Online text and video tutorials are among the most popular and heavily used resources for learning feature-rich software applications (e.g., Photoshop, Weka, AutoCAD, Fusion 360). However, when searching, users can find it difficult to assess whether a tutorial is designed for their level of expertise. TutVis stands for tutorial visualization, which is a Photoshop tutorial browsing system that provides auto-generated information to assist users in the tutorial searching and selection. The provided information is as follows: difficulty level (advanced/beginner), topics covered, length, text complexity, command usage ratio. This information is automatically calculated using different supervised and unsupervised machine learning algorithms.

• The browsing interface is developed using angular js, node js, d3 js, chart js, and bootstrap.
• The training data (1300 text and video tutorials of Photoshop and Fusion 360) are scrapped from 13 different sources.
• The information/features are generated (feature engineering) using the topic modeling algorithm (LDA), readability formulas, and heuristic calculations.
• For the classification of the tutorial’s difficulty Random Forest algorithm is used.
• The classification model can classify a tutorial’s difficulty (advanced/beginner) with 85% accuracy.

Publication Source: Check the publication

This Project’s GitHub Repository

• Application
• NLP
• Angular
• Topic Modeling
• Classification