
Contents
-
-
-
-
-
-
-
-
-
-
-
13.1 Introduction 13.1 Introduction
-
13.2 Supervised Learning for Categorization 13.2 Supervised Learning for Categorization
-
13.2.1 Decision Tree Induction 13.2.1 Decision Tree Induction
-
13.2.2 Rule Induction 13.2.2 Rule Induction
-
13.2.3 Instance-Based Categorization 13.2.3 Instance-Based Categorization
-
-
13.3 Unsupervised Learning by Clustering 13.3 Unsupervised Learning by Clustering
-
13.3.1 Hierarchical Agglomerative Clustering 13.3.1 Hierarchical Agglomerative Clustering
-
13.3.2 K-Means Clustering 13.3.2 K-Means Clustering
-
-
13.4 Applications to Computational Linguistics 13.4 Applications to Computational Linguistics
-
13.4.1 Morphology 13.4.1 Morphology
-
13.4.2 Part-of-Speech Tagging 13.4.2 Part-of-Speech Tagging
-
13.4.3 Word-Sense Disambiguation 13.4.3 Word-Sense Disambiguation
-
13.4.4 Syntactic Parsing 13.4.4 Syntactic Parsing
-
13.4.5 Semantic Parsing 13.4.5 Semantic Parsing
-
13.4.6 Information Extraction 13.4.6 Information Extraction
-
13.4.7 Anaphora Resolution 13.4.7 Anaphora Resolution
-
-
13.5 Further Reading and Relevant Resources 13.5 Further Reading and Relevant Resources
-
References References
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
13 Machine Learning
Get accessRaymond J. Mooney is a Professor in the Department of Computer Science at the University of Texas at Austin. He received his PhD in 1988 from the University of Illinois at Urbana/Champaign. He is an author of over 170 published research papers, primarily in the areas of machine learning and natural language processing. He was President of the International Machine Learning Society from 2008 to 2011 and is a Fellow of AAAI, ACM, and ACL.
-
Published:05 April 2018
Cite
Abstract
This chapter introduces symbolic machine learning in which decision trees, rules, or case-based classifiers are induced from supervised training examples. It describes the representation of knowledge assumed by each of these approaches and reviews basic algorithms for inducing such representations from annotated training examples and using the acquired knowledge to classify future instances. It also briefly reviews unsupervised learning, in which new concepts are formed from unannotated examples by clustering them into coherent groups. These techniques can be applied to learn knowledge required for a variety of problems in computational linguistics ranging from part-of-speech tagging and syntactic parsing to word sense disambiguation and anaphora resolution. Applications to a variety of these problems are reviewed.
Sign in
Personal account
- Sign in with email/username & password
- Get email alerts
- Save searches
- Purchase content
- Activate your purchase/trial code
- Add your ORCID iD
Purchase
Our books are available by subscription or purchase to libraries and institutions.
Purchasing informationMonth: | Total Views: |
---|---|
October 2022 | 12 |
November 2022 | 9 |
December 2022 | 10 |
January 2023 | 19 |
February 2023 | 9 |
March 2023 | 10 |
April 2023 | 7 |
May 2023 | 4 |
June 2023 | 17 |
July 2023 | 10 |
August 2023 | 6 |
September 2023 | 1 |
October 2023 | 11 |
November 2023 | 7 |
December 2023 | 2 |
January 2024 | 4 |
February 2024 | 5 |
March 2024 | 19 |
April 2024 | 8 |
May 2024 | 17 |
June 2024 | 28 |
July 2024 | 10 |
August 2024 | 13 |
September 2024 | 9 |
October 2024 | 13 |
November 2024 | 4 |
December 2024 | 7 |
January 2025 | 9 |
February 2025 | 2 |
March 2025 | 15 |
April 2025 | 16 |
May 2025 | 9 |
Get help with access
Institutional access
Access to content on Oxford Academic is often provided through institutional subscriptions and purchases. If you are a member of an institution with an active account, you may be able to access content in one of the following ways:
IP based access
Typically, access is provided across an institutional network to a range of IP addresses. This authentication occurs automatically, and it is not possible to sign out of an IP authenticated account.
Sign in through your institution
Choose this option to get remote access when outside your institution. Shibboleth/Open Athens technology is used to provide single sign-on between your institution’s website and Oxford Academic.
If your institution is not listed or you cannot sign in to your institution’s website, please contact your librarian or administrator.
Sign in with a library card
Enter your library card number to sign in. If you cannot sign in, please contact your librarian.
Society Members
Society member access to a journal is achieved in one of the following ways:
Sign in through society site
Many societies offer single sign-on between the society website and Oxford Academic. If you see ‘Sign in through society site’ in the sign in pane within a journal:
If you do not have a society account or have forgotten your username or password, please contact your society.
Sign in using a personal account
Some societies use Oxford Academic personal accounts to provide access to their members. See below.
Personal account
A personal account can be used to get email alerts, save searches, purchase content, and activate subscriptions.
Some societies use Oxford Academic personal accounts to provide access to their members.
Viewing your signed in accounts
Click the account icon in the top right to:
Signed in but can't access content
Oxford Academic is home to a wide variety of products. The institutional subscription may not cover the content that you are trying to access. If you believe you should have access to that content, please contact your librarian.
Institutional account management
For librarians and administrators, your personal account also provides access to institutional account management. Here you will find options to view and activate subscriptions, manage institutional settings and access options, access usage statistics, and more.