CD-CARS: Cross-domain context-aware recommender systems
In this paper, we address two research topics in Recommender Systems (RSs) which have
been developed in parallel without a deeper integration: Cross-Domain RS (CDRS) and …
been developed in parallel without a deeper integration: Cross-Domain RS (CDRS) and …
Context-aware user and item representations based on unsupervised context extraction from reviews
User reviews often supply valuable information to alleviate the rating sparsity problem that
can occur in recommender systems. Recent work has employed deep learning techniques …
can occur in recommender systems. Recent work has employed deep learning techniques …
[PDF][PDF] Context aware recommender system algorithms: state of the art and focus on factorization based methods
Abstract Context Aware Recommender Systems (CARS) have become an important
research area since its introduction in 2001 by (Herlocker and Konstan, 2001) and …
research area since its introduction in 2001 by (Herlocker and Konstan, 2001) and …
Textual context aware factorization machines: Improving recommendation by leveraging users' reviews
Context Aware Recommender Systems (CARS) are Recommender Systems (RS) that
consider, in addition to users and items, other contextual information to provide more …
consider, in addition to users and items, other contextual information to provide more …
[PDF][PDF] Extracting Context Data from User Reviews for Recommendation: A Linked Data Approach.
PG Campos, N Rodríguez-Artigot… - ComplexRec …, 2017 - arantxa.ii.uam.es
In this paper we describe a novel approach to extract contextual information from user
reviews, which can be exploited by context-aware recommender systems. The approach …
reviews, which can be exploited by context-aware recommender systems. The approach …
Review Aware Recommender System: Using Reviews for Context Aware Recommendation
Context aware recommender systems (CARS) are recommender systems (RS) that provide
recommendations according to user contexts. The first challenge for building such a system …
recommendations according to user contexts. The first challenge for building such a system …
Context aware contrastive opinion summarization
SK Lavanya, B Parvathavarthini - … Intelligence in Data Science: Third IFIP …, 2020 - Springer
Abstract Model-based approaches for context-sensitive contrastive summarization depend
on hand-crafted features for producing a summary. Deriving these hand-crafted features …
on hand-crafted features for producing a summary. Deriving these hand-crafted features …
[PDF][PDF] Recomendación contextualizada usando una ontología de contexto genérica y de gran escala construida semiautomáticamente a partir de DBpedia
NR Artigot, PGC Soto, IC Gutiérrez - core.ac.uk
Los sistemas de recomendación son un tipo específico de filtrado de información que
presenta a un usuario recursos (películas, música, libros, noticias, páginas web, etc.) que le …
presenta a un usuario recursos (películas, música, libros, noticias, páginas web, etc.) que le …
Context-sensitive contrastive feature-based opinion summarisation of online reviews
SK Lavanya, B Parvathavarthini - International Journal of …, 2020 - inderscienceonline.com
Contrastive opinion summarisation (COS) systems produce summary by selecting and
aligning contrastive sentences from a set of positive and negative opinionated sentences …
aligning contrastive sentences from a set of positive and negative opinionated sentences …
[PDF][PDF] Unsupervised Context Extraction for Review-Based Recommendations.
P Sitkrongwong - 2020 - ir.soken.ac.jp
Recommender systems were devised to provide personalized recommendations on suitable
items that would match the individual users' interests. The standard recommendation …
items that would match the individual users' interests. The standard recommendation …