Related papers: Finding and Recommending Scholarly Articles
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…
Artificial intelligence (AI) has acquired notorious relevance in modern computing as it effectively solves complex tasks traditionally done by humans. AI provides methods to represent and infer knowledge, efficiently manipulate texts and…
The past few centuries have witnessed a dramatic growth in scientific and technological knowledge. However, the nature of that growth - whether exponential or otherwise - remains controversial, perhaps partly due to the lack of quantitative…
Analyzing 13,455 journals listed in the Journal Citation Report (Thomson Reuters) from 1997 through 2013, we report that the mean cited half-life of the scholarly literature is 6.5 years and growing at a rate of 0.13 years per annum.…
Considering the premise that the number of products offered grow in an exponential fashion and the amount of data that a user can assimilate before making a decision is relatively small, recommender systems help in categorizing content…
The current communication presents a simple exercise with the aim of solving a singular problem: the retrieval of extremely large amounts of items in the Web of Science interface. As it is known, Web of Science interface allows a user to…
The task of expert finding has been getting increasing attention in information retrieval literature. However, the current state-of-the-art is still lacking in principled approaches for combining different sources of evidence in an optimal…
Scientific literature has been growing exponentially for decades, with publications from the last twenty years now comprising 60% of all academic output. While the impact of information overload on news and social-media consumption is…
Researchers spend a great deal of time reading research papers. Keshav (2012) provides a three-pass method to researchers to improve their reading skills. This article extends Keshav's method for reading a research compendium. Research…
Recommender Systems are tools that improve how users find relevant information in web systems, so they do not face too much information. In order to generate better recommendations, the context of information should be used in the…
With the rapid growth of the Internet and overwhelming amount of information that people are confronted with, recommender systems have been developed to effiectively support users' decision-making process in online systems. So far, much…
Scholarly article impact reflects the significance of academic output recognised by academic peers, and it often plays a crucial role in assessing the scientific achievements of researchers, teams, institutions and countries. It is also…
Information retrieval (IR) and recommender systems (RS) have been employed for addressing search tasks executed during literature review and the overall scholarly communication lifecycle. Majority of the studies have concentrated on…
As the field of recommender systems has developed, authors have used a myriad of notations for describing the mathematical workings of recommendation algorithms. These notations ap-pear in research papers, books, lecture notes, blog posts,…
The emergence of academic search engines (Google Scholar and Microsoft Academic Search essentially) has revived and increased the interest in the size of the academic web, since their aspiration is to index the entirety of current academic…
Modern recommender systems operate in uniquely dynamic settings: user interests, item pools, and popularity trends shift continuously, and models must adapt in real time without forgetting past preferences. While existing tutorials on…
Recommender systems are central to modern online platforms, but a popular concern is that they may be pulling society in dangerous directions (e.g., towards filter bubbles). However, a challenge with measuring the effects of recommender…
Recommender systems are effective tools for mitigating information overload and have seen extensive applications across various domains. However, the single focus on utility goals proves to be inadequate in addressing real-world concerns,…
We stand at the foot of a significant inflection in the trajectory of scientific discovery. As society continues on its fast-paced digital transformation, so does humankind's collective scientific knowledge and discourse. We now read and…
Classifying journals or publications into research areas is an essential element of many bibliometric analyses. Classification usually takes place at the level of journals, where the Web of Science subject categories are the most popular…