Requirements for Data Integration Solutions in the Fashion Industry Sample Clauses

Requirements for Data Integration Solutions in the Fashion Industry. We will describe the scenarios in the fashion industry where data integration is more problematic, pointing out the requirements for data integration that arise from them, both in terms of infrastructure as well as datasets. We will refer to the tasks introduced in Section 1.1, analysing one of the main workflows that FashionBrain project aims to consider in terms of data integration.
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Requirements for Data Integration Solutions in the Fashion Industry. We will describe the scenarios in the fashion industry where data integration is more problematic, pointing out the requirements for data integration that arise from them, both in terms of infrastructure as well as datasets. We will refer to the tasks introduced in Section 1.1, analysing one of the main workflows that FashionBrain project aims to consider in terms of data integration. Fig.1: FashionBrain data processing workflow. In Figure 1 an important data processing workflow related to FashionBrain is sketched, and will use as motivation for the description of the requirements for data integration. We describe each step of the workflow in the following, with the corresponding requirement. To support data integration across sources and data types and to have a central data schema, a fashion ontology needs to be built (Xxxx, Xxx, and Yu), based on redundancy-minimizing shopping categories (unlike the traditional fashion ontologies on which e.g. clothes are divided depending on the gender). This is necessary when integration of images and text are done against a structured catalog (like shown in Figure 1). FashionBrain project is also exploring alternative solutions when integration between images and text are done without the need of a schema, like in the case of deep neural networks (Xxxxxxx, Heinz, and Xxxxxxxx): Long short-term memory (LSTM) is an artificial neural network architecture that is recurrent, and allows data to flow both forwards and backwards within the network. This technique can be used both for task 6 or to build a schema-free solution for tasks 1-5 .

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