SSMF: Shifting Seasonal Matrix Factorization

10/25/2021
by   Koki Kawabata, et al.
0

Given taxi-ride counts information between departure and destination locations, how can we forecast their future demands? In general, given a data stream of events with seasonal patterns that innovate over time, how can we effectively and efficiently forecast future events? In this paper, we propose Shifting Seasonal Matrix Factorization approach, namely SSMF, that can adaptively learn multiple seasonal patterns (called regimes), as well as switching between them. Our proposed method has the following properties: (a) it accurately forecasts future events by detecting regime shifts in seasonal patterns as the data stream evolves; (b) it works in an online setting, i.e., processes each observation in constant time and memory; (c) it effectively realizes regime shifts without human intervention by using a lossless data compression scheme. We demonstrate that our algorithm outperforms state-of-the-art baseline methods by accurately forecasting upcoming events on three real-world data streams.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/23/2017

Online Forecasting Matrix Factorization

In this paper the problem of forecasting high dimensional time series is...
research
09/06/2019

Demand Forecasting in the Presence of Systematic Events: Cases in Capturing Sales Promotions

Reliable demand forecasts are critical for the effective supply chain ma...
research
03/07/2023

Fast and Multi-aspect Mining of Complex Time-stamped Event Streams

Given a huge, online stream of time-evolving events with multiple attrib...
research
04/27/2018

Event Forecasting with Pattern Markov Chains

We present a system for online probabilistic event forecasting. We assum...
research
12/05/2020

Biclustering and Boolean Matrix Factorization in Data Streams

We study the clustering of bipartite graphs and Boolean matrix factoriza...
research
09/05/2023

T-SaS: Toward Shift-aware Dynamic Adaptation for Streaming Data

In many real-world scenarios, distribution shifts exist in the streaming...
research
03/05/2019

A Prediction Tournament Paradox

In a prediction tournament, contestants "forecast" by asserting a numeri...

Please sign up or login with your details

Forgot password? Click here to reset