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	This ontology document is licensed under the Creative Commons
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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=abe">
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  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
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  <description><![CDATA[UMBC ebiquity RSS Tag Search for abe]]></description>
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      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/474/TABEL-A-Domain-Independent-and-Extensible-Framework-for-Inferring-the-Semantics-of-Tables"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/472/Many-Facets-of-Energy-Disaggregation"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/446/Predicting-Chronic-Diseases-with-Machine-Learning"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/431/Analytics-for-Detecting-Web-and-Social-Media-Abuse"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/409/Genetic-information-for-chronic-disease-prediction"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/398/Group-recognition-in-Social-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/357/Detecting-Domain-Shift"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/355/Clustering-short-status-messages-a-topic-model-based-approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/47/Ebiquity-team-wins-the-Best-Paper-Award-at-the-IEEE-BigDataSecurity-2022-Conference"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/66/Database-Semanticizer"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/111/Medical-Device-Regulatory-Compliance"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/78/Policy-based-Automated-WAN-Configuration-and-Management"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/82/RDF123"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1187/Evaluating-Causal-AI-Techniques-for-Health-Misinformation-Detection"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1186/MedReg-KG-KnowledgeGraph-for-Streamlining-Medical-Device-Regulatory-Compliance"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1173/GenAIPABench-A-Benchmark-for-Generative-AI-based-Privacy-Assistants"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1174/Comparison-of-attribute-based-encryption-schemes-in-securing-healthcare-systems"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1058/Semantically-Rich-Differential-Access-to-Secure-Cloud-EHR"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1036/Process-Knowledge-Infused-AI-Toward-User-Level-Explainability-Interpretability-and-Safety"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1024/Semantically-Rich-Access-Control-in-Cloud-EHR-Systems-Based-on-MA-ABE"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1022/CyberEnt-A-Cybersecurity-Domain-Specific-Dataset-for-Named-Entity-Recognition"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/852/Delegated-Authorization-Framework-for-EHR-Services-using-Attribute-Based-Encryption"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/988/Secure-Cloud-EHR-with-Semantic-Access-Control-Searchable-Encryption-and-Attribute-Revocation"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/74/Database-Semanticizer-Presentation"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/306/Detecting-Domain-Shift"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/238/RDF-Web-service-v1-0-java-servlet-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/237/RDF123-java-application-v1-0"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/236/RDF123-linux-application-v1-0-With-Java-VM-self-contained-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/233/RDF123-presentation"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/228/RDF123-windows-application-v1-0-With-Java-VM-self-contained-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/212/Splog-Blog-Dataset"/>
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/474/TABEL-A-Domain-Independent-and-Extensible-Framework-for-Inferring-the-Semantics-of-Tables">
  <title><![CDATA[TABEL -- A Domain Independent and Extensible Framework for Inferring the Semantics of Tables]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/474/TABEL-A-Domain-Independent-and-Extensible-Framework-for-Inferring-the-Semantics-of-Tables</link>
  <description><![CDATA[ 

 Dissertation Defense

Tables are an integral part of documents, reports and Web pages in many scientific and technical domains, compactly encoding important information that can be difficult to express in text. Table-like structures outside documents, such as spreadsheets, CSV files, log files and databases, are widely used to represent and share information. However, tables remain beyond the scope of regular text processing systems which often treat them like free text.

This ...]]></description>
  <dc:date>2015-01-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/472/Many-Facets-of-Energy-Disaggregation">
  <title><![CDATA[Many Facets of Energy Disaggregation]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/472/Many-Facets-of-Energy-Disaggregation</link>
  <description><![CDATA[In this week's Ebiquity meeting, PhD student Nilavra Phatak from the UMBC Information Systems Department will discuss his work on "Many Facets of Energy Disaggregation".

