Text Mining with MATLAB® 2nd Edition by Rafael E. Banchs 9783030876951 3030876950

Text Mining with MATLAB® 2nd Edition Rafael E. Banchs – Ebook Instant Download/Delivery ISBN(s): 9783030876951, 3030876950

Product details:

• ISBN 10:3030876950
• ISBN 13:9783030876951
• Author: Rafael E. Banchs 

Text Mining with MATLAB®

Table contents:

1 Introduction
1.1 About Text Mining and MATLAB®
1.2 About this Book
1.3 A (very) Brief Introduction to MATLAB®
1.4 The Text Analytics Toolbox™
1.5 Further Reading
1.6 References
Part I: Fundamentals
2 Handling Text Data
2.1 Character and Character Arrays
2.2 Handling Text with Cell Arrays
2.3 Handling Text with Structures
2.4 Handling Text with String Arrays
2.5 Some Useful Functions
2.6 Further Reading
2.7 Proposed Exercises
2.8 References
3 Regular Expressions
3.1 Basic Operators for Matching Characters
3.2 Matching Sequences of Characters
3.3 Conditional Matching
3.4 Working with Tokens
3.5 Further Reading
3.6 Proposed Exercises
3.7 References
4 Basic Operations with Strings
4.1 Searching and Comparing
4.2 Replacement and Insertion
4.3 Segmentation and Concatenation
4.4 Set Operations
4.5 Further Reading
4.6 Proposed Exercises
4.7 References
5 Reading and Writing Files
5.1 Basic File Formats
5.2 Other Useful Formats
5.3 Handling Files and Directories
5.4 Further Reading
5.5 Proposed Exercises
5.6 References
6 The Structure of Language
6.1 Levels of the Linguistic Phenomena
6.2 Morphology and Syntax
6.3 Semantics and Pragmatics
6.4 Further Reading
6.5 Proposed Exercises
6.6 References
Part II: Mathematical Models
7 Basic Corpus Statistics
7.1 Fundamental Properties
7.2 Word Co-occurrences
7.3 Accounting for Order
7.4 Further Reading
7.5 Proposed Exercises
7.6 Short Projects
7.7 References
8 Statistical Models
8.1 Basic n-gram Models
8.2 Discounting
8.3 Model Interpolation
8.4 Topic Models
8.5 Further Reading
8.6 Proposed Exercises
8.7 Short Projects
8.8 References
9 Geometrical Models
9.1 The Term-Document Matrix
9.2 The Vector Space Model
9.3 Association Scores and Distances
9.4 Further Reading
9.5 Proposed Exercises
9.6 Short Projects
9.7 References
10 Dimensionality Reduction
10.1 Vocabulary Pruning and Merging
10.2 The Linear Transformation Approach
10.3 Non-linear Projection Methods
10.4 Embeddings
10.5 Further Reading
10.6 Proposed Exercises
10.7 Short Projects
10.8 References
Part III: Methods and Applications
11 Document Categorization
11.1 Data Collection Preparation
11.2 Unsupervised Clustering
11.3 Supervised Classification in Vector Space
11.4 Supervised Classification in Probability Space
11.5 Further Reading
11.6 Proposed Exercises
11.7 Short Projects
11.8 References
12 Document Search
12.1 Binary Search
12.2 Vector-based Search
12.3 The BM25 Ranking Function
12.4 Cross-language Search
12.5 Further Reading
12.6 Proposed Exercises
12.7 Short Projects
12.8 References
13 Content Analysis
13.1 Dimensions of Analysis
13.2 Polarity Estimation
13.3 Qualifier and Aspect Identification
13.4 Entity, Relation and Definition Extraction
13.5 Further Reading
13.6 Proposed Exercises
13.7 Short Projects
13.8 References
14 Keyword Extraction and Summarization
14.1 Keywords and Word Clouds
14.2 Text Summarization
14.3 Further Reading
14.4 Proposed Exercises
14.5 Short Projects
14.6 References
15 Question Answering and Dialogue
15.1 Question Answering
15.2 Dialogue Systems
15.3 Further Reading
15.4 Proposed Exercises
15.5 Short Projects
15.6 References

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