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 20 of 82 for “"Information Networks"”.
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Mining heterogeneous information networks
… entities are interconnected, forming gigantic networks. By structuring these objects and their interactions into multiple types, such networks become semi-structured heterogeneous information networks. Most real-world applications that handle big data, including interconnected social media and …
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Outlier detection for information networks
The study of networks has emerged in diverse disciplines as a means of analyzing complex relationship data. There has been a significant amount of work in network science which studies properties of networks, querying over networks, link analysis, influence propagation, network optimization, and …
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On querying large scale information networks
"Social and technical information systems usually consist of a large number of interacting physical, conceptual, and human/societal entities. Such individual entities are interconnected to form large and sophisticated networks, which, without loss of generality, are often refereed to as information …
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Publication venue recommendation in heterogeneous information networks
… which make recommendations using co-author networks and author-venue links in the bibliographic information networks. However, we have not yet seen a general framework that incorporates a broad range of both content-based features and network-based features, which are potentially capable of …
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Distributed detection and coding in information networks
This thesis investigates the distributed information and detection of a binary source through a parallel system of relays. Each relay observes the source output through a noisy channel, and the channel outputs are independent conditional on the source input. The relays forward limited information …
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Managing information : networks, value, policy, and principles
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 1998.
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Tie Inducement using Closure Analysis in Information Networks
… work addresses one important problem in Social Networks Analysis, namely link prediction. Link Prediction is important to understand and evaluate the change in structure for a certain social network over a given period of time. While different methods exist to address link prediction in this …
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Entity recommendation and search in heterogeneous information networks
With the rapid 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 …
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Discovering roles and types from hierarchical information networks
… from the social to the scientific including information, media, biology, chemistry, medical systems, and e-commerce systems. These graphs are called information networks because they represent bits of information and their relationships. In my thesis, I investigate the principles and …
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Graph regularized transductive classification on heterogeneous information networks
A heterogeneous information network is a network composed of multiple types of objects and links. Recently, it has been recognized that strongly-typed heterogeneous information networks are prevalent in the real world. Sometimes, label information is available for some objects. Learning from such …
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IVIS: Search and visualization on heterogeneous information networks
… search and visualization on heterogeneous information networks. We first build our system on a specialized heterogeneous information network: DBLP. The system aims to facilitate people, especially computer science researchers, toward a better understanding and user experience about academic …
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Relation2vec: Contextualized network embedding for heterogeneous information networks
… are often combinatorial, to the contemporary networks is challenging due to the sheer size of the present day network data. On the other hand, deep neural networks (DNNs) have been exceptionally successful at learning from big data and achieved superhuman performance in the fields of computer …
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Leveraging heterogeneous information networks for personalized entity recommendation
… simplification, instead we utilize heterogeneous information networks to capture the complexity of the behaviors for which we are seeking to make recommendations. Our proposed approach captures the different behaviors of individuals by examining their heterogeneous relationships in the network and …
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Privacy risk and de-anonymization in heterogeneous information networks
… the released social network is a heterogeneous information network. Prior work has shown how privacy can be compromised in homogeneous information networks by the use of specific types of graph patterns. We show how the extra information derived from heterogeneity can be used to relax these …
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Density-based clustering of information networks by substructure optimization
Information networks, such as biological or social networks, contain groups of related entities, which can be identified by clustering. Density-based clustering (DBC) differs from vertex-partitioning methods in that some vertices are classified as noise. This approach is useful in practice to …
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Information trust, inference and transfer in social and information networks
… overarching goal is to aggregate crowdsourced information that is collected from computing systems based on social networks and represented in information networks. Due to the autonomous nature of such a social computing paradigm, the crowdsourced information is often subject to low quality, …
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Probabilistic interpretation of path-based relevance in heterogeneous information networks
… 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 probabilistic interpretation of existing …
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Constructing and mining structured heterogeneous information networks from massive text corpora
In today's information society, we are soaked with overwhelming amounts of natural-language text data, ranging from news articles and social media posts to research literature, medical records, and corporate reports. A grand challenge for data miners is to develop effective and scalable methods to …
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A schema conversion approach for constructing heterogeneous information networks from documents
Information networks with multi-typed nodes and edges with different semantics are called heterogenous information networks. Since heterogeneous information networks embed more complex information than homogeneous information networks due to their multi-typed nodes and edges, mining such networks …
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Constructing and modeling text-rich information networks: a phrase mining-based approach
… which is often characterized by an explosion of information. Most of this surge owes its origin to the unstructured data in the wild like words, images and video as comparing to the structured information stored in fielded form in databases. The proliferation of text-heavy data is particularly …
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