This unit is a duplicate unit of FIT5212. The ITIxxxx units have been created for the Monash Indonesia offering of the Master of Data Science due to the different teaching mode.

On successful completion of this unit, you should be able to:

1. appraise what kinds of semi-structured data exist and the problems they present for analysis;
2. analyse different kinds of algorithms for different kinds of semi-structured data;
3. develop and modify some standard algorithms for semi-structured data;
4. examine some characteristic industry problems involving semi-structured data, and analyse the suitability of different algorithms.

020119

Semi-structured data is one of the fastest growing kinds of data in both the public and private sector, for instance in health. Email collections with sender-recipient graphs, metadata and text content is one example. This unit will explore basic forms of semi-structured data: text, time-sequence data, graphs and multiple relations in a database. Basic machine learning algorithms for these kinds of data will be analysed and applied. Some characteristic industry problems for the application of semi-structured data will also be investigated such as cohort analysis and market-basket analysis.

On-campus

Examination (2 hours and 10 minutes): 50%; in-semester assessment: 50%

Minimum total expected workload equals 12 hours per week comprising:

• Two hours/week lectures
• Two hours/week laboratories

FIT

ITI5197