Content Recommendations.md - himent12/FlashGenie GitHub Wiki
๐ฎ Content Recommendations
FlashGenie's Content Recommendations use AI to suggest new flashcards, identify knowledge gaps, and optimize your learning content.
๐ฏ What are Content Recommendations?
Content Recommendations are AI-powered suggestions that:
- Generate new flashcards based on your existing content
- Identify knowledge gaps in your current understanding
- Suggest related topics to expand your knowledge
- Recommend content improvements for existing cards
- Create balanced learning paths across topics
๐ก Key Features
AI-Generated Flashcards
# Generate new flashcard suggestions
python -m flashgenie suggest "Spanish Vocabulary" --cards 5
Sample output:
Suggested Flashcards:
1. Q: ยฟCuรกl es la diferencia entre "ser" y "estar"?
A: "Ser" describes permanent qualities, while "estar" describes temporary states.
2. Q: ยฟCรณmo se forma el subjuntivo presente?
A: Form the subjunctive by taking the yo form of present indicative, drop the -o, and add the opposite vowel endings.
...
Knowledge Gap Detection
# Identify knowledge gaps
python -m flashgenie suggest "Biology" --gaps
Sample output:
Knowledge Gaps Detected:
1. Cell Respiration (connects Mitochondria and Energy concepts)
2. DNA Transcription (prerequisite for RNA Translation)
3. Enzyme Kinetics (builds on Protein Structure)
Topic Expansion
# Get related topic suggestions
python -m flashgenie suggest "Machine Learning" --topics
Sample output:
Related Topics:
1. Neural Networks (High relevance)
2. Gradient Descent (Medium relevance)
3. Overfitting & Regularization (Medium relevance)
4. Feature Engineering (Low relevance)
๐ Using Content Recommendations
Basic Usage
# Get basic card suggestions
python -m flashgenie suggest "History"
Advanced Usage
# Get comprehensive recommendations
python -m flashgenie suggest "Physics" \
--cards 10 \
--gaps \
--topics \
--difficulty medium \
--format detailed
Available Parameters
Parameter | Description | Example |
---|---|---|
--cards |
Number of cards to suggest | --cards 5 |
--gaps |
Identify knowledge gaps | --gaps |
--topics |
Suggest related topics | --topics |
--difficulty |
Target difficulty level | --difficulty medium |
--format |
Output format | --format detailed |
๐ง Recommendation Types
Card Content Suggestions
# Get specific card type suggestions
python -m flashgenie suggest "Math" --card-type definition
Available card types:
- definition - Term explanations
- concept - Deeper understanding
- application - Practical usage
- comparison - Contrasting ideas
- process - Step-by-step procedures
Content Improvement Suggestions
# Get improvement suggestions for existing cards
python -m flashgenie suggest-improvements "Spanish Vocabulary"
Improvement categories:
- Clarity - Clearer wording
- Specificity - More precise information
- Memorability - Easier to remember
- Connections - Related concepts
- Examples - Illustrative examples
Learning Path Recommendations
# Get a recommended learning sequence
python -m flashgenie suggest-path "Programming"
Sample output:
Recommended Learning Path:
1. Basic Syntax (Mastered)
2. Control Structures (In Progress)
3. Functions (Suggested Next)
4. Data Structures (Future)
5. Object-Oriented Programming (Future)
๐งช The Science Behind It
Content Recommendations are powered by:
- Natural Language Processing - Understanding content semantics
- Knowledge Graph Analysis - Mapping concept relationships
- Spaced Repetition Optimization - Timing for new content
- Difficulty Calibration - Appropriate challenge levels
- Learning Path Optimization - Efficient knowledge acquisition
๐ Managing Recommendations
# Accept and add suggested cards
python -m flashgenie accept-suggestions 1,3,5
# Save suggestions for later
python -m flashgenie save-suggestions --output suggestions.json
# Rate suggestion quality
python -m flashgenie rate-suggestions --quality high
๐ฏ Tips for Effective Recommendations
- Start with a focused deck - More specific decks yield better suggestions
- Add detailed tags - Tags improve recommendation relevance
- Rate suggestions - Feedback improves future recommendations
- Balance acceptance - Don't accept all suggestions automatically
- Combine with knowledge graphs - Visualize how suggestions fill gaps
๐ Next Steps
- Adaptive Study Sessions - Create optimized study plans
- Knowledge Graph Visualization - Visualize your knowledge
- Advanced Content Creation - Master flashcard creation
FlashGenie v1.5.0 | Last updated: June 2025