Memory-Augmented Neural Networks for Predictive Process Analytics

02/03/2018
by   Asjad Khan, et al.
0

Process analytics involves a sophisticated layer of data analytics built over the traditional notion of process mining. The flexible execution of business process instances involves multiple critical decisions including what task to perform next and what resources to allocate to a task. In this paper, we explore the application of deep learning techniques for solving various process analytics related problems. Based on recent advances in the field we specifically look at memory-augmented neural networks (MANN)s and adapt the latest model to date, namely the Differential Neural Computer. We introduce two modifications to account for a variety of tasks in predictive process analytics: (i) separating the encoding phase and decoding phase, resulting dual controllers, one for each phase; (ii) implementing a write-protected policy for the memory during the decoding phase. We demonstrate the feasibility and usefulness of our approach by solving a number of common process analytics tasks such as next activity prediction, time to completion and suffix prediction. We also introduce the notion of MANN based process analytics recommendation machinery that once deployed can serve as an effective business process recommendation engine enabling organizations to answer various prescriptive process analytics related questions.Using real-world datasets, we benchmark our results against those obtained from the state-of-art methods. We show that MANNs based process analytics methods can acheive state-of-the-art performance and have a lot of value to offer for enterprise specific process anlaytics applications.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/31/2019

Towards a Predictive Patent Analytics and Evaluation Platform

The importance of patents is well recognised across many regions of the ...
research
02/11/2018

Dual Control Memory Augmented Neural Networks for Treatment Recommendations

Machine-assisted treatment recommendations hold a promise to reduce phys...
research
06/28/2018

Deep learning in business analytics and operations research: Models, applications and managerial implications

Business analytics refers to methods and practices that create value thr...
research
01/25/2023

A Survey of Process-Oriented Data Science and Analytics for supporting Business Process Management

Process analytics approaches allow organizations to support the practice...
research
03/28/2014

DimmWitted: A Study of Main-Memory Statistical Analytics

We perform the first study of the tradeoff space of access methods and r...
research
11/15/2018

Curricular Analytics: A Framework for Quantifying the Impact of Curricular Reforms and Pedagogical Innovations

In this paper we articulate a framework for quantifying the complexity o...
research
03/28/2023

Enabling Inter-organizational Analytics in Business Networks Through Meta Machine Learning

Successful analytics solutions that provide valuable insights often hing...

Please sign up or login with your details

Forgot password? Click here to reset