Add task category and Github link to dataset card

This PR adds the `task_categories` metadata field and a link to the Github repository for better discoverability and clarity. The "other" category is used as no more specific category is available, but we suggest adding descriptive tags such as `poi-recommendation`, `trajectory-prediction`, `human-mobility` to improve searchability.

README.md

@@ -1,5 +1,11 @@
 ---
 license: apache-2.0
+task_categories:
+- other
+tags:
+- poi-recommendation
+- trajectory-prediction
+- human-mobility
 dataset_info:
 - config_name: default
   features:
@@ -92,13 +98,13 @@ configs:
 
 [![huggingface](https://img.shields.io/badge/%F0%9F%A4%97-Hugging_Face_Collections-yellow)](https://huggingface.co/collections/w11wo/massive-steps-point-of-interest-check-in-dataset-67edf6dbb60e30eac9a9af1b)
 [![arXiv](https://img.shields.io/badge/arXiv-2505.11239-b31b1b.svg)](https://arxiv.org/abs/2505.11239)
-[![GitHub](https://img.shields.io/badge/github-%23121011.svg?logo=github&logoColor=white)](https://github.com/w11wo/Massive-STEPS)
+[![GitHub](https://img.shields.io/badge/github-%23121011.svg?logo=github&logoColor=white)](https://github.com/cruiseresearchgroup/Massive-STEPS)
 
 </div>
 
 ## Dataset Summary
 
-**[Massive-STEPS](https://github.com/w11wo/Massive-STEPS)** is a large-scale dataset of semantic trajectories intended for understanding POI check-ins. The dataset is derived from the [Semantic Trails Dataset](https://github.com/D2KLab/semantic-trails) and [Foursquare Open Source Places](https://huggingface.co/datasets/foursquare/fsq-os-places), and includes check-in data from 12 cities across 10 countries. The dataset is designed to facilitate research in various domains, including trajectory prediction, POI recommendation, and urban modeling. Massive-STEPS emphasizes the importance of geographical diversity, scale, semantic richness, and reproducibility in trajectory datasets.
+**[Massive-STEPS](https://github.com/cruiseresearchgroup/Massive-STEPS)** is a large-scale dataset of semantic trajectories intended for understanding POI check-ins. The dataset is derived from the [Semantic Trails Dataset](https://github.com/D2KLab/semantic-trails) and [Foursquare Open Source Places](https://huggingface.co/datasets/foursquare/fsq-os-places), and includes check-in data from 12 cities across 10 countries. The dataset is designed to facilitate research in various domains, including trajectory prediction, POI recommendation, and urban modeling. Massive-STEPS emphasizes the importance of geographical diversity, scale, semantic richness, and reproducibility in trajectory datasets.
 
 | **City**        |                                 **URL**                                 |
 | --------------- | :---------------------------------------------------------------------: |