- Title Information
- Title
- Unsupervised Linguistic Inference
- Name:
Personal
- Name Part
- Lamar, Michael Taylor
- Role
- Role Term:
Text
- creator
- Origin Information
- Copyright Date
- 2010
- Physical Description
- Extent
- xiii, 152 p.
- digitalOrigin
- born digital
- Note
- Thesis (Ph.D. -- Brown University (2010)
- Name:
Personal
- Name Part
- Bienenstock, Lucien
- Role
- Role Term:
Text
- Director
- Name:
Personal
- Name Part
- Geman, Stuart
- Role
- Role Term:
Text
- Reader
- Name:
Personal
- Name Part
- Charniak, Eugene
- Role
- Role Term:
Text
- Reader
- Name:
Corporate
- Name Part
- Brown University. Applied Mathematics
- Role
- Role Term:
Text
- sponsor
- Genre (aat)
- theses
- Abstract
- This dissertation describes two novel algorithms for fully unsupervised part-of-speech tagging (POST), both of which exceed the performance of the current state-of-the-art models in both accuracy and computational cost. The first iterative algorithm produces a collection of geometric descriptor vectors that characterize each word type along with a clustering of these vectors which provide the inferred POS labels. The second algorithm also produces a clustering of descriptor vectors, but it relies on simple biologically-plausible mechanisms which cause these vectors to self-organize in response to the presentation of natural language data. These biological mechanisms are extended for use in a related algorithm for grammar induction which is shown to perform well on simple context free grammars. Finally, a careful examination of the three most common evaluation criteria for unsupervised POST is included which demonstrates that only one of these three criteria performs satisfactorily.
- Subject
- Topic
- part of speech tagging
- Subject
- Topic
- unsupervised
- Subject (FAST)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/871998")
- Topic
- Computational linguistics
- Record Information
- Record Content Source (marcorg)
- RPB
- Record Creation Date
(encoding="iso8601")
- 20111003
- Language
- Language Term:
Code (ISO639-2B)
- eng
- Language Term:
Text
- English
- Identifier:
DOI
- 10.7301/Z07M0655
- Access Condition:
rights statement
(href="http://rightsstatements.org/vocab/InC/1.0/")
- In Copyright
- Access Condition:
restriction on access
- Collection is open for research.
- Type of Resource (primo)
- dissertations