarking of various models in a real-world, multi-city context to advance the field.

Contribution

The paper provides the first large-scale, publicly available dataset for site recommendation, along with benchmark experiments and potential application directions.

Findings

Benchmarking shows existing models' performance on OpenSiteRec

OpenSiteRec covers multiple cities and diverse entities

Dataset availability encourages further research in site recommendation

Abstract

As a representative information retrieval task, site recommendation, which aims at predicting the optimal sites for a brand or an institution to open new branches in an automatic data-driven way, is beneficial and crucial for brand development in modern business. However, there is no publicly available dataset so far and most existing approaches are limited to an extremely small scope of brands, which seriously hinders the research on site recommendation. Therefore, we collect, construct and release an open comprehensive dataset, namely OpenSiteRec, to facilitate and promote the research on site recommendation. Specifically, OpenSiteRec leverages a heterogeneous graph schema to represent various types of real-world entities and relations in four international metropolises. To evaluate the performance of the existing general methods on the site recommendation task, we conduct benchmarking experiments of several representative recommendation models on OpenSiteRec. Furthermore, we also highlight the potential application directions to demonstrate the wide applicability of OpenSiteRec. We believe that our OpenSiteRec dataset is significant and anticipated to encourage the development of advanced methods for site recommendation. OpenSiteRec is available online at https://OpenSiteRec.github.io/.