SMLIR 2016 - 2nd Workshop on Tools and Technologies in Statistics, Machine Learning and Information Retrieval

The integration of tools and technologies for building IDA processes is a key point in developing applications which improve the effectiveness of various intelligent applications. The AI community will benefit from the discussions related to the advantages and drawbacks of various options in a practical context with experimental results, by improving the efficiency of building high quality software systems supporting the research efforts.
The first step of developing an IDA application concentrates on choosing the right tool or technology that fits the task requirements (e.g., input size, algorithm type, running time efficiency, scalability, etc.). The diversity of the available options is an indication of the necessity for a detailed analysis. From this point of view, the AI community needs to be aware of success and failure attempts of many practical research efforts in order to provide the possibility of a proper future design choice.
Existing tools and technologies implement in different ways recent advances on techniques from statistical/machine learning, information retrieval and data mining domains in terms of programming language (e.g., Java, C/C++, C#, R, etc.), toolkits (e.g., R, Weka, Apache Mahout, MLTK, Maple, Matlab, etc.) and implementation details that may have a great impact on running times, scalability, effectiveness or efficiency.
This workshop aims at bringing together researchers from academia and industry practitioners with special interest in statistics/machine learning, information retrieval, data mining to (1) discuss current state of the art tools and technologies, (2) identify patterns for proper usage of various options for different tasks, and (3) lay out a vision regarding the modality in which tools and technologies will influence future applications. The organizers hope to obtain common background knowledge for integrating various tools and technologies in future AI applications.