it is frequent for text corpora and knowledge bases to provide complementary views on a common topic. While, traditionally, the retrieval unit was the document, modern search engines have evolved to also retrieve entities and to provide direct answers to the information needs of the...
Charge transport in molecular solids, such as semiconducting polymers, is strongly affected by packing and structural order over several length scales. Conventional approaches to modeling these phenomena range from analytical models to numerical models u
Graph-based ranking models have been widely applied in information retrieval area. In this paper, we focus on a well known graph-based model - the Ranking on Data Manifold model, or Manifold Ranking (MR). Particularly, it has been successfully applied to content-based image retrieval, because...
Nowadays graph neural networks have achieved excellent performance on many graph-based tasks such as abstract meaning representation (AMR) text generation and graph reasoning. Graph-based models often calculate the information flow by nodes and their associated edges. But node-based or edge-based calcu...
We present a generic framework for spatio-temporal (ST) data modeling, analysis, and forecasting, with a special focus on data that is sparse in both space and time. Our multi-scaled framework is a seamless coupling of two major components: a self-exciting point process that models the macro...
A schematic of our Adaptive Graph U-Net architecture, which is used to estimate 3D coordinates from 2D coordinates. In each of the pooling layers, we roughly cut the number of nodes in half, while in each unpooling layer, we double the number of nodes in the graph. The red arrows in ...
Graph data models are widely used in various area to present,store and process the data with complicated relationships.Considering the deficiency of existing music data models and query languages,this paper firstly presents a graph-based music data model named Gra-MM to model music data with compli...
Proximal support vector machine based hybrid prediction models for trend forecasting in financial markets indicators has been considered based on their application in technical analysis as input feature to predict the future (one-day-ahead) direction of stock ... D Kumar,SS Meghwani,M Thakur - 《...
Quite different from both supervised and semi-supervised feature selection, we propose a "hybrid"framework based on graph models. We first apply supervised methods to select a small set of most critical features from the labeled data. Importantly, these initial features might otherwise be missed ...
General SST models 在前面的介绍中,SST 模型只在最近的回合中使用对话上下文。每次都要考虑到最新的用户话语和系统响应。它可以自然地扩展到编码对话上下文,即下式中的 DST 公式: St=fsst−k(St−k,Ut−k+1sys,Uusrt−k+1,...,Usyst,Uusrt) 实验 数据集 MultiWOZ 2.0 MultiWOZ 2.1 主要结果...