Resolving data sparsity and cold start problem in collaborative filtering recommender system using linked open data
The web contains a huge volume of data, and it's populating every moment to the point that
human beings cannot deal with the vast amount of data manually or via traditional tools …
human beings cannot deal with the vast amount of data manually or via traditional tools …
A novel matrix factorization model for recommendation with LOD-based semantic similarity measure
R Wang, HK Cheng, Y Jiang, J Lou - Expert Systems with Applications, 2019 - Elsevier
Collaborative Filtering (CF) algorithms have been widely used to provide personalized
recommendations in e-commerce websites and social network applications. Among them …
recommendations in e-commerce websites and social network applications. Among them …
Measuring semantic distance for linked open data-enabled recommender systems
G Piao, JG Breslin - Proceedings of the 31st Annual ACM Symposium on …, 2016 - dl.acm.org
The Linked Open Data (LOD) initiative has been quite successful in terms of publishing and
interlinking data on the Web. On top of the huge amount of interconnected data, measuring …
interlinking data on the Web. On top of the huge amount of interconnected data, measuring …
Semantic relatedness in DBpedia: A comparative and experimental assessment
The evaluation of semantic relatedness between web resources is still an open challenge.
This paper focuses on knowledge-based methods that provide an alternative to corpus …
This paper focuses on knowledge-based methods that provide an alternative to corpus …
What's in an index: Extracting domain-specific knowledge graphs from textbooks
I Alpizar-Chacon, S Sosnovsky - … of the ACM Web Conference 2022, 2022 - dl.acm.org
A typical index at the end of a textbook contains a manually-provided vocabulary of terms
related to the content of the textbook. In this paper, we extend our previous work on …
related to the content of the textbook. In this paper, we extend our previous work on …
A study of the similarities of entity embeddings learned from different aspects of a knowledge base for item recommendations
G Piao, JG Breslin - The Semantic Web: ESWC 2018 Satellite Events …, 2018 - Springer
The recent development of deep learning approaches provides a convenient way to learn
entity embeddings from different aspects such as texts and a homogeneous or …
entity embeddings from different aspects such as texts and a homogeneous or …
MasonTigers at SemEval-2024 Task 1: An Ensemble Approach for Semantic Textual Relatedness
This paper presents the MasonTigers entry to the SemEval-2024 Task 1-Semantic Textual
Relatedness. The task encompasses supervised (Track A), unsupervised (Track B), and …
Relatedness. The task encompasses supervised (Track A), unsupervised (Track B), and …
Towards a privacy conserved and linked open data based device recommendation in iot
Abstract Interconnecting Internet of Things (IoT) devices creates a network of services
capable of working together to accomplish certain goals in different domains. The …
capable of working together to accomplish certain goals in different domains. The …
PLDSD: propagated linked data semantic distance
Linked Open Data (LOD) has been exploited by recommender systems in different ways.
One way measures the semantic distance between LOD resources so that nearby resources …
One way measures the semantic distance between LOD resources so that nearby resources …
Two-Stage Detection of Semantic Redundancies in RDF Data
Y Chen, D Li, L Yan, Z Ma - Journal of Web Engineering, 2022 - ieeexplore.ieee.org
With the enrichment of the RDF (resource description framework), integrating diverse data
sources may result in RDF data duplication. Failure to effectively detect the duplicates brings …
sources may result in RDF data duplication. Failure to effectively detect the duplicates brings …