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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=data+analysis">
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  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=data+analysis]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for data analysis]]></description>
  <items>
    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/479/Is-your-personal-data-at-risk-App-analytics-to-the-rescue"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/238/Probabilistic-Approximate-Algorithms-for-Distributed-Data-Mining-in-Peer-to-Peer-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/223/A-Game-Theoretic-Framework-for-Distributed-Multi-Party-Privacy-Preserving-Data-Mining"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/31/Welcome-to-the-Splogosphere"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1156/Privacy-Preserving-Data-Sharing-in-Agriculture-Enforcing-Policy-Rules-for-Secure-and-Confidential-Data-Synthesis"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1071/Knowledge-Graph-driven-Tabular-Data-Discovery-from-Scientific-Documents"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1066/CDFMR-A-Distributed-Statistical-Analysis-of-Stock-Market-Data-using-MapReduce-with-Cumulative-Distribution-Function"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1014/PriveTAB-Secure-and-Privacy-Preserving-sharing-of-Tabular-Data"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/992/A-Policy-Driven-Approach-to-Secure-Extraction-of-COVID-19-Data-From-Research-Papers"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/843/An-Integrated-Knowledge-Graph-to-Automate-GDPR-and-PCI-DSS-Compliance"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/741/A-database-based-distributed-computation-architecture-with-Accumulo-and-D4M-An-application-of-eigensolver-for-large-sparse-matrix"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/513/Atmospheric-Composition-Processing-System-ACPS-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/292/Predictive-Mining-of-Time-Series-Data-in-Astronomy"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/440/Structured-speech-input-for-clinical-data-collection"/>
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/479/Is-your-personal-data-at-risk-App-analytics-to-the-rescue">
  <title><![CDATA[Is your personal data at risk? App analytics to the rescue]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/479/Is-your-personal-data-at-risk-App-analytics-to-the-rescue</link>
  <description><![CDATA[According to Virustotal, a prominent virus and malware tool, the Google Play Store has a few thousand apps from major malware families. Given such a revelation, access control systems for mobile data management, have reached a state of critical importance. We propose the development of a system which would help us detect the pathways using which user's data is being stolen from their mobile devices. We use a multi layered approach which includes app meta data analysis, understanding code patt...]]></description>
  <dc:date>2015-09-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/238/Probabilistic-Approximate-Algorithms-for-Distributed-Data-Mining-in-Peer-to-Peer-Networks">
  <title><![CDATA[Probabilistic Approximate Algorithms for Distributed Data Mining in Peer-to-Peer Networks]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/238/Probabilistic-Approximate-Algorithms-for-Distributed-Data-Mining-in-Peer-to-Peer-Networks</link>
  <description><![CDATA[Peer-to-peer(P2P) computing is emerging as a new distributed computing 
paradigm for novel applications that involves exchange of information 
among  peers with little centralized coordination. Analyzing data 
distributed in P2P networks requires peer-to-peer data mining algorithms 
that can mine the data without data centralization. However, 
replicating  result of centralized data mining in an exact fashion is 
often communication-wise expensive. Approximate algorithms can be a 
real...]]></description>
  <dc:date>2008-04-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/223/A-Game-Theoretic-Framework-for-Distributed-Multi-Party-Privacy-Preserving-Data-Mining">
  <title><![CDATA[A Game Theoretic Framework for Distributed Multi-Party Privacy Preserving Data Mining]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/223/A-Game-Theoretic-Framework-for-Distributed-Multi-Party-Privacy-Preserving-Data-Mining</link>
  <description><![CDATA[Privacy protection is increasingly becoming an important issue in many
data mining applications, particularly in the area of security
and surveillance. However, privacy preserving data analysis is a
non-trivial problem because of many reasons. First of all, privacy
is a social concept. In most multi-party data mining scenarios
participants have varying interests, objectives and expectations
about data privacy. Enforcing a single model of privacy with strong
assumptions regarding the be...]]></description>
  <dc:date>2007-11-19</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/31/Welcome-to-the-Splogosphere">
  <title><![CDATA[Welcome to the Splogosphere]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/31/Welcome-to-the-Splogosphere</link>
  <description><![CDATA[Welcome to the Splogosphere!

