A review of text-based recommendation systems
Many websites over the Internet are producing a variety of textual data; such as news,
research articles, ebooks, personal blogs, and user reviews. In these websites, the textual …
research articles, ebooks, personal blogs, and user reviews. In these websites, the textual …
Review of ontology-based recommender systems in e-learning
In recent years there has been an enormous increase in learning resources available online
through massive open online courses and learning management systems. In this context …
through massive open online courses and learning management systems. In this context …
A hybrid probabilistic multiobjective evolutionary algorithm for commercial recommendation systems
As big-data-driven complex systems, commercial recommendation systems (RSs) have
been widely used in such companies as Amazon and Ebay. Their core aim is to maximize …
been widely used in such companies as Amazon and Ebay. Their core aim is to maximize …
A comparative overview of hybrid recommender systems: Review, challenges, and prospects
Recommender System (RS) helps to find the items according to user interest and provides
various suggestions that help in the decision‐making process. These suggestions depend …
various suggestions that help in the decision‐making process. These suggestions depend …
User profile correlation-based similarity (UPCSim) algorithm in movie recommendation system
Collaborative filtering is one of the most widely used recommendation system approaches.
One issue in collaborative filtering is how to use a similarity algorithm to increase the …
One issue in collaborative filtering is how to use a similarity algorithm to increase the …
An edge intelligence empowered recommender system enabling cultural heritage applications
Recommender systems are increasingly playing an important role in our life, enabling users
to find “what they need” within large data collections and supporting a variety of applications …
to find “what they need” within large data collections and supporting a variety of applications …
An integrated recommender system for improved accuracy and aggregate diversity
Abstract Information explosion creates dilemma in finding preferred products from the digital
marketplaces. Thus, it is challenging for online companies to develop an efficient …
marketplaces. Thus, it is challenging for online companies to develop an efficient …
Deep learning-enhanced framework for performance evaluation of a recommending interface with varied recommendation position and intensity based on eye …
P Sulikowski, T Zdziebko - Electronics, 2020 - mdpi.com
The increasing amount of marketing content in e-commerce websites results in the limited
attention of users. For recommender systems, the way recommended items are presented …
attention of users. For recommender systems, the way recommended items are presented …
Item feature refinement using matrix factorization and boosted learning based user profile generation for content-based recommender systems
A Pujahari, DS Sisodia - Expert Systems with Applications, 2022 - Elsevier
A content-based recommender system uses essential item features that play a crucial role in
building quality user preference profiles. However, in most real-world datasets, the item …
building quality user preference profiles. However, in most real-world datasets, the item …
User preferences modeling using dirichlet process mixture model for a content-based recommender system
Recommender systems have been developed to assist users in retrieving relevant
resources. Collaborative and content-based filtering are two basic approaches that are used …
resources. Collaborative and content-based filtering are two basic approaches that are used …