The future work is to consider dynamic relation on social data mining and how graph based approaches adapt from the new situations.Wang, Guan.Engineering,Computer.
graph-based substructure pattern mining abstract we investigate new approaches frequentgraph-based pattern mining graphdatasets novelalgorithm called gspan (graph-based substructure pattern mining), which discovers frequent substructures without candidate generation. gspan builds newlexicographic order among ...
A Comprehensive Survey on Deep Graph Representation Learning Methods 2023, Journal of Artificial Intelligence Research GraphMAE: Self-Supervised Masked Graph Autoencoders 2022, Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining View all citing articles on ScopusVi...
especially including healthcare assistance and human-robot interaction2. Many researchers have addressed the problem of revealing the emotions from speech signals, by exploiting a variety of speech characteristics, with the most prominent being pitch, energy, jitter and...
Two nodes in the graph can have an edge between them if and only if those two entities have some relation in UMLS. There are various types of relations present in UMLS and this approach considers all types of relations i.e. no manual filter is applied on type of relations. This makes ...
The WEKA data mining software: an update 2009, 11(1):10–18. Automated concept-level information extraction to reduce the need for custom software and rules development 2011, 18(5):607–613. Kintsch W: Comprehension: a paradigm for cognition. Cambridge University Press; 1998:461. Google Schol...
Graph-based methods are capable of learning molecular representations by operating the convolutions on the encoded molecular graphs directly. In the graph representation for a molecule, the connectivity relation between atoms is represented by a graphG = (V,E). Here, the nodesVare represented...
graph neural networks have also been well applied in relation prediction. For example, Liu et al. [35] proposed a model based on a multi-component Graph Attention Network (GAT [36]) for microbe-disease association prediction. This model consists of three parts: a decomposer and combiner based...
Mining point-of-interest data from social networks for urban land use classification and disaggregation. Comput. Environ. Urban Syst. 2015, 53, 36–46. [Google Scholar] [CrossRef] Kunze, C.; Hecht, R. Semantic enrichment of building data with volunteered geographic information to improve ...
Entity structure within and throughout: Modeling mention dependencies for document-level relation extraction. In: Proceedings of the AAAI Conference on Artificial Intelligence. Online: AAAI, 14149–14157 Xu Z, Dang Y, Zhang Z, Chen J (2020). Typical short-term remedy knowledge mining for product...