In the last decade, automatic extraction and classification of in-text citations have received
immense popularity and have become one of the most frequently used techniques to …

Some science and technology policies promote collaboration between natural sciences
(NS) and social sciences and humanities (SSH) on research topics related to complex …

This paper aims to map the trending topics of Bibliometric-enhanced Information Retrieval
(BIR) based on co-word network analysis and strategic diagram. The bibliographic dataset …

In recent scientific advances, Artificial Intelligence and Natural Language Processing are the
major contributors to classifying documents and extracting information. Classifying citations …

The amount of information in digital libraries (DLs) has been experiencing rapid growth. With
the intense competition for research breakthroughs, researchers often intentionally or …

Citations are used to establish a link between articles. This intent has changed over the
years, and citations are now being used as a criterion for evaluating the research work or the …

Semantic tags can enrich citation graphs by inter-connecting papers with citation reasons.
One of the best sources of knowledge to tell the reason for citation is the author himself …

Identification of influential research articles has been an area of interest for quite a long time.
Usually, the importance of an article is measured by the number of citations it has gained …

Heretofore, the only way to evaluate an author has been frequency-based citation metrics
that assume citations to be of a neutral sentiment. However, considering the sentiment …

In recent years, large datasets of citation contexts from research publications have become
available for scientometric studies. Such citation contexts contain different characteristics of …