The four dimensions of social network analysis: An overview of research methods, applications, and software tools
Social network based applications have experienced exponential growth in recent years.
One of the reasons for this rise is that this application domain offers a particularly fertile …
One of the reasons for this rise is that this application domain offers a particularly fertile …
Topic analysis and development in knowledge graph research: A bibliometric review on three decades
Abstract Knowledge graph as a research topic is increasingly popular to represent structural
relations between entities. Recent years have witnessed the release of various open-source …
relations between entities. Recent years have witnessed the release of various open-source …
Knowledge-enabled BERT for aspect-based sentiment analysis
A Zhao, Y Yu - Knowledge-Based Systems, 2021 - Elsevier
To provide explainable and accurate aspect terms and the corresponding aspect–sentiment
detection, it is often useful to take external domain-specific knowledge into consideration. In …
detection, it is often useful to take external domain-specific knowledge into consideration. In …
Self-supervised graph convolutional network for multi-view clustering
Despite the promising preliminary results, existing graph convolutional network (GCN)
based multi-view learning methods directly use the graph structure as view descriptor, which …
based multi-view learning methods directly use the graph structure as view descriptor, which …
BaGFN: broad attentive graph fusion network for high-order feature interactions
Modeling feature interactions is of crucial significance to high-quality feature engineering on
multifiled sparse data. At present, a series of state-of-the-art methods extract cross features …
multifiled sparse data. At present, a series of state-of-the-art methods extract cross features …
A convolutional stacked bidirectional LSTM with a multiplicative attention mechanism for aspect category and sentiment detection
TE Trueman, E Cambria - Cognitive Computation, 2021 - Springer
Traditionally, sentiment analysis is a binary classification task that aims to categorize a piece
of text as positive or negative. This approach, however, can be too simplistic when the text …
of text as positive or negative. This approach, however, can be too simplistic when the text …
Temporal network embedding for link prediction via VAE joint attention mechanism
Network representation learning or embedding aims to project the network into a low-
dimensional space that can be devoted to different network tasks. Temporal networks are an …
dimensional space that can be devoted to different network tasks. Temporal networks are an …
Trans4E: Link prediction on scholarly knowledge graphs
Abstract The incompleteness of Knowledge Graphs (KGs) is a crucial issue affecting the
quality of AI-based services. In the scholarly domain, KGs describing research publications …
quality of AI-based services. In the scholarly domain, KGs describing research publications …
On proximity and structural role-based embeddings in networks: Misconceptions, techniques, and applications
Structural roles define sets of structurally similar nodes that are more similar to nodes inside
the set than outside, whereas communities define sets of nodes with more connections …
the set than outside, whereas communities define sets of nodes with more connections …
OntoSenticNet 2: Enhancing reasoning within sentiment analysis
Sentiment analysis is a trending topic that has not yet exhausted its attractiveness, despite
the huge research effort carried out in the last 15 years. One of the most promising directions …
the huge research effort carried out in the last 15 years. One of the most promising directions …