Lower-dimensional representation of scientific text has attracted much attention among
researchers due to its impact on many data mining and recommendation tasks. This paper …

Citation recommendation systems mainly help researchers find the lists of references that
related to their interests effectively and automatically. The existing approaches face the …

A network is a structure that can represent an organic relationship of observations. Network
representation learning has the advantage of extracting latent features in a network. In …

Text representation is the preliminary work for in-depth analysis and mining of information in
scientific papers. It directly affects the effects of downstream tasks such as, scientific papers …

Over the last century, we observe a steady and exponential growth of scientific publications
globally. The overwhelming amount of available literature makes a holistic analysis of the …

This study aims at representing research patterns of bibliographic entities (eg, scholars,
papers, and venues) with a fixed-length vector. Bibliographic network structures rooted in …

Scientific articles usually follow a common pattern of discourse, and their contents can be
divided into several facets, such as objective, method, and result. We examine the efficacy of …

We provide an up-to-date view on the knowledge management system ScienceWISE (SW)
and address issues related to the automatic assignment of articles to research topics. So far …

Influential scientific papers tend to be primarily based on combinations of prior works.
However, assessing the potential impact of a new scientific paper remains a challenging …

We present Paper2vec, a novel neural network embedding based approach for creating
scientific paper representations which make use of both textual and graph-based …