A decade of in-text citation analysis based on natural language processing and machine learning techniques: an overview of empirical studies
In-text citation analysis is one of the most frequently used methods in research evaluation.
We are seeing significant growth in citation analysis through bibliometric metadata, primarily …
We are seeing significant growth in citation analysis through bibliometric metadata, primarily …
A meta-analysis of semantic classification of citations
The aim of this literature review is to examine the current state of the art in the area of citation
classification. In particular, we investigate the approaches for characterizing citations based …
classification. In particular, we investigate the approaches for characterizing citations based …
Bibliometric-enhanced information retrieval: a novel deep feature engineering approach for algorithm searching from full-text publications
Recently, tremendous advances have been observed in information retrieval systems
designed to search for relevant knowledge in scientific publications. Although these …
designed to search for relevant knowledge in scientific publications. Although these …
Scientific document summarization in multi-objective clustering framework
The exponential growth in the number of scientific articles has made it difficult for the
researchers to keep themselves updated with the new developments. Scientific document …
researchers to keep themselves updated with the new developments. Scientific document …
Can machines tell stories? A comparative study of deep neural language models and metrics
Massive textual content has enabled rapid advances in natural language modeling. The use
of pre-trained deep neural language models has significantly improved natural language …
of pre-trained deep neural language models has significantly improved natural language …
Multi-view multi-objective clustering-based framework for scientific document summarization using citation context
Due to the expanding rate of scientific publications, it has become a necessity to summarize
scientific documents to allow researchers to keep track of recent developments. In this …
scientific documents to allow researchers to keep track of recent developments. In this …
An in-text citation classification predictive model for a scholarly search system
We argue that citations in scholarly documents do not always perform equivalent functions
or possess equal importance. To address this problem, we worked with a corpus of over 21 k …
or possess equal importance. To address this problem, we worked with a corpus of over 21 k …
Tweet coupling: A social media methodology for clustering scientific publications
We argue that classic citation-based scientific document clustering approaches, like co-
citation or Bibliographic Coupling, lack to leverage the social-usage of the scientific literature …
citation or Bibliographic Coupling, lack to leverage the social-usage of the scientific literature …
Bibliometric-enhanced information retrieval: preface
The special issue on Bibliometric-enhanced Information Retrieval presents works at the
crossroad between Bibliometrics and Information Retrieval, two domains closely related on …
crossroad between Bibliometrics and Information Retrieval, two domains closely related on …
Automatic text summarization using document clustering named entity recognition
SR Senthamizh, K Arutchelvan - International Journal of …, 2022 - search.proquest.com
Due to the rapid development of internet technology, social media and popular research
article databases have generated many open text information. This large amount of textual …
article databases have generated many open text information. This large amount of textual …