Established: March 11, 2014

A Large-Scale Real-World Image Dataset

We argue that the massive amount of click data from commercial search engines provides a data set that is unique in the bridging of the semantic and intent gap. Search engines generate millions of click data (a.k.a. image-query pairs), which provide almost “unlimited” yet strong connections between semantics and images, as well as connections between users’ intents and queries. This site is to introduce such as dataset, Clickture.

The dataset, named Clickture, was sampled from one-year click log of a commercial image search engine. It consists of a big table with 212:3 million triads: Clickture = {}. A triad means that the image K was clicked C times in the search results of query Q in one year (maybe by different users at different times). Image K is represented by a unique “key” which is hash code generated from the image URL, together with the original URL. Query Q is a textual word or phrase, and click count C is an integer which is no less than one. One image may correspond with to one or more entries in the table. One query may also appear in multiple entries triads that are associated with different images. There are 40 million unique (in terms of URLs) image keys, that is, images in the dataset, and 73.6 million unique queries (based on textual string comparison in lower case) in the Clickture.

Through users’ click action during image search, the query Q in the triad is linked to the image K. In general, the bigger the click count C is, the higher probability that the corresponding query is relevant to the image. For convenience, we call Q a “clicked query” of Image K, and K a “clicked image” of query Q, and call 〈K,Q〉 a “clicked image-query pair”, and the triad 〈K,Q,C〉 as “click data”. We also call “clicked queries” of an image as “labels” of the image.

To enable the use of Clickture by a wide range of research organizations and individuals with different computing, networking, storage and programing capacities, a subset of Clickture images (1 million images and 11.7 million queries), is provided. We call this set Clickture-Lite and the full 40M dataset Clickture-Full (or in brief Clickture). The 1M images in Clickture-Lite are randomly sampled from the 40M image dataset (based on click frequency).

How to get Clickture-Full

Please send emails to Xian-Sheng Hua ( Due to large size of the dataset, we will send you a hard drive.

Related Events

  • ACM Multimedia Grand Challenge 2014 (Based on Clickture-Lite and optionally Clickture-Full)
  • ICME Grand Challenge 2014 (Based on Clickture-Lite)
  • MSR-Bing Image Retrieval Grand Challenge 2013 (Based on Clickture-Lite)


  • Portrait of Yuxiao Hu

    Yuxiao Hu

    Senior Research Software Developer

  • Portrait of Kuansan Wang

    Kuansan Wang

    Managing Director, MSR Outreach Academic Services

  • Portrait of Jin Li

    Jin Li

    Partner Research Manager