Datasets for GeoPhrase Tree

This is the experiment dataset for our paper: \GeoPhrase Tree: An Efficient Index for Frequent Phrase Query over Spatio-Temporal Ranges\Our experiments are carried out on three datasets: FourSquare, Yelp and GeoText.FourSquare dataset includes check-ins, tips, and tags of restaurant venues in New York (NYC) collected from Foursquare over a four-month period. The dataset is useful for assessing the algorithm\u2019s ability to identify popular phrases related to specific locations and times.Yelp dataset is a larger dataset that consists of more than 7 million geo-tagged reviews with timestamp from Yelp, a restaurant review website. It contains user feedback, ratings, and geographical coordinates. It also allows us to test the algorithm\u2019s scalability and efficiency in handling large-scale data.GeoText dataset comprises 377,616 messages from approx- imately 9,475 geo-located microblog users within the United States. The dataset spans a wide range of topics and events, while also deviating from strict grammatical norms. It includes abbreviations and popular phrases, making it an ideal resource for evaluating the effectiveness of our algorithm in processing diverse content and identifying frequent phrases across multi- ple domains.