Knowledge Discovery from Citation Networks
A Bernoulli Process Topic (BPT) model that enables knowledge discovery from citation networks to improve data mining tasks
Background:
Knowledge discovery from citation networks (i.e., textual data with links such as scientific articles, legal documents, webpages, and emails) provides insight into vast areas since huge repositories are made available...
Published: 4/18/2024
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Inventor(s): Zhongfei Zhang, Zhen Guo
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Computers, Campus > Binghamton University
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Semi-supervised Learning Based on Semiparametric Regularization
Semiparametric regularization based approach allows a family of algorithms to be developed based on various choices of the original RKHS and the loss function
Technology Overview:
Labeled data are often expensive to obtain since they require the efforts of experienced experts. Meanwhile, the unlabeled data are relatively easy to collect. Semiparametric...
Published: 4/18/2024
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Inventor(s): Zhongfei Zhang, Guo Zhen
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Computers, Technology Classifications > Information Technology, Campus > Binghamton University
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Enhanced Max Margin Learning on Multimodal Data Mining in a Multimedia Database
An Enhanced Max Margin Learning (EMML) framework that is much more efficient in learning with a much faster convergence rate, verified in empirical evaluations
Background:
The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured...
Published: 4/18/2024
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Inventor(s): Zhen Guo, Zhongfei Zhang
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Computers, Campus > Binghamton University
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Mixed Membership Relational Clustering
Relational clustering model provides a principal framework to unify various tasks including traditional attributes-based clustering, semi-supervised clustering, co-clustering and graph clustering
Background:
Recently, semi-supervised clustering has attracted significant attention, which is a special type of clustering using both labeled and unlabeled...
Published: 4/18/2024
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Inventor(s): Bo Long, Zhongfei Zhang
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Computers, Campus > Binghamton University
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Spectral Relational Clustering, Multi-type Relational Data, Collective Factorization on Related Matrices
A novel general algorithm to cluster multi-type interrelated data objects simultaneously by iteratively embedding each type of data objects into low dimensional spaces
Background:
Most clustering approaches in the literature focus on "flat" data in which each data object is represented as a fixed-length feature vector. However, many real-world...
Published: 4/18/2024
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Inventor(s): Zhongfei Zhang
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Computers, Campus > Binghamton University
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Soft Correspondence Ensemble Clustering (SCEC)
New framework to address the correspondence problem of clustering ensembles
Technology Overview:
The developed framework is based on soft correspondence to directly address the correspondence problem of clustering ensembles. By the concept of soft correspondence, a cluster from one clustering corresponds to each cluster from another clustering...
Published: 4/18/2024
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Inventor(s): Bo Long, Zhongfei Zhang
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Computers, Campus > Binghamton University
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Method and Apparatus for Image Annotation and Multimodal Image Retrieval
Novel method improves content-Based Image Retrieval (CBIR) using probabilistic semantic model
Background:
Efficient access to multimedia database content requires the ability to search and organize multimedia information. In one form of traditional image retrieval, users have to provide examples of images that they are looking for. Similar images...
Published: 4/18/2024
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Inventor(s): Ruofei Zhang, Zhongfei Zhang
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Computers, Campus > Binghamton University
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Semisupervised Autoencoder for Sentiment Analysis
Semisupervised Autoencoder for Sentiment Analysis that reduces bias and requires minimal training
Background:
They act as the feature learning methods by reconstructing inputs with respect to a given loss function. In a neural network implementation of autoencoders, the hidden layer is taken as the learned feature. While it is often trivial to...
Published: 4/18/2024
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Inventor(s): Shuangfei Zhai, Zhongfei Zhang
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Artificial Intelligence, Campus > Binghamton University
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Pattern Change Discovery Between High Dimensional Datasets
Pattern Change Discovery Between High Dimensional Datasets
Background:
This technology provides a powerful solution to the general problem of pattern change discovery between high-dimensional data sets. Current technologies either mainly focus on magnitude change detection of low-dimensional data sets or are under supervised frameworks.
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Published: 4/18/2024
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Inventor(s): Yi Xu, Zhongfei Zhang
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Computers, Technology Classifications > Information Technology, Campus > Binghamton University
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Fast, Automatic Detection of Independent Motion from Compressed Surveillance Video
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Technology Overview:
An algorithm that automates qualitative surveillance video detection of independently moving objects in two modes: (1) real-time (in combination with sensors) and (2) very fast scanning...
Published: 4/18/2024
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Inventor(s): Zhongfei Zhang
Keywords(s): #SUNYresearch, Technologies
Category(s): Technology Classifications > Computers, Technology Classifications > Artificial Intelligence, Campus > Binghamton University
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