Buzzmatch : File Content-Based with Image and Text Filtering Categorization Application Through Keyword Matching Using Modified Artificial Bee Colony (ABC) Approach /
Espinosa, Joesef Andrei
Buzzmatch : File Content-Based with Image and Text Filtering Categorization Application Through Keyword Matching Using Modified Artificial Bee Colony (ABC) Approach / Joesef Andrei Espinosa, Rasheed Riga, Jan Christian Torres, Jon Rexzel Valloyaz. - ix, 81 pages : illustrations ; 29 cm. + 1 CD-ROM (4 3/4 in.)
Thesis (Undergraduate)
College of Science --
Includes bibliographical references.
"This study focuses on providing assistance in efficiently categorizing and organizing PDF, MS Docx and TXT files based on image and text filtering. The researchers of this study found that there are professionals such as professors and students that have a hard time finding and retrieving electronic text-based documents. The main objective of this study is to develop a computer application that provides the user with categorizing electronic text-based documents by content. The system was developed using python and Tkinter framework, The system can automatically read and categorize the content of the documents. The evaluation criteria were based on ISO 25010 and the application is tested in terms of functional suitability, performance efficiency, usability, reliability, and maintainability. The level of acceptability of the system was graded with a mean rating of 3.53 which was interpreted as highly acceptable." -- Author's Abstract
BTH QA 76 / E87 2024
Buzzmatch : File Content-Based with Image and Text Filtering Categorization Application Through Keyword Matching Using Modified Artificial Bee Colony (ABC) Approach / Joesef Andrei Espinosa, Rasheed Riga, Jan Christian Torres, Jon Rexzel Valloyaz. - ix, 81 pages : illustrations ; 29 cm. + 1 CD-ROM (4 3/4 in.)
Thesis (Undergraduate)
College of Science --
Includes bibliographical references.
"This study focuses on providing assistance in efficiently categorizing and organizing PDF, MS Docx and TXT files based on image and text filtering. The researchers of this study found that there are professionals such as professors and students that have a hard time finding and retrieving electronic text-based documents. The main objective of this study is to develop a computer application that provides the user with categorizing electronic text-based documents by content. The system was developed using python and Tkinter framework, The system can automatically read and categorize the content of the documents. The evaluation criteria were based on ISO 25010 and the application is tested in terms of functional suitability, performance efficiency, usability, reliability, and maintainability. The level of acceptability of the system was graded with a mean rating of 3.53 which was interpreted as highly acceptable." -- Author's Abstract
BTH QA 76 / E87 2024