Multi-view data containing complementary and consensus information can facilitate representation learning by exploiting the intact integration of multi-view features. Because most objects in real world often have underlying connections, organizing as heterogeneous graphs is beneficial to extracting latent among different objects. Due powerful capability gather neighborhood nodes, this paper, we...

Relation Extraction (RE) is to predict the relation type of two entities that are mentioned in a piece text, e.g., sentence or dialogue. When given text long, it challenging identify indicative words for prediction. Recent advances on RE task from BERT-based sequence modeling and graph-based relationships among tokens sequence. In this paper, we propose construct latent multi-view graph capture...

Bundle recommendation aims to recommend the user a bundle of items as whole. Previous models capture user’s preferences on both and association items. Nevertheless, they usually neglect diversity intents adopting fail disentangle in representations. In real scenario recommendation, intent may be naturally distributed different bundles that (Global view). And contain multiple (Local Each view ha...

In this paper, we propose to represent and classify complicated objects. In order to represent the objects, we propose a multi-graph-view model which uses graphs constructed from multiple graph-views to represent an object. In addition, a bag based multi-graph model is further used to relax labeling by only requiring one label for a bag of graphs, which represent one object. In order to learn c...

this commentary considers the potential role of patient and public involvement in implementation. developing an analytical thread from the resource-based view of the firm, we argue that this involvement may create unique resources that have the capacity to enhance the impact of implementation activity for healthcare organisations.

evaluating the investment that healthcare organisations make in quality improvement requires knowledge of impact at multiple levels, including patient care, workforce and other organisational resources. the degree to which these resources help organisations to survive and thrive in the challenging contexts in which healthcare is designed and delivered is unknown. investigating this question fro...

Most of the existing incomplete multi-view clustering (IMVC) methods focus on attaining a consensus representation from different views but ignore important information hidden in missing and latent intrinsic structures each view. To tackle these issues, this paper, unified novel framework, named tensorized with graph completion (TIMVC_IGC) is proposed. Firstly, owing to effectiveness low-rank r...

Existing graph partitioning approaches are mainly based on optimizing edge cuts and do not take the distribution of edge weights (link distribution) into consideration. In this paper, we propose a general model to partition graphs based on link distributions. This model formulates graph partitioning under a certain distribution assumption as approximating the graph affinity matrix under the cor...

OF THE DISSERTATION Theory and Practice of Non-Binary Graph-Based Codes: A Combinatorial View