Relational classification in networked data plays an important role in many problems such as text categorization, classification of Web pages, group finding in peer networks, etc. We have previously demonstrated
Collective classification refers to the classification of interlinked and relational objects described as nodes in a graph. The Iterative Classification Algorithm (ICA) is a simple, efficient and widely used method to solve this problem. It is representative of a family of methods for which inference...
Relational Mathematics (2011) K. Bache et al. UCI machine learning repository (2013) R. Belohlavek et al. Impact of boolean factorization as preprocessing methods for classification of boolean data Ann. Math. Artif. Intell. (2014) R. Belohlavek et al. Discovery of optimal factors in binary ...
and evidence of effectiveness. These gaps limit understanding and ability to implement innovations within complex healthcare and social contexts. The purpose of this scoping review and synthesis is to identify and provide a classification of network alteration strategies that have been tested...
3.3 Cross-Attention-Based Entity Alignment We build a cross-attention-based classification model for entity alignment by classifying a pair of entities into a match or a non-match. Figure 2 illustrates the overall architecture of the entity alignment model. The components of the model are ...
classification, in part because the optimal weight assignment is generally unknown.This is to say,attribute weights may need to be tuned and evaluated in an iterative way to produce interpretable data classes that best fit a particular application or best match a specific biophysical pattern.Thus, ...
(as print images) and personal information are enrolled, and features, such as minutiae, core, delta, and classification type, are extracted. Classification type may be, for example, whorl, left loop, right loop, tented arch, and plain arch. Moreover, image quality at individual pixel ...
Increasingly more iterative and recursive query tasks are processed in data management systems, such as graph-structured data analytics, demanding fast response time. We have identified several critical issues that hinder high performance iterative data processing. First, the existing iterative SQL model ...
As a research area, relational clustering has received a great deal of attention recently, because of the large variety of social media applications and other modern relational data sources that have become popular, such as weblogs, protein interaction networks, social networks, and citation graphs....
We consider here the task of multi-label classification for data organized in a multi-relational graph. We propose the IMMCA model—Iterative Multi-label Multi-relational Classification Algorithm—a general algorithm for solving the inference and learning problems for this task. Inference is performed...