1.
STANISLAW GUNER
REAL INSIGHTS INTO
THE WORLD OF
ONLINE TUTORS

2.
STANISLAW GUNER
REAL INSIGHTS INTO THE WORLD OF ONLINE TUTORS.
A comparison of Bayesian and
Non-Bayesian techniques in the
field of Recommendation Systems.
My initial interest in this project stems
from the challenge to combine novel
machine learning algorithms with the
ability to cater to the unique needs of
the application domain. The second
reason is that this domain is well
suited to the development of a Hybrid
Recommendation System (HRS). This
means the end result combines a
variety of information sources available
to the system.
Our focus of the work is to combine
these systems and to evaluate the
practical challenges of working
with Bayesian and Non-Bayesian
frameworks in the context of a RS for
our domain. I hope to show that RS
has more to offer to a business than
just to provide recommendations.
I’m working with Massive Analytic,
who already provide these services
to companies. My work will hopefully
generate a small but significant
improvement in their processes.
Task:
Academically, I’m interested in ways of combining Collaborative Filtering (CF)
with Content Based Systems (CBS). CF aims to learn from the social structure
of the dataset, while CBS is focused on processing complex user inputs (e.g.
natural language). For example, a CF component implements a user-item matrix
factorization model with added information of implicit user signals and temporal
dynamics. As part of CBS, we explore topic models like Latent Dirichlet
Allocation to discover how tutors can be categorized based on the content
of their profiles.
As we work with consumer data we’d like to be able to not only develop
predictive models, but also to offer insights into e.g. what students value in
a tutor or what qualities make up a good teacher. Those insights can inform
development of services or marketing campaigns. Such an approach
transcends traditional understanding of an RS.
Review:
Performance of the system will be compared with effectiveness of an in-
use RS, for which historic recommendations are available. We also aim to
offer an API that will help MyTutorWeb to provide justifications for the given
recommendations. For example, if a factor that dominates a recommendation is
tutors’ GPA, we can display to the user that the tutor ranks in the top percentile
of the available tutors. Finally, studying the topics tutors discuss in their profiles
and the relation of those topics to consumer conversion can aid in informing
prospective tutors on how to write their profiles.

3.
Q&A
WE SAT DOWN WITH STANISLAW AND ASKED HIM A FEW
QUESTIONS ABOUT HIS PROJECT AND ASK WHAT HE
THINKS THE FUTURE HOLDS FOR HIMSELF.
What makes this project unique?
This will be the first RS developed
in the domain of online tutoring.
Academic literature in RS tends to
focus on conceptual strengths of
proposed methods, while I think
it’s valuable to also share practical
considerations of designing a
system from the ground up.
What led you to
where you are today?
The final year of my undergraduate
degree in Economics included
a small course in Business
Intelligence. I immediately liked
that challenge of working with
real data, rather than with
abstract economic models.
What’s the next step?
I’d like to work as a Machine
Learning engineer involved
with projects that require
an understanding of unique
domain characteristics and the
methodological techniques needed
to analyze them. I’d love to be
working in the Natural Language
Processing field. The idea of
understanding language has struck
a chord with me ever since reading
‘Philosophical Investigations’ by
L. Wittgenstein.
What advice would you
give your 18 year old self?
I used to think that by choosing a
particular career you are forced to
make sacrifices by not pursuing
your other interests, which would
then go to waste. In fact, those
other interests are exactly what
makes you unique in the field
you are working on. Having an
unconventional perspective will
help you produce things others
can not.
Who’s your career hero?
Prof. David Barber who teaches
Graphical Models and Applied
Machine Learning. He is someone
who really understand what they
are doing and such remarkable
level of competence is the quality
I value in people the most. He told
me “Don’t push the button, make
the button”.
What excites you about the
opportunities with data today
and in the future?
The growing field of service design.
Services will be built by software
intelligent enough to find patterns
in data. This is starting already with
High Frequency Trading. Business
strategy needs to adapt to a
world that is build on top of these
intelligent systems.
////
“Don’t
push the
button...
make the
button”