Machine Learning@MendeleyPart I: Introduction

Presenter Name: Kris Jack (@_krisjack), Lili Tcheang and Maya HristakevaPresenter Title: Chief Data Scientist, Data Analyst, Senior Data ScientistDate: 01/10/14

What is Machine Learning (ML)?

• Applications of Machine Learning– Spam Detection for Email– Personalised Search (e.g.

Google, Bing)– Speech Recognition– Recommender System (e.g.

Amazon, Netflix)• Definition:– Software that improves itself

with experience (e.g. exposure to new data)

Why is ML Important to Mendeley?

• Information Extraction– Metadata extraction

• Catalogue:– Crowdsourcing– Duplicate detection

• User Profiling– Descriptive and Predictive

• Recommendations– Contextualise research– Make new discoveries

A Closer Look at 2 ML Applications

• User Profiling:– What are our users currently

doing with Mendeley?

• Recommender Systems:– How are we helping

researchers with their work?

Machine Learning@MendeleyPart II: What kind of User are you?User ProfilingPresenter Name: Kris Jack (@_krisjack), Lili Tcheang and Maya HristakevaPresenter Title: Chief Data Scientist, Data Analyst, Senior Data ScientistDate: 01/10/14

Here’s What We Did…

•Take 2000 users.•Extract 40 activities recorded for those 2000 users.•See how those users cluster according to their activities.

What were those activities?

• Social– Group invites– New followee– Posts– etc

• Productivity– Reading– Writing– Search– etc

Here’s how people cluster

-0.4 0.1 0.6 1.1-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

More Productivity

Mor

e So

cial

Social

ProductivityBoth

Why is this interesting?

Career Progression

Student PhD Student Post Doc Professor

Social

Productivity

Both

Librarian Other

Machine Learning@MendeleyPart III: Recommendations

Presenter Name: Kris Jack (@_krisjack), Lili Tcheang and Maya HristakevaPresenter Title: Chief Data Scientist, Data Analyst, Senior Data ScientistDate: 01/10/14

Recommendations @ Mendeley

• Mendeley Suggest• Related Research• Mendeley Digest• People Recommender

Recommendations @ Mendeley

• Mendeley Suggest• Related Research• Mendeley Digest • People Recommender

Recommendations @ Mendeley

• Mendeley Suggest• Related Research• Mendeley Digest• People Recommender

Recommendations @ Mendeley

• Mendeley Suggest• Related Research• Mendeley Digest• People Recommender

Recommendations @ Mendeley

• Mendeley Suggest• Related Research• Mendeley Digest• People Recommender

your coauthors authors of the paper you are

reading (i.e. real-time)

your colleagues

authors of work that interests

you

Authors you

cited/were cited by

Authors who are influential/

trending in your field

Authors who your

influencers follow

Recommendations @ Mendeley

• Mendeley Suggest• Related Research• Mendeley Digest• People Recommender

ML @ Mendeley

• Information Extraction– Metadata extraction

• Catalogue:– Crowdsourcing– Duplicate detection

• User Profiling– Descriptive and Predictive

• Recommendations– Contextualise research– Make new discoveries

Thank you for your timewww.mendeley.com