Update README.md

README.md

@@ -1,46 +1,45 @@
 ---
 license: cc-by-4.0
 task_categories:
-- text-retrieval
-- web-mining
-- text-classification
+  - text-retrieval
+  - text-classification
+  - feature-extraction
 language:
-- ja
-- en
-pretty_name: TakaraSpider Japanese Web Crawl Dataset
+  - ja
+  - en
+pretty_name: "TakaraSpider Japanese Web Crawl Dataset"
 size_categories:
-- 100K<n<1M
+  - 100K<n<1M
 tags:
-- web-crawl
-- japanese
-- multilingual
-- html
-- text-extraction
-- nlp
-- cross-cultural
+  - web-crawl
+  - japanese
+  - multilingual
+  - html
+  - text-extraction
+  - nlp
+  - cross-cultural
 dataset_info:
   features:
-  - name: crawl_id
-    dtype: string
-  - name: timestamp
-    dtype: timestamp[ns, tz=UTC]
-  - name: url
-    dtype: string
-  - name: source_url
-    dtype: string
-  - name: html
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 47700748411
-    num_examples: 257900
-  download_size: 14798581589
-  dataset_size: 47700748411
-configs:
-- config_name: default
+    - name: crawl_id
+      dtype: string
+    - name: timestamp
+      dtype: timestamp[ns, tz=UTC]
+    - name: url
+      dtype: string
+    - name: source_url
+      dtype: string
+    - name: html
+      dtype: string
+  config_name: default
   data_files:
-  - split: train
-    path: data/train-*
+    - split: train
+      path: "data/train-*"
+  default: true
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: "data/train-*"
 ---
 
 # TakaraSpider Japanese Web Crawl Dataset
@@ -49,7 +48,7 @@ configs:
 
 ## Dataset Summary
 
-TakaraSpider is a large-scale web crawl dataset specifically designed to capture Japanese web content alongside international sources. The dataset contains **257,900 web pages** collected through systematic crawling, with a primary focus on Japanese language content (77%) while maintaining substantial international representation (23%). This makes it ideal for Japanese-English comparative studies, cross-cultural web analysis, and multilingual NLP research.
+TakaraSpider is a large-scale web crawl dataset specifically designed to capture Japanese web content alongside international sources. The dataset contains **257,900 web pages** collected through systematic crawling, with a primary focus on Japanese language content (78.5%) while maintaining substantial international representation (21.5%). This makes it ideal for Japanese-English comparative studies, cross-cultural web analysis, and multilingual NLP research.
 
 The dataset was generated by the TakaraSpider crawler, which was specifically engineered to capture high-quality Japanese web content while maintaining broad international coverage.
 
@@ -66,9 +65,9 @@ The dataset was generated by the TakaraSpider crawler, which was specifically en
 
 ## Languages
 
-- **Japanese (ja)**: 76.9% of content - Primary focus with rich representation
-- **English (en)**: 5.7% of content - International perspective
-- **Other/Unknown**: 17.4% of content - Diverse multilingual representation
+- **Japanese (ja)**: 78.5% of content - Primary focus with rich representation
+- **English (en)**: 5.3% of content - International perspective
+- **Other/Unknown**: 16.2% of content - Diverse multilingual representation
 
 ![Language Distribution](./analytics_output/language_distribution.png)
 
@@ -91,13 +90,13 @@ The dataset was generated by the TakaraSpider crawler, which was specifically en
 - **`crawl_id`** (string): Unique identifier for each crawl session
 - **`timestamp`** (timestamp): ISO 8601 formatted crawl timestamp with timezone
 - **`url`** (string): Target URL that was crawled
-- **`source_url`** (string): Referring/source URL (when available)  
+- **`source_url`** (string): Referring/source URL (when available)
 - **`html`** (string): Complete raw HTML content of the page
 
 ### Data Splits
 
 | Split | Examples |
-|-------|----------|
+| ----- | -------- |
 | train | 257,900  |
 
 ## Dataset Creation
@@ -122,12 +121,13 @@ The data was collected through systematic web crawling using the TakaraSpider cr
 
 - Prioritize Japanese (.jp) domains while maintaining international diversity
 - Capture complete HTML content with metadata
-- Ensure broad domain coverage (3,470+ unique domains)
+- Ensure broad domain coverage (10,590+ unique domains)
 - Maintain crawl provenance through unique session IDs
 
