Results 81 to 90 of about 693,638 (193)

Including Item Characteristics in the Probabilistic Latent Semantic Analysis Model for Collaborative Filtering [PDF]

We propose a new hybrid recommender system that combines some advantages of collaborative and content-based recommender systems. While it uses ratings data of all users, as do collaborative recommender systems, it is also able to recommend new items and ...
Kagie, M., Loos, M.J.H.M. van der, Wezel, M.C. van   +2 more
core   +1 more source

Content-Based Book Recommending Using Learning for Text Categorization

, 1999
Recommender systems improve access to relevant products and information by making personalized suggestions based on previous examples of a user's likes and dislikes. Most existing recommender systems use social filtering methods that base recommendations
Mooney, Raymond J., Roy, Loriene
core   +3 more sources

Ontologies and Information Extraction

, 2005
This report argues that, even in the simplest cases, IE is an ontology-driven process. It is not a mere text filtering method based on simple pattern matching and keywords, because the extracted pieces of texts are interpreted with respect to a ...
Nazarenko, Adeline, Nédellec, Claire
core   +1 more source

Leveraging Machine Learning for Personalized Recommendations in Mobile Tourism: A Study on Collaborative and Content-Based Filtering

Journal of Technology Informatics and Engineering
The rapid growth of the tourism industry, coupled with the increasing reliance on mobile technology, necessitates the development of intelligent applications that enhance user experience through personalized recommendations.
ahmad zainudin, Edy Siswanto
doaj   +1 more source

Comparison of Selected Algorithms in Movie Recommender System

Applied Sciences
Recommender systems are currently very popular, and their main goal is to propose relevant content to users based on various parameters. The main goal of this paper is to create a comprehensive comparison of selected algorithms in movie recommender ...
Bogdan Walek, Ondřej Sládek
doaj   +1 more source

An enhanced hybrid recommender system using an adaptive optimization approach

Discover Artificial Intelligence
E-commerce platforms generate vast amounts of data, making it challenging for customers to find relevant products efficiently. Recommendation Systems (RS) address this issue by analysing user interactions to suggest personalized items. The two primary RS
Chour Singh Rajpoot, Varun Tiwari, Santosh Kumar Vishwakarma   +2 more
doaj   +1 more source

Content-based image filtering

, 2013
This paper presents an adaptive content-based image denoising technique. This technique uses image area classification for two purposes: perform more precise filtering and decrease computation complexity compared to modern filters of the same quality performance. Overview of several top image filtering techniques was made.
openaire   +1 more source

Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator

International Journal of Information and Communication Technology Research, 2010
Recommender systems have become significant tools in electronic commerce, proposing effectively those items that best meet the preferences of users. A variety of techniques have been proposed for the recommender systems such as, collaborative filtering ...
Javad Basiri, Azadeh Shakery, Behzad Moshiri, Morteza Zihayat   +3 more
doaj  

Deep learning and content-based filtering techniques for improving plant disease identification and treatment recommendations: A comprehensive review. [PDF]

Heliyon
Isinkaye FO, Olusanya MO, Singh PK.
europepmc   +1 more source

DeepSentRec: a deep learning-based sentiment-aware product recommendation system. [PDF]

Sci Rep
Kollu SRP, Garapati Y.
europepmc   +1 more source