Related papers: A Recommender System to Support the Scholarly Comm…

As more scholarly content is born digital or converted to a digital format, digital libraries are becoming increasingly vital to researchers seeking to leverage scholarly big data for scientific discovery. Although scholarly products are…

There exist situations of decision-making under information overload in the Internet, where people have an overwhelming number of available options to choose from, e.g. products to buy in an e-commerce site, or restaurants to visit in a…

Semantic parsing is the task of translating natural language utterances into machine-readable meaning representations. Currently, most semantic parsing methods are not able to utilize contextual information (e.g. dialogue and comments…

Recommender systems are typically designed to fulfill end user needs. However, in some domains the users are not the only stakeholders in the system. For instance, in a news aggregator website users, authors, magazines as well as the…

In this big data era, it is hard for the current generation to find the right data from the huge amount of data contained within online platforms. In such a situation, there is a need for an information filtering system that might help them…

Recommender systems can be characterized as software solutions that provide users convenient access to relevant content. Traditionally, recommender systems research predominantly focuses on developing machine learning algorithms that aim to…

The success of research institutions heavily relies upon identifying the right researchers "for the job": researchers may need to identify appropriate collaborators, often from across disciplines; students may need to identify suitable…

As the amount of data on the World Wide Web continues to grow exponentially, access to semantically structured information remains limited. The Semantic Web has emerged as a solution to enhance the machine-readability of data, making it…

The article first summarizes reasons why current approaches supporting Open Learning and Distance Education need to be complemented by tools permitting lecturers, researchers and students to cooperatively organize the semantic content of…

Linked Open Datasets about scholarly publications enable the development and integration of sophisticated end-user services; however, richer datasets are still needed. The first goal of this Challenge was to investigate novel approaches to…

Data and algorithm sharing is an imperative part of data and AI-driven economies. The efficient sharing of data and algorithms relies on the active interplay between users, data providers, and algorithm providers. Although recommender…

Purpose: Finding scholarly articles is a time-consuming and cumbersome activity, yet crucial for conducting science. Due to the growing number of scholarly articles, new scholarly search systems are needed to effectively assist researchers…

Recommender systems apply data mining techniques and prediction algorithms to predict users' interest on information, products and services among the tremendous amount of available items. The vast growth of information on the Internet as…

The Semantic Web is one of the main efforts aiming to enhance human and machine interaction by representing data in an understandable way for machines to mediate data and services. It is a fast-moving and multidisciplinary field. This study…

Researchers and scientists increasingly rely on specialized information retrieval (IR) or recommendation systems (RS) to support them in their daily research tasks. Paper recommender systems are one such tool scientists use to stay on top…

In the WWW (World Wide Web), dynamic development and spread of data has resulted a tremendous amount of information available on the Internet, yet user is unable to find relevant information in a short span of time. Consequently, a system…

Finding relevant publications is important for scientists who have to cope with exponentially increasing numbers of scholarly material. Algorithms can help with this task as they help for music, movie, and product recommendations. However,…

Research in the Life Sciences depends on the integration of large, distributed and heterogeneous data sources and web services. The discovery of which of these resources are the most appropriate to solve a given task is a complex research…

Scholarly reading often involves engaging with various supplementary materials beyond PDFs to support understanding. In practice, scholars frequently incorporate such external materials into their reading workflow through annotation.…

Recommender systems are indispensable in the realm of online applications, and sequential recommendation has enjoyed considerable prevalence due to its capacity to encapsulate the dynamic shifts in user interests. However, previous…