Document categorization using Machine learning techniques
In order to gain information from huge amount of text more efficiently and accurately, readers may use a system which can automatically categorize input text files and generate summary for each categories. The more precise outcomes from the system, the more less time spending on searching of reading...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2014
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| Online Access: | http://hdl.handle.net/10356/61495 |
| _version_ | 1811678061971636224 |
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| author | Hu, Jing |
| author2 | Mao, Kezhi |
| author_facet | Mao, Kezhi Hu, Jing |
| author_sort | Hu, Jing |
| collection | NTU |
| description | In order to gain information from huge amount of text more efficiently and accurately, readers may use a system which can automatically categorize input text files and generate summary for each categories. The more precise outcomes from the system, the more less time spending on searching of reading .
In this project, implementing Machine Learning technique – Naïve Bayes learning algorithm--on text classification and generating an extractive summary for each categories are two main functions. Relative research works on Machine Learning and Text Mining are exhibited in details. The experiment results are presented and discussed. Aim to achieving better performance on text mining, future works are also introduced. |
| first_indexed | 2024-10-01T02:47:17Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/61495 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:47:17Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | ntu-10356/614952023-07-07T17:13:02Z Document categorization using Machine learning techniques Hu, Jing Mao, Kezhi School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications In order to gain information from huge amount of text more efficiently and accurately, readers may use a system which can automatically categorize input text files and generate summary for each categories. The more precise outcomes from the system, the more less time spending on searching of reading . In this project, implementing Machine Learning technique – Naïve Bayes learning algorithm--on text classification and generating an extractive summary for each categories are two main functions. Relative research works on Machine Learning and Text Mining are exhibited in details. The experiment results are presented and discussed. Aim to achieving better performance on text mining, future works are also introduced. Bachelor of Engineering 2014-06-10T09:23:41Z 2014-06-10T09:23:41Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/61495 en Nanyang Technological University 74 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications Hu, Jing Document categorization using Machine learning techniques |
| title | Document categorization using Machine learning techniques |
| title_full | Document categorization using Machine learning techniques |
| title_fullStr | Document categorization using Machine learning techniques |
| title_full_unstemmed | Document categorization using Machine learning techniques |
| title_short | Document categorization using Machine learning techniques |
| title_sort | document categorization using machine learning techniques |
| topic | DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications |
| url | http://hdl.handle.net/10356/61495 |
| work_keys_str_mv | AT hujing documentcategorizationusingmachinelearningtechniques |