This paper reviews the research trends that link the advanced technical aspects of
recommendation systems that are used in various service areas and the business aspects of …

In the last 16 years, more than 200 research articles were published about research-paper
recommender systems. We reviewed these articles and present some descriptive statistics in …

We introduce S2ORC, a large corpus of 81.1 M English-language academic papers
spanning many academic disciplines. The corpus consists of rich metadata, paper abstracts …

With the rapid growth of digital publishing, harvesting, managing, and analyzing scholarly
information have become increasingly challenging. The term Big Scholarly Data is coined …

Scientific literature with rich metadata can be represented as a labeled directed graph. This
graph representation enables a number of scientific tasks such as ad hoc retrieval or named …

With the tremendous growth in the number of scientific papers being published, searching
for references while writing a scientific paper is a time-consuming process. A technique that …

We present a content-based method for recommending citations in an academic paper draft.
We embed a given query document into a vector space, then use its nearest neighbors as …

Traditional citation analysis has been widely applied to detect patterns of scientific
collaboration, map the landscapes of scholarly disciplines, assess the impact of research …

Recommender Systems are the set of tools and techniques to provide useful
recommendations and suggestions to the users to help them in the decision-making process …

Citation recommendation describes the task of recommending citations for a given text. Due
to the overload of published scientific works in recent years on the one hand, and the need …