DeepPredict:A Zone Preference Prediction System for Online Lodging Platforms  

作　　者：Yihan Ma Hua Sun Yang Chen Jiayun Zhang Yang Xu Xin Wang Pan Hui 

机构地区：[1]School of Computer Science,Fudan University,Shanghai 200433,China [2]Department of Computer Science,University of Helsinki,Helsinki 00014,Finland [3]Department of Computer Science and Engineering,Hong Kong University of Science and Technology,Hong Kong,China

出　　处：《Journal of Social Computing》2021年第1期52-70,共19页社会计算（英文）

基　　金：This work was sponsored by the National Natural Science Foundation of China(Nos.71731004,62072115,61602122,and 61971145);Shanghai Pujiang Program(No.2020PJD005);the Research Grants Council of Hong Kong(No.16214817);the 5GEAR Project and FIT Project from the Academy of Finland.

摘　　要：Online lodging platforms have become more and more popular around the world.To make a booking in these platforms,a user usually needs to select a city first,then browses among all the prospective options.To improve the user experience,understanding the zone preferences of a user's booking behavior will be helpful.In this work,we aim to predict the zone preferences of users when booking accommodations for the next travel.We have two main challenges:(1)The previous works about next information of Points Of Interest(Pals)recommendation are mainly focused on users'historical records in the same city,while in practice,the historical records of a user in the same city would be very sparse.(2)Since each city has its own specific geographical entities,it is hard to extract the structured geographical features of accommodation in different cities.Towards the difficulties,we propose DeepPredict,a zone preference prediction system.To tackle the first challenge,DeepPredict involves users'historical records in all the cities and uses a deep learning based method to process them.For the second challenge,DeepPredict uses HERE places API to get the information of pals nearby,and processes the information with a unified way to get it.Also,the description of each accommodation might include some useful information,thus we use Sent2Vec,a sentence embedding algorithm,to get the embedding of accommodation description.Using a real-world dataset collected from Airbnb,DeepPredict can predict the zone preferences of users'next bookings with a remarkable performance.DeepPredict outperforms the state-of-the-art algorithms by 60%in macro Fl-score.

关 键 词：online lodging platform zone preference prediction deep leaming 

分 类 号：F42[经济管理—产业经济]