How to Analyze Image Repositories for Keyword Frequency & Trends

Analyzing keyword trends and frequencies in large scanned image archives is critical for compliance audits, business intelligence, and operational reporting. Aspose.OCR Image Text Finder for .NET streamlines this process with robust batch search and reporting features.

Real-World Problem

Manual audit or frequency counting across thousands of images is slow and error-prone—businesses need automated analytics for keyword discovery, compliance, and performance insights.

Solution Overview

Batch scan images for keywords, count and aggregate occurrences, then analyze or visualize trends for actionable insight.

Prerequisites

1. Visual Studio 2019 or later
2. .NET 6.0 or later (or .NET Framework 4.6.2+)
3. Aspose.OCR for .NET from NuGet
4. Keyword list in a text file (e.g., one per line)

PM> Install-Package Aspose.OCR

Step-by-Step Implementation

List<string> keywords = new List<string>(File.ReadAllLines("keywords.txt"));
string[] files = Directory.GetFiles("./archive", "*.png", SearchOption.AllDirectories);

Dictionary<string, int> keywordCounts = new Dictionary<string, int>();
RecognitionSettings settings = new RecognitionSettings();
settings.Language = Language.English;
AsposeOcr ocr = new AsposeOcr();
foreach (string keyword in keywords) keywordCounts[keyword] = 0;
foreach (string file in files)
{
    foreach (string keyword in keywords)
    {
        if (ocr.ImageHasText(file, keyword, settings))
        {
            keywordCounts[keyword]++;
        }
    }
}

using (var writer = new StreamWriter("keyword_frequency.csv"))
{
    writer.WriteLine("Keyword,Count");
    foreach (var kvp in keywordCounts)
    {
        writer.WriteLine($"{kvp.Key},{kvp.Value}");
    }
}

using Aspose.OCR;
using System;
using System.Collections.Generic;
using System.IO;

class Program
{
    static void Main(string[] args)
    {
        List<string> keywords = new List<string>(File.ReadAllLines("keywords.txt"));
        string[] files = Directory.GetFiles("./archive", "*.png", SearchOption.AllDirectories);
        Dictionary<string, int> keywordCounts = new Dictionary<string, int>();
        foreach (string keyword in keywords) keywordCounts[keyword] = 0;
        RecognitionSettings settings = new RecognitionSettings();
        settings.Language = Language.English;
        AsposeOcr ocr = new AsposeOcr();
        foreach (string file in files)
        {
            foreach (string keyword in keywords)
            {
                if (ocr.ImageHasText(file, keyword, settings))
                    keywordCounts[keyword]++;
            }
        }
        using (var writer = new StreamWriter("keyword_frequency.csv"))
        {
            writer.WriteLine("Keyword,Count");
            foreach (var kvp in keywordCounts)
            {
                writer.WriteLine($"{kvp.Key},{kvp.Value}");
            }
        }
    }
}

Use Cases and Applications

Compliance and Policy Audits

Track how often sensitive terms appear across digital archives.

Business Intelligence

Analyze trends in contracts, forms, or communications over time or by source.

Digital Asset Management

Improve searchability and insight for large scanned archives.

Common Challenges and Solutions

Challenge 1: Large Data Volumes

Solution: Schedule off-hours jobs and use robust error handling/logging.

Challenge 2: Incomplete/Noisy Data

Solution: Preprocess images, review outliers, and tune keyword lists.

Challenge 3: Multi-Language or Multi-Category Sets

Solution: Segment analysis by language or content type.

Performance Considerations

• Monitor CPU/disk on big archives
• Parallelize processing if needed
• Visualize results with BI/reporting tools

Best Practices

1. Curate/update keyword lists for your audit
2. Schedule regular reports for trends
3. Visualize trends for actionable insight
4. Back up all data and results securely

Advanced Scenarios

Scenario 1: Time Series or Category-Based Analysis

Track trends by month, year, or document type for deep insight.

Scenario 2: Alerting and Workflow Triggers on Trend Spikes

Trigger alerts if frequency of a term rises unexpectedly.

Conclusion

Aspose.OCR Image Text Finder for .NET enables powerful analytics on scanned archives—empowering compliance, business intelligence, and reporting with actionable keyword frequency and trend data.

For advanced analytics features, visit Aspose.OCR for .NET API Reference .