Concept Mining: Fundamentals and Applications
Podrobnosti o e‑knize
An activity known as idea mining is one in which concepts are extracted from artifacts for the purpose of analysis. Aspects of artificial intelligence and statistics, such as data mining and text mining, are frequently incorporated into the approaches taken to solve the problem. The problem is not easy to solve since artifacts are often a loosely structured sequence of words and other symbols; yet, solving it can yield valuable insights into the meaning, provenance, and similarity of documents. Artifacts are typically loosely structured sequences of words and other symbols.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Concept Mining
Chapter 2: Text Mining
Chapter 3: Word-sense Disambiguation
Chapter 4: Latent Semantic Analysis
Chapter 5: Sentiment Analysis
Chapter 6: Unstructured Data
Chapter 7: Knowledge Extraction
Chapter 8: Explicit Semantic Analysis
Chapter 9: Automatic Summarization
Chapter 10: Word2vec
(II) Answering the public top questions about concept mining.
(III) Real world examples for the usage of concept mining in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of concept mining' technologies.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of concept mining.