UMBC study estimates that 75% of posts to English language weblogs are spam


Baltimore, December 16, 2005

 A weblog monitoring system developed by UMBC Ph.D. student Pranam
Kolari shows that a new form of spam -- spam blogs or splogs --
has quickly become a serious problem. 

 Splogs are "fake"
weblog sites that have been set up to carry paid advertisements,
promote affiliated web sites by increasing their PageRank, and to get
new sites noti...]]></description>
  <dc:date>2005-12-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1156/Privacy-Preserving-Data-Sharing-in-Agriculture-Enforcing-Policy-Rules-for-Secure-and-Confidential-Data-Synthesis">
  <title><![CDATA[Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1156/Privacy-Preserving-Data-Sharing-in-Agriculture-Enforcing-Policy-Rules-for-Secure-and-Confidential-Data-Synthesis</link>
  <description><![CDATA[Big Data empowers the farming community with the information needed to optimize resource usage, increase productivity, and enhance the sustainability of agricultural practices. The use of Big Data in farming requires the collection and analysis of data from various sources such as sensors, satellites, and farmer surveys. While Big Data can provide the farming community with valuable insights and improve efficiency, there is significant concern regarding the security of this data as well as th...]]></description>
  <dc:date>2023-12-18</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1071/Knowledge-Graph-driven-Tabular-Data-Discovery-from-Scientific-Documents">
  <title><![CDATA[Knowledge Graph-driven Tabular Data Discovery from Scientific Documents]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1071/Knowledge-Graph-driven-Tabular-Data-Discovery-from-Scientific-Documents</link>
  <description><![CDATA[Synthesizing information from collections of tables embedded within scientific and technical documents is increasingly critical to emerging knowledge-driven applications. Given their structural heterogeneity, highly domain-specific content, and diffuse context, inferring a precise semantic understanding of such tables is traditionally better accomplished through linking tabular content to concepts and entities in reference knowledge graphs. However, existing tabular data discovery systems are...]]></description>
  <dc:date>2023-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1066/CDFMR-A-Distributed-Statistical-Analysis-of-Stock-Market-Data-using-MapReduce-with-Cumulative-Distribution-Function">
  <title><![CDATA[CDFMR: A Distributed Statistical Analysis of Stock Market Data using MapReduce with Cumulative Distribution Function]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1066/CDFMR-A-Distributed-Statistical-Analysis-of-Stock-Market-Data-using-MapReduce-with-Cumulative-Distribution-Function</link>
  <description><![CDATA[The stock market generates massive data daily on
top of a deluge of historical data. Investors and traders look to
stock market data analysis for assurance in their investments, a
prime indicator of our global economy. This has led to immense
popularity in the topic, and consequently, much research has been
done on stock market predictions and future trends. However,
due to the relatively slow electronic trading systems and order
processing times, the velocity of data, the variety of d...]]></description>
  <dc:date>2023-07-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1014/PriveTAB-Secure-and-Privacy-Preserving-sharing-of-Tabular-Data">
  <title><![CDATA[PriveTAB : Secure and Privacy-Preserving sharing of Tabular Data]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1014/PriveTAB-Secure-and-Privacy-Preserving-sharing-of-Tabular-Data</link>
  <description><![CDATA[Machine Learning has increased our ability to model large quantities of data efficiently in a short time. Machine learning approaches in many application domains require collecting large volumes of data from distributed sources and combining them. However, sharing of data from multiple sources leads to concerns about privacy. Privacy regulations like European Union's General Data Protection Regulation (GDPR) have specific requirements on when and how such data can be shared. Even when there a...]]></description>
  <dc:date>2022-04-24</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/992/A-Policy-Driven-Approach-to-Secure-Extraction-of-COVID-19-Data-From-Research-Papers">
  <title><![CDATA[A Policy-Driven Approach to Secure Extraction of COVID-19 Data From Research Papers]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/992/A-Policy-Driven-Approach-to-Secure-Extraction-of-COVID-19-Data-From-Research-Papers</link>
