Associated rule mining for automatic electronic component performance attribute identification****

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Lytica's electronic components supply chain information products operate by using a reference library that was developed in-house that tracks information about all products that are available in the global marketplace. Our current reference library contains for now around 20 million parts, and we have an active research program in place to employ information extraction methods to read new product information from PDF datasheets. **The main goal of this project is to develop a software method that can automatically recommend fit/form/function performance characteristics from a given MPN. We seek to perform the experimental development of Bootstrap Technologies an electronic component repository that can provide performance and product compliance attributes for eight major vendors and thousands of manufacturers' websites. This partnership with UQO focuses on the following tasks: **(1) Document annotation for various datasheets**(2) Recognizing the key words (core electronics components) **(3) Extract aspects of each electronic components**(4) Build a database of similar electronic components based on parameters, performance and cost ****The project will be conducted at UQO by Dr. Ahmed Lakhssassi. In addition to contributing to the training of two graduate students and one professional, this research will promote the development of Canadian industry by aiding Lytica in creating new processes, by developing new expertise in tracks information about all products that are available in the global marketplace. Lytica seeks to grow and dominate the Billion dollar market in 2019.******