DeepAI AI Chat
Log In Sign Up

Scalable Models for Computing Hierarchies in Information Networks

by   Baoxu Shi, et al.
University of Notre Dame

Information hierarchies are organizational structures that often used to organize and present large and complex information as well as provide a mechanism for effective human navigation. Fortunately, many statistical and computational models exist that automatically generate hierarchies; however, the existing approaches do not consider linkages in information networks that are increasingly common in real-world scenarios. Current approaches also tend to present topics as an abstract probably distribution over words, etc rather than as tangible nodes from the original network. Furthermore, the statistical techniques present in many previous works are not yet capable of processing data at Web-scale. In this paper we present the Hierarchical Document Topic Model (HDTM), which uses a distributed vertex-programming process to calculate a nonparametric Bayesian generative model. Experiments on three medium size data sets and the entire Wikipedia dataset show that HDTM can infer accurate hierarchies even over large information networks.


page 1

page 2

page 3

page 4


TWAG: A Topic-Guided Wikipedia Abstract Generator

Wikipedia abstract generation aims to distill a Wikipedia abstract from ...

Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling

Analyzing the underlying structure of multiple time-sequences provides i...

Random-walk Based Generative Model for Classifying Document Networks

Document networks are found in various collections of real-world data, s...

The nested Chinese restaurant process and Bayesian nonparametric inference of topic hierarchies

We present the nested Chinese restaurant process (nCRP), a stochastic pr...

Nonparametric Relational Topic Models through Dependent Gamma Processes

Traditional Relational Topic Models provide a way to discover the hidden...

Double Articulation Analyzer with Prosody for Unsupervised Word and Phoneme Discovery

Infants acquire words and phonemes from unsegmented speech signals using...

Scalable Text and Link Analysis with Mixed-Topic Link Models

Many data sets contain rich information about objects, as well as pairwi...