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.
Results
Showing 1 to 17 of 17 for “"heterogeneous information networks"”.
-
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 …
-
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 …
-
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 …
-
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 …
-
IVIS: Search and visualization on heterogeneous information networks
… a system to support 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 …
-
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 …
-
Leveraging heterogeneous information networks for personalized entity recommendation
… necessitates approaches which can utilize the heterogeneous environments in which the recommendation task is set rather than reducing them to single relationship. In this work, we explore the problem of entity recommendation without such a simplification, instead we utilize heterogeneous …
-
Privacy risk and de-anonymization in heterogeneous information networks
… multiple types, 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 …
-
Probabilistic interpretation of path-based relevance in heterogeneous information networks
… 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 probabilistic interpretation of …
-
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 …
-
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 …
-
A framework for dynamic heterogeneous information networks change discovery based on knowledge engineering and data mining methods
Information Networks are collections of data structures that are used to model interactions in social and living phenomena. They can be either homogeneous or heterogeneous and static or dynamic depending upon the type and nature of relations between the network entities. Static, homogeneous and …
-
AsymSim: meta path-based similarity with asymmetric relations
… search is a deceptively complex problem in information network analysis. Past research has primarily focused on similarity search in homogeneous networks, but real world data is often best represented using heterogeneous information networks, with multiple node and relation types carrying …
-
A multi-armed bandit approach for batch mode active learning on information networks
… for Active Learning), for classification on heterogeneous information networks. Observing the parallels between active learning and multi-armed bandit (MAB), we base MABAL on an existing combinatorial MAB algorithm to combine simple strategies to generate query batches. MABAL employs a novel …
-
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 …
-
Analyzing intentions from big data traces of human activities
… hand, we examine the privacy risk in anonymized heterogeneous information networks representing large-scale human activities, such as in social networking. Such data are released for external researchers to improve the prediction accuracy for users' online social networking intentions on the …
-
Graph Neural Networks for Health-Aware Food and Multi-Criteria Recommendation Systems
… Recommendation System with Dual Attention in Heterogeneous Graphs (HFRS-DA) and the Multiview Graph Dual Attention and Contrastive Learning for Multi-Criteria Recommender Systems (D-MGAC). The first framework, HFRS-DA, addresses the challenge of effectively integrating heterogeneous …