  <description><![CDATA[The entire scientific and academic community has been mobilized to gain a better understanding of the COVID-19 disease and its impact on humanity. Most research related to COVID-19 needs to analyze large amounts of data in very little time. This urgency has made Big Data Analysis, and related questions around the privacy and security of the data, an extremely important part of research in the COVID-19 era. The White House OSTP has, for example, released a large dataset of papers related to CO...]]></description>
  <dc:date>2021-08-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/843/An-Integrated-Knowledge-Graph-to-Automate-GDPR-and-PCI-DSS-Compliance">
  <title><![CDATA[An Integrated Knowledge Graph to Automate GDPR and PCI DSS Compliance]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/843/An-Integrated-Knowledge-Graph-to-Automate-GDPR-and-PCI-DSS-Compliance</link>
  <description><![CDATA[Big data analytics related to consumer behavior,
market analysis, opinions, and recommendation often deal with
end user's derived and inferred data, along with the observed
data. To ensure consumer data protection, rules defined by the
European Union’s General Data Protection Regulation (EU
GDPR) must be adhered to by every organization
using Personally Identifiable Information (PII) data for Big
Data analysis. Similarly, Payment Card Industry Data Security
Standard (PCI DSS) has po...]]></description>
  <dc:date>2018-12-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/741/A-database-based-distributed-computation-architecture-with-Accumulo-and-D4M-An-application-of-eigensolver-for-large-sparse-matrix">
  <title><![CDATA[A database-based distributed computation architecture with Accumulo and D4M: An application of eigensolver for large sparse matrix]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/741/A-database-based-distributed-computation-architecture-with-Accumulo-and-D4M-An-application-of-eigensolver-for-large-sparse-matrix</link>
  <description><![CDATA[NoSQL distributed databases have been devised to tackle the challenges resulting from volume, velocity and variety of big data. Graph representation of datasets requires efficient distributed linear algebra operations for large sparse matrix constructed from big data. Storing the transformed matrix into the database not only speeds up the big data analysis process but also facilitates the computation because of indexing. The Hadoop based approach does not natively support iterative algorithms...]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/513/Atmospheric-Composition-Processing-System-ACPS-">
  <title><![CDATA[Atmospheric Composition Processing System (ACPS)]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/513/Atmospheric-Composition-Processing-System-ACPS-</link>
  <description><![CDATA[The Atmospheric Composition Processing System (ACPS) is a Community-Oriented Measurement-based Processing System that builds on the heritage mission-based processing used for MODIS, Total Ozone Mapping Spectrometer, and Ozone Monitoring Instrument missions. The ACPS features key changes in scalability, interfaces, and provenance capture that will increase access to NASA's Earth Science data and processing capabilities as well as improve the overall system's usefulness as compared with its pre...]]></description>
  <dc:date>2009-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/292/Predictive-Mining-of-Time-Series-Data-in-Astronomy">
  <title><![CDATA[Predictive Mining of Time Series Data in Astronomy]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/292/Predictive-Mining-of-Time-Series-Data-in-Astronomy</link>
  <description><![CDATA[We discuss the development of a Java toolbox for astronomical time
series data. Rather than using methods conventional in astronomy (e.g.,
power spectrum and cross-correlation analysis) we employ rule discovery
techniques commonly used in analyzing stock-market data. By clustering
patterns found within the data, rule discovery allows one to build pre-
dictive models, allowing one to forecast when a given event might occur
or whether the occurrence of one event will trigger a second. We ...]]></description>
  <dc:date>2003-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/440/Structured-speech-input-for-clinical-data-collection">
  <title><![CDATA[Structured speech input for clinical data collection]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/440/Structured-speech-input-for-clinical-data-collection</link>
  <description><![CDATA[This paper presents an environment for collecting clinical data using structured speech input. The system uses nomenclature terms and data consistency rules to limit the speech input to a discrete set of phrases which can be configured to support a wide range of studies. This information is stored in an event-oriented data model as strongly typed observations for subsequent distribution and data analysis. The use of speech input should result in increased efficiency during hands-busy data col...]]></description>
  <dc:date>2002-06-30</dc:date>
 </item>
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