A path-based recommendations approach for online systems via hyperbolic network embedding

Due to the huge expand in global markets and financial transactions, the importance of E-commerce has grown significantly, so to achieve fully functioning, scalable, reliable, efficient, secure, and user-friendly E-commerce system, Adequate system analysis and design procedures are essential. On the other hand The internet vast growing has totally altered the way most companies work. The Internet has created a means for e-Commerce the internet has created a way to provide a unique avenue for companies and customers to sell and buy goods and services. When creating an e-commerce website, there are several goals that must be taken into account, one of them is how to Increase the site’s efficiency to ensure customer turnout and thus achieve the required material profits. There are several methods that are followed to increase the efficiency of the site. One of these methods is the recommender system. This paper produces a study overview of the value of recommended systems and thoroughly analyzed Collaborative Recommender System (CF) techniques with its techniques., which presents proposals to customers according to their interests, making it easier for the customer to search and thus choose the goods that suit him.

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StreetLines: A Smart and Scalable Tourism Platform Based on Efficient Knowledge-Mining

Alexandridis,

Siolas,

Papagiannis

et al. 2024

Digital

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Identifying and understanding visitor needs and expectations is of the utmost importance for a number of stakeholders and policymakers involved in the touristic domain. Apart from traditional forms of feedback, an abundance of related information exists online, scattered across various data sources like online social media, tourism-related platforms, traveling blogs, forums, etc. Retrieving and analyzing the aforementioned content is not a straightforward task and in order to address this challenge, we have developed the StreetLines platform, a novel information system that is able to collect, analyze and produce insights from the available tourism-related data. Its highly modular architecture allows for the continuous monitoring of varying pools of heterogeneous data sources whose contents are subsequently stored, after preprocessing, in a data repository. Following that, the aforementioned data feed a number of independent and parallel processing modules that extract useful information for all individuals involved in the tourism domain, like place recommendation for visitors and sentiment analysis and keyword extraction reports for professionals in the tourism industry. The presented platform is an outcome of the StreetLines project and apart from the contributions of its individual components, its novelty lies in the holistic approach to knowledge extraction and tourism data mining.

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A path-based recommendations approach for online systems via hyperbolic network embedding

Cited by 4 publications

References 17 publications

A Survey of Graph Curvature and Embedding in Non-Euclidean Spaces

A Survey of Graph Curvature and Embedding in Non-Euclidean Spaces

Recommendation Systems For E-commerce Systems An Overview

StreetLines: A Smart and Scalable Tourism Platform Based on Efficient Knowledge-Mining

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