Mining and Learning with Graphs
نویسندگان
چکیده
Link-based data may be studied formally by means of unordered trees. On a dataset formed by such link-based data, a natural notion of support-based closure can be immediately defined. Abstracting information from subsets of such data requires, first, a formal notion of intersection; second, deeper understanding of the notion of closure; and, third, efficient algorithms for computing intersections on unordered trees. We provide answers to these three questions.
منابع مشابه
Bibliometric Networks on Analyze Flipped Learning Research
Aim: The purpose is to provide a comprehensive overview of the current state of research in the field of flipped learning and classroom. It is a science metrics attempt to extract and analyze bibliographic networks based on the international scientific indexing (ISI) Methodology: Systematic search technique was applied: A set of scientific productions indexed in the field of flipped learning an...
متن کاملBig Graph Mining: Frameworks and Techniques
Big graph mining is an important research area and it has attracted considerable attention. It allows to process, analyze, and extract meaningful information from large amounts of graph data. Big graph mining has been highly motivated not only by the tremendously increasing size of graphs but also by its huge number of applications. Such applications include bioinformatics, chemoinformatics and...
متن کاملROC Graphs: Notes and Practical Considerations for Data Mining Researchers
Receiver Operating Characteristics (ROC) graphs are a useful technique for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been increasingly adopted in the machine learning and data mining research communities. Although ROC graphs are apparently simple, there are some common misconceptions and pitfalls w...
متن کاملPolynomial-Delay Enumeration of Monotonic Graph Classes
Algorithms that list graphs such that no two listed graphs are isomorphic, are important building blocks of systems for mining and learning in graphs. Algorithms are already known that solve this problem efficiently for many classes of graphs of restricted topology, such as trees. In this article we introduce the concept of a dense augmentation schema, and introduce an algorithm that can be use...
متن کاملRDF2Vec: RDF Graph Embeddings for Data Mining
Linked Open Data has been recognized as a valuable source for background information in data mining. However, most data mining tools require features in propositional form, i.e., a vector of nominal or numerical features associated with an instance, while Linked Open Data sources are graphs by nature. In this paper, we present RDF2Vec, an approach that uses language modeling approaches for unsu...
متن کاملDynamic Graph-based Relational Learning of Temporal Patterns in Biological Networks Changing over Time
We propose a dynamic graph-based relational learning approach using graph-rewriting rules to analyze how biological networks change over time. The analysis of dynamic biological networks is necessary to understand life at the systemlevel, because biological networks continuously change their structures and properties while an organism performs various biological activities to promote reproducti...
متن کامل