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Tarvel Review Ratings Data Set
Download: Data Folder, Data Set Description

Abstract: Google reviews on attractions from 24 categories across Europe are considered. Google user rating ranges from 1 to 5 and average user rating per category is calculated.

Data Set Characteristics:  

Multivariate, Text

Number of Instances:

5456

Area:

N/A

Attribute Characteristics:

Real

Number of Attributes:

25

Date Donated

2018-12-19

Associated Tasks:

Classification, Clustering

Missing Values?

N/A

Number of Web Hits:

33507


Source:

Shini Renjith, shinirenjith '@' gmail.com


Data Set Information:

This data set is populated by capturing user ratings from Google reviews. Reviews on attractions from 24 categories across Europe are considered. Google user rating ranges from 1 to 5 and average user rating per category is calculated.


Attribute Information:

Attribute 1 : Unique user id
Attribute 2 : Average ratings on churches
Attribute 3 : Average ratings on resorts
Attribute 4 : Average ratings on beaches
Attribute 5 : Average ratings on parks
Attribute 6 : Average ratings on theatres
Attribute 7 : Average ratings on museums
Attribute 8 : Average ratings on malls
Attribute 9 : Average ratings on zoo
Attribute 10 : Average ratings on restaurants
Attribute 11 : Average ratings on pubs/bars
Attribute 12 : Average ratings on local services
Attribute 13 : Average ratings on burger/pizza shops
Attribute 14 : Average ratings on hotels/other lodgings
Attribute 15 : Average ratings on juice bars
Attribute 16 : Average ratings on art galleries
Attribute 17 : Average ratings on dance clubs
Attribute 18 : Average ratings on swimming pools
Attribute 19 : Average ratings on gyms
Attribute 20 : Average ratings on bakeries
Attribute 21 : Average ratings on beauty & spas
Attribute 22 : Average ratings on cafes
Attribute 23 : Average ratings on view points
Attribute 24 : Average ratings on monuments
Attribute 25 : Average ratings on gardens


Relevant Papers:

Renjith, Shini, A. Sreekumar, and M. Jathavedan. 2018. “Evaluation of Partitioning Clustering Algorithms for Processing Social Media Data in Tourism Domain”. In 2018 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 127–31. IEEE.



Citation Request:

Renjith, Shini, A. Sreekumar, and M. Jathavedan. 2018. “Evaluation of Partitioning Clustering Algorithms for Processing Social Media Data in Tourism Domain”. In 2018 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 127–31. IEEE.


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