Topic Modeling for OLAP on Multidimensional Text Databases: Topic Cube and its Applications

Metadata Updated: July 17, 2020

As the amount of textual information grows explosively in various kinds of business systems, it becomes more and more desirable to analyze both structured data records and unstructured text data simultaneously. Although online analytical processing (OLAP) techniques have been proven very useful for analyzing and mining structured data, they face challenges in handling text data. On the other hand, probabilistic topic models are among the most effective approaches to latent topic analysis and mining on text data. In this paper, we study a new data model called topic cube to combine OLAP with probabilistic topic modeling and enable OLAP on the dimension of text data in a multidimensional text database. Topic cube extends the traditional data cube to cope with a topic hierarchy and stores probabilistic content measures of text documents learned through a probabilistic topic model. To materialize topic cubes efficiently, we propose two heuristic aggregations to speed up the iterative Expectation-Maximization (EM) algorithm for estimating topic models by leveraging the models learned on component data cells to choose a good starting point for iteration. Experimental results show that these heuristic aggregations are much faster than the baseline method of computing each topic cube from scratch. We also discuss some potential uses of topic cube and show sample experimental results.

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Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date August 1, 2018
Metadata Updated Date July 17, 2020
Data Update Frequency irregular

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Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date August 1, 2018
Metadata Updated Date July 17, 2020
Publisher Dashlink
Unique Identifier DASHLINK_541
Maintainer
Nikunj Oza
Maintainer Email
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://data.nasa.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 2280925e-5408-4607-9a32-f819b852dfc6
Harvest Source Id 39e4ad2a-47ca-4507-8258-852babd0fd99
Harvest Source Title NASA Data.json
Data First Published 2012-02-26
Homepage URL https://c3.nasa.gov/dashlink/resources/541/
Data Last Modified 2020-01-29
Program Code 026:029
Source Datajson Identifier True
Source Hash 4f5f76dac8ad5a585db3575e28b4c1ce780d9417
Source Schema Version 1.1

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