Event Ticket Price Prediction with Deep Neural Network on Spatial-Temporal Sparse Data

by   Fei Huang, et al.

Event ticket price prediction is important to marketing strategy for any sports team or musical ensemble. An accurate prediction model can help the marketing team to make promotion plan more effectively and efficiently. However, given all the historical transaction records, it is challenging to predict the sale price of the remaining seats at any future timestamp, not only because that the sale price is relevant to a lot of features (seat locations, date-to-event of the transaction, event date, team performance, etc.), but also because of the temporal and spatial sparsity in the dataset. For a game/concert, the ticket selling price of one seat is only observable once at the time of sale. Furthermore, some seats may not even be purchased (therefore no record available). In fact, data sparsity is commonly encountered in many prediction problems. Here, we propose a bi-level optimizing deep neural network to address the curse of spatio-temporal sparsity. Specifically, we introduce coarsening and refining layers, and design a bi-level loss function to integrate different level of loss for better prediction accuracy. Our model can discover the interrelations among ticket sale price, seat locations, selling time, event information, etc. Experiments show that our proposed model outperforms other benchmark methods in real-world ticket selling price prediction.


page 2

page 3

page 7


Prediction-based One-shot Dynamic Parking Pricing

Many U.S. metropolitan cities are notorious for their severe shortage of...

Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market

We present Luce, the first life-long predictive model for automated prop...

STEP: Spatial-Temporal Network Security Event Prediction

Network security events prediction helps network operators to take respo...

Forecasting Crude Oil Price Using Event Extraction

Research on crude oil price forecasting has attracted tremendous attenti...

Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models

Recurrent neural network based solutions are increasingly being used in ...

Context-aware multi-head self-attentional neural network model for next location prediction

Accurate activity location prediction is a crucial component of many mob...

Computing an Optimal Pitching Strategy in a Baseball At-Bat

The field of quantitative analytics has transformed the world of sports ...

Please sign up or login with your details

Forgot password? Click here to reset