Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"Network Mining"”.
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Evolving Network Representation Learning Based on Random Walks
Large-scale network mining and analysis is key to revealing the underlying dynamics of networks, not easily observable before. Lately, there is a fast-growing interest in learning low-dimensional continuous representations of networks that can be utilized to perform highly accurate and scalable …
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IDENTIFYING AND EXPLOITING SYNTHETIC LETHALITY FOR CANCER THERAPEUTICS
… SL pairs and to utilize SL pairs in biological network mining and clinical decision support. Two new methods are designed to identify potential SL pairs using multiple genomic data sources, based on statistical hypothesis testing and collective matrix factorization. A new algorithm to mine and …
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Probabilistic interpretation of path-based relevance in heterogeneous information networks
As a powerful representation paradigm for networked and multi-typed data, the heterogeneous information network (HIN) is ubiquitous. Meanwhile, defining proper relevance measures has always been a fundamental problem and of great pragmatic importance for network mining tasks. Inspired by the …
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Pattern extraction and clustering for high-dimensional discrete data
… factorizations with interesting problems in data mining and machine learning. We propose a framework for solving several low-rank matrix factorization problems, including binary matrix factorization, constrained binary matrix factorization, weighted constrained binary matrix factorization, densest …
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Harnessing heterogeneous association in real-world networks
Real-world networks often contain heterogeneity due to the heterogeneous nature of the world. A few examples of such networks include multi-view social networks, heterogeneous bibliographic networks, biomedical networks, etc. Ostensibly the heterogeneity of real-world network appears as the typed …
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Entity recommendation and search in heterogeneous information networks
… development of social media and information network-based web services, data mining studies on network analysis have gained increasing attention in recent years. Many early studies focus on homogeneous network mining, with the assumption that the network nodes and links are of the same type …
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Parallel Mining and Analysis of Triangles and Communities in Big Networks
A network (graph) is a powerful abstraction for interactions among entities in a system. Examples include various social, biological, collaboration, citation, and co-purchase networks. Real-world networks are often characterized by an abundance of triangles and the existence of well-structured …
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HPC-based Parallel Algorithms for Generating Random Networks and Some Other Network Analysis Problems
… biological, social, and various infrastructure networks, which have, in turn, contributed to the rise of massive networks. During the past decade, analyzing and mining of these networks has become an emerging research area with many real-world applications. The most relevant problems in this …
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Social analytics for health integration, intelligence, and monitoring
Nowadays, patient-generated social health data are abundant and Healthcare is changing from the authoritative provider-centric model to collaborative and patient-oriented care. The aim of this dissertation is to provide a Social Health Analytics framework to utilize social data to solve the …
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Recommendations in text-rich heterogeneous networks
… of performing recommendations in a Heterogeneous Network which has auxiliary text information present with the nodes. We cover the relevant background and illustrate heterogeneous networks along with related tasks through the help of examples. We choose the setting of Bibliographic Heterogeneous …
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Network Sampling through Crawling
… extremely important. We consider the problem of network sampling through crawling, in which the data collectors have no knowledge of the network of interest except the identity of a starting node. The data collector can expand the observed sample by querying an observed node. While the network …