Machine Learning @ Mendeley
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Transcript of Machine Learning @ Mendeley
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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
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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)
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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
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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?
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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
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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.
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What were those activities?
• Social– Group invites– New followee– Posts– etc
• Productivity– Reading– Writing– Search– etc
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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
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Why is this interesting?
Career Progression
Student PhD Student Post Doc Professor
Social
Productivity
Both
Librarian Other
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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
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Recommendations @ Mendeley
• Mendeley Suggest• Related Research• Mendeley Digest• People Recommender
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Recommendations @ Mendeley
• Mendeley Suggest• Related Research• Mendeley Digest • People Recommender
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Recommendations @ Mendeley
• Mendeley Suggest• Related Research• Mendeley Digest• People Recommender
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Recommendations @ Mendeley
• Mendeley Suggest• Related Research• Mendeley Digest• People Recommender
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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
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Recommendations @ Mendeley
• Mendeley Suggest• Related Research• Mendeley Digest• People Recommender
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ML @ Mendeley
• Information Extraction– Metadata extraction
• Catalogue:– Crowdsourcing– Duplicate detection
• User Profiling– Descriptive and Predictive
• Recommendations– Contextualise research– Make new discoveries
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Thank you for your timewww.mendeley.com