journal-matchmaker

# Journal Matchmaker

Analyzes academic paper abstracts to recommend optimal journals for submission, considering impact factors, scope alignment, and domain expertise.

## Use Cases

- Find the best-fit journal for a new manuscript
- Identify high-impact factor journals in specific research areas
- Compare journal scopes against paper content
- Discover domain-specific publication venues

## Usage

```bash
python scripts/main.py --abstract "Your paper abstract text here" [--field "field_name"] [--min-if 5.0] [--count 5]
```

### Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| `--abstract` | str | Yes | - | Paper abstract text to analyze |
| `--field` | str | No | Auto-detect | Research field (e.g., "computer_science", "biology") |
| `--min-if` | float | No | 0.0 | Minimum impact factor threshold |
| `--max-if` | float | No | None | Maximum impact factor (optional) |
| `--count` | int | No | 5 | Number of recommendations to return |
| `--format` | str | No | table | Output format: table, json, markdown |

## Examples

```bash
# Basic usage
python scripts/main.py --abstract "This paper presents a novel deep learning approach..."

# Specify field and minimum impact factor
python scripts/main.py --abstract "abstract.txt" --field "ai" --min-if 10.0 --count 10

# Output as JSON for integration
python scripts/main.py --abstract "..." --format json
```

## How It Works

1. **Abstract Analysis**: Extracts key terms, methodology, and research focus
2. **Field Classification**: Identifies the primary research domain
3. **Journal Matching**: Compares content against journal scopes and aims
4. **Impact Factor Filtering**: Applies IF constraints if specified
5. **Ranking**: Scores and ranks journals by relevance and impact

## Technical Details

- **Difficulty**: Medium
- **Approach**: Keyword extraction + journal database matching
- **Data Source**: Journal metadata from references/journals.json
- **A...