Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Uncovering hidden structures in massive data collections

03.12.2013
Advances in computer storage have created collections of data so huge that researchers often have trouble uncovering critical patterns in connections among individual items, making it difficult for them to realize fully the power of computing as a research tool.

Now, computer scientists at Princeton University have developed a method that offers a solution to this data overload. Using a mathematical method that calculates the likelihood of a pattern repeating throughout a subset of data, the researchers have been able to cut dramatically the time needed to find patterns in large collections of information such as social networks.

The tool allows researchers to identify quickly the connections between seemingly disparate groups such as theoretical physicists who study intermolecular forces and astrophysicists researching black holes.

"The data we are interested in are graphs of networks like friends on Facebook or lists of academic citations," said David Blei, an associate professor of computer science and co-author on the research, which was published Sept. 3 in the Proceedings of the National Academy of Science. "These are vast data sets and we want to apply sophisticated statistical models to them in order to understand various patterns."

Finding patterns in the connections among points of data can be critical for many applications. For example, checking citations to scientific papers can provide insights to the development of new fields of study or show overlap between different academic disciplines. Links between patents can map out groups that indicate new technological developments. And analysis of social networks can provide information about communities and allow predictions of future interests.

"The goal is to detect overlapping communities," Blei said. "The problem is that these data collections have gotten so big that the algorithms cannot solve the problem in a reasonable amount of time."

Currently, Blei said, many algorithms uncover hidden patterns by analyzing potential interactions between every pair of nodes (either connected or unconnected) in the entire data set; that becomes impractical for large amounts of data such as the collected citations of the U.S. Patent Office. Many are also limited to sorting data into single groups.

"In most cases, nodes belong to multiple groups," said Prem Gopalan, a doctoral student in Blei's research group and lead author of the paper. "We want to be able to reflect that."

The research was supported by the Office of Naval Research, the National Science Foundation and the Alfred. P. Sloan Foundation.

In very basic terms, the researchers approached the problem by dividing the analysis into two broad tasks. In one, they created an algorithm that quickly analyzes a subset of a large database. The algorithm calculates the likelihood that nodes belong to various groups in the database. In the second broad task, the researchers created an adjustable matrix that accepts the analysis of the subset and assigns "weights" to each data point reflecting the likelihood that it belongs to different groups.

Blei and Gopalan designed the sampling algorithm to refine its accuracy as it samples more subsets. At the same time, the continual input from the sampling to the weighted matrix refines the accuracy of the overall analysis.

The math behind the work is complex. Essentially, the researchers used a technique called stochastic optimization, which is a method to determine a central pattern from a group of data that seem chaotic or, as mathematicians call it, "noisy." Blei likens it to finding your way from New York to Los Angeles by stopping random people and asking for directions — if you ask enough people, you will eventually find your way. The key is to know what question to ask and how to interpret the answers.

"With noisy measurements, you can still make good progress by doing it many times as long as the average gives you the correct result," he said.

In their PNAS article, the researchers describe how they used their method to discover patterns in the connections between patents. Using public data from the U.S. National Bureau of Economic Research, Gopalan and Blei analyzed connections to the 1976 patent "Process for producing porous products."

The patent, filed by Robert W. Gore (who several years earlier discovered the process that led to the creation of the waterproof fabric Gore-Tex), described a method for producing porous material from tetrafluoroethylene polymers. The researchers analyzed a data collection of 3.7 million nodes and found that connections between Gore's 1976 filing and other patents formed 39 distinct communities in the database.

The patent "has influenced the design of many everyday materials such as waterproof laminate, adhesives, printed circuit boards, insulated conductors, dental floss and strings of musical instruments," the researchers wrote.

In the past, researchers struggled to find nuggets of critical information in data. The new challenge is not finding the needle in the data haystack, but finding the hidden patterns in the hay.

"Take the data from the world, from what you observe, and then untangle it," Blei said. "What generated it? What are the hidden structures?"

John Sullivan | EurekAlert!
Further information:
http://www.princeton.edu

More articles from Information Technology:

nachricht Fingerprints of quantum entanglement
16.02.2018 | University of Vienna

nachricht Simple in the Cloud: The digitalization of brownfield systems made easy
07.02.2018 | Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, DFKI

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Demonstration of a single molecule piezoelectric effect

Breakthrough provides a new concept of the design of molecular motors, sensors and electricity generators at nanoscale

Researchers from the Institute of Organic Chemistry and Biochemistry of the CAS (IOCB Prague), Institute of Physics of the CAS (IP CAS) and Palacký University...

Im Focus: Hybrid optics bring color imaging using ultrathin metalenses into focus

For photographers and scientists, lenses are lifesavers. They reflect and refract light, making possible the imaging systems that drive discovery through the microscope and preserve history through cameras.

But today's glass-based lenses are bulky and resist miniaturization. Next-generation technologies, such as ultrathin cameras or tiny microscopes, require...

Im Focus: Stem cell divisions in the adult brain seen for the first time

Scientists from the University of Zurich have succeeded for the first time in tracking individual stem cells and their neuronal progeny over months within the intact adult brain. This study sheds light on how new neurons are produced throughout life.

The generation of new nerve cells was once thought to taper off at the end of embryonic development. However, recent research has shown that the adult brain...

Im Focus: Interference as a new method for cooling quantum devices

Theoretical physicists propose to use negative interference to control heat flow in quantum devices. Study published in Physical Review Letters

Quantum computer parts are sensitive and need to be cooled to very low temperatures. Their tiny size makes them particularly susceptible to a temperature...

Im Focus: Autonomous 3D scanner supports individual manufacturing processes

Let’s say the armrest is broken in your vintage car. As things stand, you would need a lot of luck and persistence to find the right spare part. But in the world of Industrie 4.0 and production with batch sizes of one, you can simply scan the armrest and print it out. This is made possible by the first ever 3D scanner capable of working autonomously and in real time. The autonomous scanning system will be on display at the Hannover Messe Preview on February 6 and at the Hannover Messe proper from April 23 to 27, 2018 (Hall 6, Booth A30).

Part of the charm of vintage cars is that they stopped making them long ago, so it is special when you do see one out on the roads. If something breaks or...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

2nd International Conference on High Temperature Shape Memory Alloys (HTSMAs)

15.02.2018 | Event News

Aachen DC Grid Summit 2018

13.02.2018 | Event News

How Global Climate Policy Can Learn from the Energy Transition

12.02.2018 | Event News

 
Latest News

Fingerprints of quantum entanglement

16.02.2018 | Information Technology

'Living bandages': NUST MISIS scientists develop biocompatible anti-burn nanofibers

16.02.2018 | Health and Medicine

Hubble sees Neptune's mysterious shrinking storm

16.02.2018 | Physics and Astronomy

VideoLinks
Science & Research
Overview of more VideoLinks >>>