The objective of energy disaggregation is to get the appliance-wise energy consumption from the whole home energy signal. The disaggregated energy consumption provides a better insight into the electrical usage and helps the consumers to modify usage in order to save money and energy. The application of energy disaggregati...]]></description>
  <dc:date>2014-10-29</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/446/Predicting-Chronic-Diseases-with-Machine-Learning">
  <title><![CDATA[Predicting Chronic Diseases with Machine Learning]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/446/Predicting-Chronic-Diseases-with-Machine-Learning</link>
  <description><![CDATA[In recent years we saw an explosion of cheap genetic tests, which lead to the emergence of personalized medicine.  Personalized medicine is defined as practice of medicine that is tailored to specifics of individual patient.  My work addresses the problem of attempting to predict individual’s predisposition towards certain chronic diseases based on the individual’s genetic makeup.  The benefits of such work allow for more selective administration of invasive tests such as biopsies, which ...]]></description>
  <dc:date>2013-03-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/431/Analytics-for-Detecting-Web-and-Social-Media-Abuse">
  <title><![CDATA[Analytics for Detecting Web and Social Media Abuse]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/431/Analytics-for-Detecting-Web-and-Social-Media-Abuse</link>
  <description><![CDATA[The Web and online social media provide invaluable communication services to a global Internet user base. The tremendous success of these services, however, has also created valuable opportunities for criminals and other miscreants to abuse them for their own gain. As a result, it is both an important yet challenging problem to detect, monitor, and curtail this abuse. However, the large scale and diversity of these services, combined with the tactics used by attackers, make it difficult to di...]]></description>
  <dc:date>2012-03-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/422/Masters-Thesis-Research-Update-Amey-and-Nikhil">
  <title><![CDATA[Masters Thesis Research Update - Amey and Nikhil]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/422/Masters-Thesis-Research-Update-Amey-and-Nikhil</link>
  <description><![CDATA[In this week's lab meeting, Amey Sane and Nikhil Puranik will give an update on how their Masters thesis research is progressing. 


Amey will talk on "Exploring Hidden Markov Model for semantic activity prediction".

Smart devices like mobile phones can effectively be exploited for use, not only as a mode of contact through voice dialing but much more than that, by making use of its features like Bluetooth, Wi-Fi capability and also through its in-built sensor capability. All these can ...]]></description>
  <dc:date>2011-12-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/410/Masters-Thesis-Research-Proposal-Amey-Sane-and-Nikhil-Puranik">
  <title><![CDATA[Masters Thesis Research Proposal: Amey Sane and Nikhil Puranik]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/410/Masters-Thesis-Research-Proposal-Amey-Sane-and-Nikhil-Puranik</link>
  <description><![CDATA[In this week's lab meeting we will have Amey Sane and Nikhil Puranik talk about the research they will be pursuing for their Masters Thesis. 

Amey Sane will talk about "Context-aware Framework for modeling and prediction of User activities". His research work is part of ongoing Platys project. This project spans over the areas like mobile computing, Context-aware computing, security and privacy. My thesis work will be focused in the area of mobile-computing and Context-aware computing. In ...]]></description>
  <dc:date>2011-09-27</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/409/Genetic-information-for-chronic-disease-prediction">
  <title><![CDATA[Genetic information for chronic disease prediction]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/409/Genetic-information-for-chronic-disease-prediction</link>
  <description><![CDATA[Type 2 diabetes and coronary artery disease are commonly occurring polygenic-multifactorial diseases, which are responsible for significant morbidity and mortality. The identification of people at risk for these conditions has historically been based on clinical factors alone. However, this resulted in prediction algorithms that are linked to symptomatic states, which have limited accuracy in asymptomatic individuals. Advances in genetics have raised the hope that genetic testing may aid in d...]]></description>
  <dc:date>2011-09-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/398/Group-recognition-in-Social-Networks">
  <title><![CDATA[Group recognition in Social Networks]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/398/Group-recognition-in-Social-Networks</link>
  <description><![CDATA[Nagapradeep Chinnam will defend his MS thesis titled "Group recognition in Social Networks".

