Pattern Recognition and Machine Learning
Three important references are associated with neural network learning, pattern recognition and machine learning, and support vector machines.
From Title List to Study Map
A bibliography is more useful when it shows how each reference supports a subject. The three references in this collection are not merely three disconnected book titles. They are associated with three machine learning topics: neural network learning, pattern recognition and machine learning, and support vector machines. Reading the list as a topic-to-reference map makes it easier to decide which book belongs with which area of study.
The central task is to preserve two kinds of information at once: the topic supported by a reference and the bibliographic details that identify the reference.
The Three Topic Connections
| Topic | Associated book |
|---|---|
| Neural network learning | Neural Network Learning: Theoretical Foundations |
| Pattern recognition and machine learning | Pattern recognition and machine learning |
| Support vector machines | An Introduction to Support Vector Machines |
The three topic-to-reference relationships in the collection.
The matching can be checked directly from the listed titles and their stated associations. The first title is associated with neural network learning, the second with pattern recognition and machine learning, and the third with support vector machines. This matching is the basic state of the collection: every topic has a corresponding reference.
A Topic-Based Bibliography
Topic-based organization adds structure above the individual entries. Instead of scanning one undifferentiated list, a learner can first choose a subject area and then consult the reference associated with that area. In this collection, the three topic groups are neural network learning, pattern recognition and machine learning, and support vector machines.
Checking a Reference Entry
Sorting the Three Listed Books
Build a topic-based study collection from the three listed books, then state which bibliographic details should be checked when distinguishing entries.
- 1Step 1: Identify the topic groups
Create three groups: neural network learning, pattern recognition and machine learning, and support vector machines.
- 2Step 2: Match the titles
Place Neural Network Learning: Theoretical Foundations with neural network learning, Pattern recognition and machine learning with pattern recognition and machine learning, and An Introduction to Support Vector Machines with support vector machines.
- 3Step 3: Check identity fields
For each reference, use the author, year, title, and publisher or publication information to distinguish it from other entries.
- 4Step 4: Notice the available evidence
The supplied collection identifies the three titles and their topic associations, but it does not provide the individual authors, years, or publishers. Those fields therefore cannot be filled in from this source pack without consulting additional bibliographic information.
The organized collection has one listed book under each of the three machine learning topics. The title and topic association are available here; author, year, and publisher or publication information must be checked separately when those details are required.
| Identification field | How it helps distinguish a reference | Availability in this source pack |
|---|---|---|
| Author | Identifies who produced the work | Not provided |
| Year | Places the publication in time | Not provided |
| Title | Names the listed work | Provided |
| Publisher or publication information | Adds publication identity | Not provided |
Reference fields that should be preserved when identifying a bibliography entry.
When recording a citation, preserve the author, year, title, and publisher or publication information rather than relying on the title alone. A topic label tells you why the reference belongs in the collection; the bibliographic fields tell you which exact reference it is.
Mistakes in Topic Matching
Common mistake Treating the three titles as an unorganized list
What it looks likeWriting down all three books without associating them with topics
Why it failsThe purpose of the collection is to show which reference supports each machine learning topic.
Do this insteadRecord each title under its associated topic.
Common mistake Matching a book to a topic without checking the title
What it looks likeAssociating An Introduction to Support Vector Machines with neural network learning
Why it failsThe collection associates that book with support vector machines.
Do this insteadUse the stated topic-to-reference relationships: Neural Network Learning: Theoretical Foundations with neural network learning, Pattern recognition and machine learning with pattern recognition and machine learning, and An Introduction to Support Vector Machines with support vector machines.
Common mistake Inventing missing citation details
What it looks likeAdding an author, year, or publisher that is not present in the supplied information
Why it failsAccurate citation identification depends on preserving real author, year, title, and publisher or publication information.
Do this insteadMark unavailable fields as needing verification and consult additional bibliographic information before completing the entry.
Common mistake Using topic organization as a substitute for citation identity
What it looks likeAssuming that a topic label alone is a complete reference
Why it failsA topic explains the subject supported by the book, but author, year, title, and publisher or publication information distinguish the entry.
Do this insteadKeep both the topic association and the identifying citation fields.
Practice the Matching Process
Create a three-row study table. Put one topic in each row, match the correct book to it, and list the citation fields you would verify before treating the entry as complete.
Hints
- Use the title wording to identify the three listed books.
- The three topic groups are neural network learning, pattern recognition and machine learning, and support vector machines.
- The identity fields to verify are author, year, title, and publisher or publication information.
- 1A correct answer should place Neural Network Learning: Theoretical Foundations under neural network learning, Pattern recognition and machine learning under pattern recognition and machine learning, and An Introduction to Support Vector Machines under support vector machines. It should also distinguish topic grouping from full citation identification and recognize that author, year, title, and publisher or publication information should be checked.
Key Takeaways
- The collection lists three books: Neural Network Learning: Theoretical Foundations, Pattern recognition and machine learning, and An Introduction to Support Vector Machines.
- The books are associated respectively with neural network learning, pattern recognition and machine learning, and support vector machines.
- Organizing a bibliography by topic turns separate references into a more usable study collection.
- Author, year, title, and publisher or publication information should be preserved to distinguish reference entries.
- The supplied source identifies the titles and topic relationships but does not provide the individual authors, years, or publishers.