With the rise of social media, individuals face challenges in decision-making due to the
abundance of options available. Recommender Systems (RSs) leverage Artificial …

During the last decades, recommender systems are becoming quite popular since they
provide great assistance to users on social networks and library websites. Unfortunately, the …

Abstract The Hayes-Wheelwright Product-Process Matrix (PPM) has historically been a
pivotal tool in manufacturing, guiding firms to strategically align product volume and variety …

With the rapid growth of research publications, it has become time-consuming and
cumbersome for researchers to find research papers relevant to their research. Research …

Pre-trained models learn general representations from large datsets which can be fine-
turned for specific tasks to significantly reduce training time. Pre-trained models like …

Abstract Recommendation (recommender) systems (RS) have played a significant role in
both research and industry in recent years. In the area of academia, there is a need to help …

Abstract Aspect-Controllable Related Papers Recommendation (ACRPR) aims to satisfy
users' fine-grained needs for specific aspects when finding related papers. Existing …

Purpose This paper aims to curate open research knowledge graph (ORKG) with papers
related to ontology learning and define an approach using ORKG as a computer-assisted …

Digital libraries provide different access paths, allowing users to explore their collections.
For instance, paper recommendation suggests literature similar to some selected paper …

Authoring survey or review articles still requires significant tedious manual effort, despite
many advancements in research knowledge management having the potential to improve …