Cross-Market Recommendation (XMRec)

Cross-Market Recommendation (XMRec)


Cross-Market Recommendation Competition @ WSDM 2022

Cross-Market Product Recommendation @ CIKM 2021

Workshop of Cross-Market Recommendation @ RecSys 2021

XMarket Dataset


Here, we release XMarket, a large dataset covering 18 local markets on 16 different product categories, featuring 52.5 million user-item interactions. For more information on the XMarket dataset, please refer to our CIKM’21 paper.


Below is the list of our markets and their data. For every market below, you can click and see the list of categories as well as #user, #item, and #ratings we collected. For every market, you can download the ratings, reviews, and metadata associated with asins in this category. Please see below for how to read each type of these files and their file formats. Please reach out if you encounter any problem with these files provided below. The total size of gzipped data is ~7.5 GB.

Data Samples (and python reading code examples)

  1. Ratings

Provide a simple file format listing as userId itemId rating date. For this purpose, you can easily read each of these ratings with the following code.

import pandas as pd
cur_ratings = 'ratings_uk_Books.txt.gz' # specify the url to the file 
df = pd.read_csv(cur_ratings, compression='gzip', header=None, sep=' ', names=["userId", "itemId", "rate", "date"] )

After reading, you can see a dataframe similar to below (taken from uk market).

| userId                       |     itemId |   rate | date       |
| AFXKARXBL3X3LO5GNN4XAXC7XMPQ | 0061806765 |      3 | 2012-08-20 |
| AH3Z5FFVAQYVQNDBUG2M23ZZBCGA | 0007273754 |      5 | 2013-11-24 |
| AHDFCI7XXY5J7GIDWWE2VSLPQMCQ | 1682307530 |      4 | 2016-06-29 |
| AE5KNHUMUIHXU3FCRBDMTTZT7UYA | 1611097843 |      5 | 2014-05-29 |
| AEEHVF74E2QB7UP7VG4LFSUNXVJA | 0142410586 |      4 | 2020-04-13 |


  1. Reviews

Review files provide a list of json objects, each providing a customer review for a given product. For reading these files you can read line by line and obtain the json dictionary of a specific review as below.

import gzip
example_rev_file = 'reviews_uk_Books.json.gz'
review_lines = []
with, 'rt', encoding='utf8') as f:
    review_lines = f.readlines()
print( eval(review_lines[1].strip())[0] )

Below is the output of the sample line of the review file we read above.

 'asin': '0001047868',
 'reviewerName': 'christine mcgill',
 'reviewText': 'I thourghly enjoyed this classic, read it when I was ten so was greatly surprised that it seemed even better than I remembered.',
 'overall': 5.0,
 'summary': 'I thourghly enjoyed this classic',
 'cleanReviewTime': '2015-09-29',
 'reviewTime': '29 September 2015'


  1. Metadata

Metadata includes product descriptions, price, sales-rank, brand info, and co-purchasing links. For reading, similar to reviews, use the below python code snippet.

import gzip
example_met_file = 'metadata_us_Electronics.json.gz'
meta_lines = []
with, 'rt', encoding='utf8') as f:
    meta_lines = f.readlines()

print( eval(meta_lines[80].strip()) )

Below is the output of the sample line of the review file we read above.

