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Cet article propose une approche novatrice pour la recherche de produits eCommerce via un téléphone mobile, illustrée par un prototype nommé eCoMobile. Cette approche vise à globaliser la recherche
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How to fill out Ontology-Based Intelligent Mobile Search Oriented to Global e-Commerce

01
Identify the domain of interest for the e-commerce ontology.
02
Gather relevant data sources, including product catalogs and user behavior datasets.
03
Define the classes, properties, and relationships that will make up the ontology.
04
Use ontology modeling tools to create a structured representation of the information.
05
Incorporate semantic search algorithms to enhance query understanding.
06
Implement the ontology in a mobile application backend for seamless integration.
07
Test the application with real user queries to refine its performance.

Who needs Ontology-Based Intelligent Mobile Search Oriented to Global e-Commerce?

01
E-commerce businesses looking to enhance search functionality.
02
Mobile application developers focusing on user experience.
03
Marketers aiming to improve product discoverability.
04
Researchers in the field of artificial intelligence and knowledge representation.
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Ontology-Based Intelligent Mobile Search Oriented to Global e-Commerce is a framework that uses ontological structures to enhance mobile search functionalities, specifically tailored to optimize user experience in global e-commerce contexts.
Entities engaged in global e-commerce that utilize mobile search technologies and require advanced search functionalities to improve user interaction and product discovery may be required to file this framework.
To fill out this framework, one must collect relevant data on product categories, user preferences, and search behavior, and structure this information according to the specified ontological guidelines to ensure accurate representation.
The purpose is to enhance the efficiency and relevance of mobile searches in e-commerce by using structured data representation, allowing users to find products more effectively and improving overall customer satisfaction.
Information required includes product details, user interaction metrics, search query data, and ontological mappings relevant to the searched items to enrich the search experience.
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