Update README.md

README.md

@@ -16,6 +16,48 @@ license: other
 
 # Dataset Card: Live Streaming Room Risk Assessment (May/June 2025)
 
+---
+license: cc-by-4.0
+pretty_name: "Live or Lie — Live Streaming Room Risk Assessment (May/June 2025)"
+language:
+  - zh
+tags:
+  - live-streaming
+  - risk-assessment
+  - fraud-detection
+  - weak-supervision
+  - multiple-instance-learning
+  - behavior-sequence
+---
+
+
+## Dataset Summary
+This dataset contains **live-streaming room interaction logs** for **room-level risk assessment** under **weak supervision**. Each example corresponds to a single live-streaming room and is labeled as **risky (> 0)** or **normal (= 0)**.
+
+The task is designed for early detection: each room’s action sequence is **truncated to the first 30 minutes**, and can be structured into **user–timeslot capsules** for models such as AC-MIL.
+
+## File Structure
+The dataset is organized into two time-indexed subsets (May and June). Large LMDB data files are provided in multiple `.part` chunks to comply with storage limits.
+
+```text
+.
+├── final_May_hard1_masked_encoded.lmdb/
+│   ├── data.mdb.00.part
+│   ├── data.mdb.01.part
+│   ├── data.mdb.02.part
+│   ├── data.mdb.03.part
+│   └── lock.mdb
+├── final_June_hard1_masked_encoded.lmdb/
+│   ├── data.mdb.00.part
+│   ├── data.mdb.01.part
+│   └── lock.mdb
+├── May_train.csv
+├── May_val.csv
+├── May_test.csv
+├── June_train.csv
+├── June_val.csv
+└── June_test.csv
+
 ## Dataset Summary
 This dataset contains **live-streaming room interaction logs** for **room-level risk assessment** under **weak supervision**. Each example corresponds to a single live-streaming room and is labeled as **risky (> 0)** or **normal (= 0)**.
 
@@ -56,9 +98,24 @@ The paper uses two datasets (“May” and “June”), each with train/val/test
 | June test | 11,116  | 725 | 37 | 29.1 |
 
 ## Quickstart
+
+1. Reconstruct the LMDB files
+Before loading the data, you must merge the split parts back into a single data.mdb file for each subset. Run the following commands in your terminal:
 Below we provide a simple example showing how to load the dataset.
 
-We use LMDB to store and organize the data. Please install the Python package first:
+```
+# Reconstruct May Dataset
+cd final_May_hard1_masked_encoded.lmdb
+cat data.mdb.*.part > data.mdb
+cd ..
+
+# Reconstruct June Dataset
+cd final_June_hard1_masked_encoded.lmdb
+cat data.mdb.*.part > data.mdb
+cd ..
+```
+
+2. We use LMDB to store and organize the data. Please install the Python package first:
 ```
 pip3 install lmdb
 ```