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Towards an AI-Driven Marketplace for Small Businesses During COVID-19.
Coltey, Erik; Alonso, Daniela; Vassigh, Shahin; Chen, Shu-Ching.
Afiliación
  • Coltey E; Knight Foundation School of Computing and Information Sciences, Florida International University, 11200 SW 8th Street, Miami, 33199 FL USA.
  • Alonso D; Knight Foundation School of Computing and Information Sciences, Florida International University, 11200 SW 8th Street, Miami, 33199 FL USA.
  • Vassigh S; College of Communication, Architecture and the Arts, Florida International University, 11200 SW 8th Street, Miami, 33199 FL USA.
  • Chen SC; Knight Foundation School of Computing and Information Sciences, Florida International University, 11200 SW 8th Street, Miami, 33199 FL USA.
SN Comput Sci ; 3(6): 441, 2022.
Article en En | MEDLINE | ID: mdl-35975091
ABSTRACT
With the introduction of new COVID-19 variants such as Delta and Omicron, small businesses have been tasked with navigating a constantly changing business environment. Furthermore, due to supply chain issues, shortages of various critical products negatively affect businesses of all sizes and industries. However, continued innovation in Computer Science, specifically in sub-fields of Artificial Intelligence (AI), such as natural language processing (NLP), has created significant value for businesses through helpful data-driven features. To this end, we propose a platform utilizing AI-driven tools to help build an effective business-to-business (B2B) platform. The proposed platform aims to automate much of the market research which goes into selecting products and platform users during times of distress while still providing an intuitive e-commerce interface. There are three primary novel components to this platform. The first of these components is the Buyer's Club (BC), which allows customers to pool resources to purchase bulk orders at a reduced cost. The second component is an automated system utilizing Natural Language Processing (NLP) to detect trending disaster news topics. Disaster topic detection can be applied to inform buyers and suppliers on adapting to changing market conditions and has been shown to match closely with Google Trends data. The third component is a regulation matching system, using a custom data set to help inform customers when purchasing products. Such guidance is necessary to comply with a regulatory environment that will be irregular for the foreseeable future.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: SN Comput Sci Año: 2022 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: SN Comput Sci Año: 2022 Tipo del documento: Article