An ontology-based semantic extraction approach for B2C ecommerce

2006

E-Commerce is a direct extension of digitalization of our economy; it begins to have an important place in the internet’s user’s lives. The main problems of e-Commerce are the extraction of relevant informations about products, how to provide users with products that meet their needs, hence the need to have relevant information retrieval system ie with high accuracy and the lack of works in this field. This paper presents an information retrieval system based on an e-commerce ontology representing the different properties of the products on the internet and which will be used to establish the model of the index. At the end of this paper we have applied our product information retrieval system on a famous e-commerce web site, the results show that our system will help users to acquire the desired information on products that meet their needs.

Journal of Geography and Environmental Management, 2018

Even though online shopping is becoming increasingly popular, many consumers are still reluctant to buy online. One approach to improve adaption is to base ecommerce search engines on ontologies to allow a more intuitive search process. This paper presents the results of an analysis how a sample of online shoppers perceived various ontologybased features in an online shop. The data was gathered in two focus groups with panelists coming from different sociodemographic backgrounds. Most middle aged women actively buy through catalogs. However, across the focus groups, most panelists are very reluctant buying online. Our study suggests that age has a higher influence on the information search behaviour of consumers in online shops than gender. Kеy wоrds: consumer decision process, ecommerce, ontologybased search, ontology engineering. 1 Көш кімбaевa У., 1а* Алимғaзиевa Н., 1б Ақ тымбaевa А., 1в Жaку повa А. 1* Геогрaфия жә не тaбиғaтты пaйдaлaну фaкуль те ті, әлФaрaби aтындaғы Қaзақ ұлттық университеті, Қaзaқстaн, Алмaты қ.

Lecture Notes in Electrical Engineering, 2019

With the growth of e-commerce, shopping online has now become a part and parcel of every one's life. The advantage of e-commerce Web sites is that they can reach to a very large number of customers despite of distance and time limitations. The main aim of this paper is to extract the product information from various e-commerce sites. Extraction of such information can help the business organizations to fetch and attract the large number of customers to their Web site and increase profit. So, in this paper, we propose a fully automatic method which will extract and integrate information from multiple e-commerce Web sites in order to improve business decision making. The proposed method is also comparatively better at precision and recall than other methods.

Workshop on Adaptive Text …, 2003

Abstract. E-commerce and the continuous growth of the WWW has seen the rising of a new generation of e-retail sites. A number of commercial agent-based systems has been developed to help Internet shoppers decide what to buy and where to buy it from. In such systems, ontologies play a ...

This paper explains the basic notions of the Semantic Web and its impact on the development of ecommerce; use of Semantic Web technologies in ecommerce. Furthermore, this paper also explains the primary component of today’s Semantic web Landscape and the role of Ontology and linked data.

2004

While research on the Semantic Web has mostly focused on basic technologies that are needed to make the Semantic Web a reality, there has not been a lot of work aimed at showing the effectiveness and impact of the Semantic Web on business problems. This paper presents a case study where Web and Text mining techniques were used to add semantics to data that is stored in transactional databases of retailers. In many domains, semantic information is implicitly available and can be extracted automatically to improve data mining systems. This is a case study of a system that is trained to extract semantic features for apparel products and populate a knowledge base with these products and features. We show that semantic features of these items can be successfully extracted by applying text learning techniques to the descriptions obtained from websites of retailers. We also describe several applications of such a knowledge base of product semantics that we have built including recommender systems and competitive intelligence tools and provide evidence that our approach can successfully build a knowledge base with accurate facts which can then be used to create profiles of individual customers, groups of customers, or entire retail stores.

2003

Abstract. E-commerce and the continuous growth of the WWW has seen the rising of a new generation of e-retail sites. A number of commercial agent-based systems has been developed to help Internet shoppers decide what to buy and where to buy it from. In such systems, ontologies play a crucial role in supporting the exchange of business data, as they provide a formal vocabulary for the information and unify different views of a domain in a shared and safe cognitive approach.

International Conference on Enterprise Information Systems, 2005

Nowadays, information retrieval and extraction systems perform an important role getting relevant information from the World Wide Web (WWW). Semantic Web, which can be seen as the Web's future, introduces a set of concepts and tools that are being used to insert "intelligence" into contents of the current WWW. Among such concepts, Ontologies play a fundamental role in this new environment. Through ontologies, software agents can cover the Web "understanding" its meaning in order to execute more complex and useful tasks. This work presents an architecture that uses Semantic Web concepts allied to Regular Expressions (regex) to develop a device that retrieves/extracts specific domain information from the Web (HTML documents). The prototype developed, based on this architecture, gets data about offers announced on supermarkets Web sites, using Ontologies and regex to achieve this goal.

2003

Abstract To bring the Semantic Web to life and provide advanced knowledge services, we need efficient ways to access and extract knowledge from Web documents. Although Web page annotations could facilitate such knowledge gathering, annotations are rare and will probably never be rich or detailed enough to cover all the knowledge these documents contain. Manual annotation is impractical and unscalable, and automatic annotation tools remain largely undeveloped.

Sustainability

This paper analyses the potential enhancement of e-commerce websites with Semantic web technologies from the consumers' informational perceived satisfaction point of view. Information quality is a central preoccupation in the field of business information systems' discipline and it relates to the semantic interoperability field of research. The purpose of our study is to investigate the relationship between the enhancement of product text descriptions with semantic annotations and the perceived consumers' satisfaction. We conducted and analyzed a survey questionnaire addressed to e-commerce consumers who bought online products. We found that consumers are interested in finding products with synonym names or that belong to different categories, not necessarily from the same category of products. In addition, consumers are interested about additional text descriptions on different product characteristics and on information about the importance of product characteristics. The main conclusion is that the perceived satisfaction of the online consumers is influenced by an enhanced user experience that relates to specific Semantic web technologies.