Recent years have seen an exponential growth in the use of social
networking systems, enabling their users to easily share
information with their connections.  A typical Facebook user, as
an example, might have 300-400 connections which include
relatives, friends, business associates and casual acquaintances.
Sharing information with a such a large and diverse set of people
without violating ...]]></description>
  <dc:date>2011-05-17</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/357/Detecting-Domain-Shift">
  <title><![CDATA[Detecting Domain Shift]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/357/Detecting-Domain-Shift</link>
  <description><![CDATA[Machine learning systems are typically trained in the lab and then deployed in the wild.  But what happens when the data to which they are exposed in the wild change in a way that hurts accuracy?  For example, a system may be trained to classify movie reviews as either positive or negative (i.e., sentiment classification), but over time book reviews get mixed into the data stream.  The problem of responding to such changes when they are known to have occurred has been studied extensively.  In...]]></description>
  <dc:date>2010-09-03</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/355/Clustering-short-status-messages-a-topic-model-based-approach">
  <title><![CDATA[Clustering short status messages: a topic model based approach]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/355/Clustering-short-status-messages-a-topic-model-based-approach</link>
  <description><![CDATA[Recently, there has been an exponential rise in the use of online social media systems like Twitter and Facebook. Even more usage has been observed during events related to natural disasters, political turmoil or other such crises. Tweets or status messages are short and may not carry enough contextual clues. Hence, applying traditional natural language processing algorithms on such data is challenging. Topic model is a popular method for modeling term frequency occurrences for documents in a...]]></description>
  <dc:date>2010-07-26</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/47/Ebiquity-team-wins-the-Best-Paper-Award-at-the-IEEE-BigDataSecurity-2022-Conference">
  <title><![CDATA[Ebiquity team wins the Best Paper Award at the IEEE BigDataSecurity 2022 Conference]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/47/Ebiquity-team-wins-the-Best-Paper-Award-at-the-IEEE-BigDataSecurity-2022-Conference</link>
  <description><![CDATA[The paper "Semantically Rich Access Control in Cloud EHR Systems Based on MA-ABE" authored by Sharad Dixit, Karuna Pande Joshi, SeungGeol Choi, and Lavanya Elluri won the Best Paper Award at the IEEE Big Data Security on the Cloud 2022 held in May 6-8 at Jinan, China.]]></description>
  <dc:date>2022-05-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/66/Database-Semanticizer">
  <title><![CDATA[Database Semanticizer]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/66/Database-Semanticizer</link>
  <description><![CDATA[The vision of the Semantic web is to give the web a well defined meaning by representing the same in OWL and linking it to ontologies accepted commonly by standardization efforts. Most of the formatted data is today stored in the form of relational databases. We need to RDFize it in order to use this data on the Semantic Web. The data model behind RDF is a directed labeled graph, which consists of nodes and labeled directed arcs linking pairs of nodes. To export data from an RDBMS into R...]]></description>
  <dc:date>2004-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/111/Medical-Device-Regulatory-Compliance">
  <title><![CDATA[Medical Device Regulatory Compliance]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/111/Medical-Device-Regulatory-Compliance</link>
  <description><![CDATA[Healthcare providers are deploying a large number of AI-driven Medical devices to help monitor and medicate patients. For patients with chronic ailments, like diabetes or gastric diseases, usage of these devices becomes part of their daily lifestyle. These medical devices often capture personally identifiable information (PII) and hence are strictly regulated by the Food and Drug Administration (FDA) to ensure the safety and efficacy of the medical device. Medical device regulations are curre...]]></description>
  <dc:date>2023-08-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/78/Policy-based-Automated-WAN-Configuration-and-Management">
  <title><![CDATA[Policy-based Automated WAN Configuration and Management]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/78/Policy-based-Automated-WAN-Configuration-and-Management</link>
  <description><![CDATA[There are many significant challenges related to configuration and management of wide-area networks due to their rapidly growing complexity, failures, and attacks.  The DARPA Knowledge Plane Study identified that main challenges to be intelligent network management, fault detection, attack response, and fast network configuration.  With uncertainty and threads of battle areas, these challenges further grow exponentially.

