Abstract
The Unsupervised Distance Learning Framework (UDLF) [1] is a software developed to facilitate the general use and evaluation of novel unsupervised learning methods. These methods aim at post-processing the ranking information for different tasks, being especially useful for multimedia retrieval. The major advantage of UDLF is that it provides a unified and extensive model for implementing different unsupervised methods. Any execution or experiment can be easily conducted by setting a configuration file, no recompilation is required. To evaluate the retrieval results, the framework computes different effectiveness and efficiency measures and it allows for exporting visual output results to external files. UDLF is written in C++, works out of the box, does not require external libraries, and is compatible with different operating systems including Linux, MacOS, and Windows. The source code is publicly available on GitHub under the terms of the GPLv2 license.
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