Lexicographic text analysis using non-negative factorisation techniques
- đ¤ Speaker: Sinead Williamson
- đ Date & Time: Thursday 19 January 2006, 15:00 - 16:00
- đ Venue: Ryle Seminar Room, Cavendish Laboratory
Abstract
Non-negative matrix factorisation (NNMF) is proposed as an alternative to Principle Component Analysis for use in latent semantic analysis of large text corpora. NNMF recognises the inherent non-negativity of language data, and has been shown to organise data into easily understood concept groups of words. The representation of articles as a linear superposition of such concept groups provides an intuitive method for comparison between articles.
Series This talk is part of the Inference Group series.
Included in Lists
- All Cavendish Laboratory Seminars
- All Talks (aka the CURE list)
- Biology
- Cambridge Neuroscience Seminars
- Cambridge talks
- Centre for Health Leadership and Enterprise
- Chris Davis' list
- dh539
- dh539
- Featured lists
- Guy Emerson's list
- Hanchen DaDaDash
- Inference Group
- Inference Group Summary
- Interested Talks
- Joint Machine Learning Seminars
- Life Science
- Life Sciences
- Machine Learning Summary
- ME Seminar
- ML
- Neurons, Fake News, DNA and your iPhone: The Mathematics of Information
- Neuroscience
- Neuroscience Seminars
- Neuroscience Seminars
- Required lists for MLG
- rp587
- Ryle Seminar Room, Cavendish Laboratory
- School of Physical Sciences
- Stem Cells & Regenerative Medicine
- Thin Film Magnetic Talks
- yk373's list
Note: Ex-directory lists are not shown.
![[Talks.cam]](/static/images/talkslogosmall.gif)

Sinead Williamson
Thursday 19 January 2006, 15:00-16:00