Course Details
Course Code: ANLY610 Course ID: 4876 Credit Hours: 3 Level: Graduate
This course covers the elements of text mining techniques used to complement data mining methods but for unstructured text. The essential transformation techniques where text is prepared and handled to a form in which it can be mined is discussed and explained. Additionally, some standard techniques and excel functions will be also covered. (Prerequisite: BUSN662)
Prerequisites
Course Schedule
| Registration Dates | Course Dates | Start Month | Session | Weeks |
|---|---|---|---|---|
| 03/29/2022 - 09/02/2022 | 09/05/2022 - 10/30/2022 | September | Summer 2022 Session D | 8 Week session |
| 06/28/2022 - 12/02/2022 | 12/05/2022 - 01/29/2023 | December | Fall 2022 Session D | 8 Week session |
Current Syllabi
After successfully completing this course, you will be able to
- LO 1: Describe,using R, basic concepts and methods in text mining, for example document representation, information extraction, text classification and clustering, and topic modeling.
- LO 2: Use benchmark corpora, commercial and open-source text analysis and visualization tools to explore interesting patterns.
- LO 3: Understand conceptually the mechanism of advanced text mining algorithms for information extraction, text classification and clustering, opinion mining, and their applications in real-world problems.
- LO 4: Choose appropriate technologies for specific text analysis tasks, and evaluate the benefit and challenges of the chosen technical solution.
After successfully completing this course, you will be able to
- LO 1: Describe,using R, basic concepts and methods in text mining, for example document representation, information extraction, text classification and clustering, and topic modeling.
- LO 2: Use benchmark corpora, commercial and open-source text analysis and visualization tools to explore interesting patterns.
- LO 3: Understand conceptually the mechanism of advanced text mining algorithms for information extraction, text classification and clustering, opinion mining, and their applications in real-world problems.
- LO 4: Choose appropriate technologies for specific text analysis tasks, and evaluate the benefit and challenges of the chosen technical solution.
| Book Title: | Text Mining and Visualization: Case Studies Using Open-Source Tools - e-book available in the APUS Online Library |
| ISBN: | 9781482237573 |
| Publication Info: | CRC Press Lib |
| Author: | Hofmann and Chisholm |
| Unit Cost: | $101.35 |