 #### Who are the source language producers?
 
 The source content represents natural web usage across:
+
 - **Japanese web users**: Content creators, bloggers, businesses, news organizations
 - **International web users**: Global content accessible to Japanese audiences
 - **Mixed demographics**: Spanning individual users to large organizations
@@ -137,12 +137,14 @@ The source content represents natural web usage across:
 ### Social Impact of Dataset
 
 **Positive Impacts:**
+
 - Enables Japanese NLP research and development
-- Supports cross-cultural digital humanities research  
+- Supports cross-cultural digital humanities research
 - Facilitates web technology development and benchmarking
 - Promotes understanding of Japanese digital culture
 
 **Potential Concerns:**
+
 - May contain biased content reflecting web demographics
 - Temporal snapshot may not represent evolving web trends
 - Domain concentration could skew research findings
@@ -153,13 +155,14 @@ The source content represents natural web usage across:
 
 **Identified Biases:**
 
-1. **Geographic Bias**: 45.8% Japanese domains may not represent global web diversity
+1. **Geographic Bias**: 50.9% Japanese domains may not represent global web diversity
 2. **Temporal Bias**: Single-day crawl (June 13, 2025) captures specific moment in time
-3. **Domain Concentration**: Top 10 domains represent 15.8% of dataset
-4. **Language Detection**: 17.2% of content requires language identification
-5. **Content Type Skew**: Structured webpages (60.1%) over-represented
+3. **Domain Concentration**: Top 10 domains represent 13.4% of dataset (improved diversity)
+4. **Language Detection**: 15.9% of content requires language identification
+5. **Content Type Skew**: Structured webpages (64.1%) over-represented
 
 **Mitigation Strategies:**
+
 - Clearly document dataset composition and limitations
 - Encourage diverse evaluation across content types
 - Recommend supplementary datasets for global research
@@ -185,6 +188,7 @@ The source content represents natural web usage across:
 ### Licensing Information
 
 This dataset is released under the **Creative Commons Attribution 4.0 International License (CC-BY-4.0)**. Users are free to:
+
 - Share and redistribute the material
 - Adapt, remix, transform, and build upon the material
 - Use for any purpose, including commercial applications
@@ -218,13 +222,13 @@ Thanks to [@takarajordan](https://huggingface.co/takarajordan) for creating and
 
 ### Data Quality Metrics
 
-| Metric | Value | Description |
-|--------|-------|-------------|
-| **Duplicate URLs** | 0.0% | No duplicate URLs detected in sample |
-| **Content Completeness** | 99%+ | HTML content available for virtually all records |
-| **Metadata Completeness** | 100% | All required fields populated |
-| **Average Content Size** | 264KB | Substantial content per page |
-| **Domain Diversity** | 0.231 | High domain-to-page ratio |
+| Metric                    | Value | Description                                      |
+| ------------------------- | ----- | ------------------------------------------------ |
+| **Duplicate URLs**        | 0.0%  | No duplicate URLs detected in sample             |
+| **Content Completeness**  | 99%+  | HTML content available for virtually all records |
+| **Metadata Completeness** | 100%  | All required fields populated                    |
+| **Average Content Size**  | 198KB | Substantial content per page                     |
+| **Domain Diversity**      | 0.205 | Strong domain-to-page ratio                      |
 
 ## Getting Started
 
@@ -236,7 +240,7 @@ from datasets import load_dataset
 # Load the full dataset
 dataset = load_dataset("takarajordan/takaraspider")
 
-# Or stream for memory efficiency  
+# Or stream for memory efficiency
 dataset = load_dataset("takarajordan/takaraspider", streaming=True)
 
 # Sample for testing
@@ -266,11 +270,11 @@ domains = [urlparse(url).netloc for url in dataset["train"]['url']]
 Complete analytics and visualizations are available in the `analytics_output/` directory:
 
 - **Domain Distribution**: Top domains by page count
-- **Geographic Analysis**: TLD-based geographic distribution  
+- **Geographic Analysis**: TLD-based geographic distribution
 - **Content Analysis**: Size distribution and content types
 - **Language Breakdown**: Detailed language detection results
 - **URL Structure**: Path depth and navigation patterns
 
 ---
 
-*This dataset card was generated using comprehensive analytics based on a 15,000-sample representative subset (5.8% of full dataset). Last updated: June 18, 2025.*
+_This dataset card was generated using comprehensive analytics based on a 51,580-sample representative subset (20% of full dataset). Last updated: June 18, 2025._