 {'asin': 'B000023VW2',
 'title': 'Sangean ANT-60 Short Wave Antenna',
 'averageRating': '4.3',
 'ratingCount': '698 global ratings',
 'amazon_badge': 'Amazon\'s \nChoice for "shortwave antenna"',
 'ratingDist': {'5': '67%', '4': '14%', '3': '10%', '2': '3%', '1': '6%'},
 'ratingByFeature': {},
 'price': '$12.86',
 'imgUrl': '{"":[369,569],"":[230,355],"":[276,425],"":[292,450],"":[303,466],"":[339,522],"":[441,679]}',
 'related': {
	 'sponsored': ['B000NOSCN0', 'B07NRSWB6Q', 'B00008N9M7', 'B0823N6DWV', 'B07NRNVCTV', 'B00QXJMZRS', 'B07SXF87LJ', 'B07P8BW3P2', 'B07YN62TM1', 'B07CNMDTY8', 'B000NOSCN0', 'B00R6VXD6Y', 'B074QLLVC6', 'B00008N9M7', 'B00QXJMZRS', 'B07R284TN5','B01N3POQ92', 'B07P8BW3P2', 'B07R3QG1CR','B000O8SQNG'],
	  'alsoBought': [],
	  'alsoViewed': ['B0104MT5HW', 'B00GJ51NVA', 'B08464KCG1', 'B0055Q5FIQ', 'B082B4C7CC', 'B001KC579Q', 'B0141X3B5W', 'B00IDM4N5K', 'B07T6LK1X2', 'B004H912FC', 'B08HCYYW88', 'B07T2FQH6N', 'B0104J57GS', 'B0014T7W8Y', 'B001HX4D84', 'B004QJKO52', 'B01ARN28SQ', 'B07T1F6LDY', '1999830024', 'B00X15M5MC', 'B08BLF7QDV', 'B005OEA88Q', 'B0035X1EC2', 'B01MSMRASH', 'B078JKXCYH', 'B085ZSXF8Z', 'B009ENG6TI','B00BLW627G', 'B001P4LTAU'],
	  'boughtTogether': ['B000023VW2', 'B005KVJYTW', 'B004H912FC'],
	  'compared': ['B000023VW2', 'B01I27ZOQM','B082B4C7CC', 'B001PNNXGO', 'B001KC579Q', 'B0055Q5FIQ']
 'productDetails': {
      'Product Dimensions': '5.98 x 8.27 x 0.94 inches',
      'Item Weight': '1.41 ounces',
      'Manufacturer': 'Sangean',
      'ASIN': 'B000023VW2',
      'Item model number': 'ANT-60',
      'Customer Reviews': ['/*',
	   '* Fix for UDP-1061. Average customer reviews has a small extra line on hover',
  	'Best Sellers Rank': '#13 in Radio Antennas',
  	'Is Discontinued By Manufacturer': 'No',
  	'Date First Available': 'October 15, 1999'},
	 'sellerPage': '/stores/SANGEAN/page/E550CD6C-93E0-447F-B3F0-A06E71DF322F?ref_=ast_bln',
	 'categories': ['Electronics',
	  'Accessories & Supplies',
	  'Audio & Video Accessories',
	  'Radio Antennas'],
 	'description': "From the Manufacturer\nShortwave radios brought the world together long before the Internet, and now the Sangean ANT-60 antenna helps maximize your shortwave experience. Ideally suited for today's compact shortwave receiver and fully portable inside its convenient, compact carrying case, the ANT-60 extends to a full 23 feet and enhances the performance and reception of your shortwave radio beyond that of a typical built-in telescoping antenna. An adapter plug is provided for those receivers lacking a standard 1/8-inch (3.5mm) miniplug.",
 	'overviewFeatures': {},
 	'features': ['Improves the performance and reception of your shortwave radio',
	  'Extends to 23 feet and can be easily rewound into its compact case',
	  'Has 3.5-millimeter mini plug',
	  'Fits any 3.5-millimeter external antenna jack',
	  'Includes adapter plug'],
	'reviewFilters': []}



If you use this dataset, please refer to our CIKM’21 paper:

	author = {Bonab, Hamed and Aliannejadi, Mohammad and Vardasbi, Ali and Kanoulas, Evangelos and Allan, James},
	booktitle = {Proceedings of the 30th ACM International Conference on Information \& Knowledge Management},
	publisher = {ACM},
	title = {Cross-Market Product Recommendation},
	year = {2021}}


FOREC's data cleaning and code are provided in this repository.