travelers' rating about POI(Point of Intereset)

  • Last Update:July,8,2019 Created:July,8,2019
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Title of the dataset travelers' rating about POI(Point of Intereset)
Provenance of the dataset
How were the data collected/created? What was the cost? This dataset is collected by asking every traveler who has expereiced POI. Cost : investigators' salary, traffic fee.
Data sharing policy With anyone.
Data sharing policy everyone can use it.

About data analysis and simulation

Type of data: Check all that apply. Use "Other" to specify other types so that we can include them in further updates. series table
Variable labels of dataset (the names of the variables) review_id|longitude|latitude|altitude|review_date|temperature|rating|user_id|user_birthday|user_nationality|category user_career|double user_income
Outline of data The dataset is about travelers' personal information.The number of instances is 2000'000 and the number of attributes is 12. The data are collected to find out which factors could affect travelers when they are rating about POI.
Simulation process The input set are No.2-No.12attributes.(This is beacause the first attribute is ID which should not be used to exercise).The output set are factors that most likely have relationship with rating. We can use some regression method to find out the specific relationship with rating. At the same time,there are some missing in user_income.We can use career and natian information to forecast and fill the losing.
Expected outcome of the process (obtained knowledge, analysis results, output of tools) By using this dataset,I can have the answer about important factors that affect rating and the relationship among these factors.
Anticipation for analyses/simulations other than the typical ones provided above Use more suitable regression methods.


What kind of data/tools do you wish to have? If I can get these travelers' interests,it will be better because I want to analy the relationship between rating and hobby. If it is too difficult,it is ok to use interest data of people who live near them to replace.
Visualized information
Sample data
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