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 6 of 6 for “"meta-path based"”.
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AsymSim: meta path-based similarity with asymmetric relations
… networks by introducing the concept of meta paths, or paths that connect object types via a sequence of relations. These meta path-based similarity measures can capture the subtlety of peer similarity for paths containing symmetric edges, but real data contains asymmetric relations that …
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Mining heterogeneous information networks
… interconnected data, including (1) ranking-based clustering, (2) meta-path-based similarity search and mining, (3) user-guided relation strength-aware mining, and many other potential developments. This thesis introduces this new research frontier and points out some promising research …
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Publication venue recommendation in heterogeneous information networks
… researchers. Authors often make their decision based on the topics suitability between the paper content and target venues, the likelihood of getting accepted into the venues, the publication history of the authors and other reasonable considerations. A good number of works do content-based …
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Leveraging heterogeneous information networks for personalized entity recommendation
… to the recommendation problem, with network-based techniques garnering increasing interest and study in recent years. However, most of these studies only explore the problem in the context of a single relationship between entities, such as a following relationship in a social network like …
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Relation2vec: Contextualized network embedding for heterogeneous information networks
… and edges. Our method leverages the idea of meta-path, which allows a high-level abstraction of paths and denotes complex relationships among the nodes, to provide context for the nodes in the network, and then utilizes DNN, specifically, bi-directional long short-term memory, to encode the …
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Structure-aware Deep Learning
… graph neural networks operating on complex meta-information enriched graphs. Additionally, we explore methods for the integration of intermediary expressions in strongly typed heterogeneous graphs, improving prediction via meta-path-based processing. We also develop methods for automated …