In order to overcome the challenges, the project aims at developing a...]]></description>
  <dc:date>2006-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/82/RDF123">
  <title><![CDATA[RDF123]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/82/RDF123</link>
  <description><![CDATA[RDF123 is an application and web service for converting data in simple spreadsheets to an RDF graph.  Users control how the spreadsheet's data is converted to RDF by constructing a graphical RDF123 template that specifies how each row in the spreadsheet is converted as well as metadata for the spreadsheet and its RDF translation.  The template can map spreadsheet cells to a new RDF node or to a literal value. Labels on the nodes in the map can be used to create blank nodes or labeled nodes, a...]]></description>
  <dc:date>2007-04-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1187/Evaluating-Causal-AI-Techniques-for-Health-Misinformation-Detection">
  <title><![CDATA[Evaluating Causal AI Techniques for Health  Misinformation Detection]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1187/Evaluating-Causal-AI-Techniques-for-Health-Misinformation-Detection</link>
  <description><![CDATA[Abstract—The proliferation of health misinformation on social media, particularly regarding chronic conditions such as diabetes, hypertension, and obesity, poses significant public health risks. This study evaluates the feasibility of leveraging Natural Language Processing (NLP) techniques for real-time misinformation detection and classification, focusing on Reddit discussions. Using logistic regression as a baseline model, supplemented by Latent Dirichlet Allocation (LDA) for topic modeli...]]></description>
  <dc:date>2025-03-17</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1186/MedReg-KG-KnowledgeGraph-for-Streamlining-Medical-Device-Regulatory-Compliance">
  <title><![CDATA[MedReg-KG: KnowledgeGraph for Streamlining Medical Device Regulatory Compliance]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1186/MedReg-KG-KnowledgeGraph-for-Streamlining-Medical-Device-Regulatory-Compliance</link>
  <description><![CDATA[Healthcare providers are deploying a large number
of AI-driven Medical devices to help monitor and medicate
patients. For patients with chronic ailments, like diabetes or
gastric diseases, usage of these devices becomes part of their
daily lifestyle. These medical devices often capture personally
identifiable information (PII) and hence are strictly regulated by
the Food and Drug Administration (FDA) to ensure the safety
and efficacy of the medical device. Medical device regulations
a...]]></description>
  <dc:date>2024-12-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1173/GenAIPABench-A-Benchmark-for-Generative-AI-based-Privacy-Assistants">
  <title><![CDATA[GenAIPABench: A Benchmark for Generative AI-based Privacy Assistants]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1173/GenAIPABench-A-Benchmark-for-Generative-AI-based-Privacy-Assistants</link>
  <description><![CDATA[Website privacy policies are often lengthy and intricate. Privacy assistants help simplify policies and make them more accessible and user-friendly. The emergence of generative AI (genAI) offers new opportunities to build privacy assistants that can answer users’ questions about privacy policies. However, genAI’s reliability is a concern due to its potential for producing inaccurate information. This study introduces GenAIPABench, a benchmark for evaluating Generative AI-based Privacy Ass...]]></description>
  <dc:date>2024-07-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1174/Comparison-of-attribute-based-encryption-schemes-in-securing-healthcare-systems">
  <title><![CDATA[Comparison of attribute‑based encryption schemes in securing healthcare systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1174/Comparison-of-attribute-based-encryption-schemes-in-securing-healthcare-systems</link>
  <description><![CDATA[E-health has become a top priority for healthcare organizations focused on advancing healthcare
services. Thus, medical organizations have been widely adopting cloud services, resulting in the
effective storage of sensitive data. To prevent privacy and security issues associated with the data,
attribute-based encryption (ABE) has been a popular choice for encrypting private data. Likewise,
the attribute-based access control (ABAC) technique has been widely adopted for controlling data
ac...]]></description>
  <dc:date>2024-03-26</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1058/Semantically-Rich-Differential-Access-to-Secure-Cloud-EHR">
  <title><![CDATA[Semantically Rich Differential Access to Secure Cloud EHR]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1058/Semantically-Rich-Differential-Access-to-Secure-Cloud-EHR</link>
  <description><![CDATA[Existing Cloud-based Electronic Health Record (EHR) services face challenges in handling heterogeneous data and maintaining performance with large records since they often use a relational database or only partially store information in a graph database. We have developed a novel approach that allows fine-grained field-level security for Cloud EHRs to protect patient privacy and data security. Our graph-based EHR has been developed by integrating Attribute-based Encryption (ABE) with ontology...]]></description>
  <dc:date>2023-05-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1036/Process-Knowledge-Infused-AI-Toward-User-Level-Explainability-Interpretability-and-Safety">
  <title><![CDATA[Process Knowledge-Infused AI: Toward User-Level Explainability, Interpretability, and Safety]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1036/Process-Knowledge-Infused-AI-Toward-User-Level-Explainability-Interpretability-and-Safety</link>
  <description><![CDATA[AI has seen wide adoption for automating tasks in several domains. However, AI's use in high-value, sensitive, or safety-critical applications such as self-management for personalized health or personalized nutrition has been challenging. These require that the AI system follows guidelines or well-defined processes set by experts, community, or standards. We characterize these as process knowledge (PK). For example, to diagnose the severity of depression, the AI system should incorporate PK t...]]></description>
  <dc:date>2022-09-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1024/Semantically-Rich-Access-Control-in-Cloud-EHR-Systems-Based-on-MA-ABE">
  <title><![CDATA[Semantically Rich Access Control in Cloud EHR Systems Based on MA-ABE]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1024/Semantically-Rich-Access-Control-in-Cloud-EHR-Systems-Based-on-MA-ABE</link>
  <description><![CDATA[Winner of the Best Paper Award in the conferenceWith the rapid implementation of Cloud-based Electronic Health Record (EHR) systems, health providers are specifically concerned about handling data privacy on the cloud. Existing methods have either scalability issues by requiring that patients grant access to their medical data or a trust issue by having a single authority, thereby creating the problem of a single point of attack. Hence there is a need to develop an EHR system that addresses t...]]></description>
  <dc:date>2022-05-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1022/CyberEnt-A-Cybersecurity-Domain-Specific-Dataset-for-Named-Entity-Recognition">
  <title><![CDATA[CyberEnt: A Cybersecurity Domain Specific Dataset for Named Entity Recognition]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1022/CyberEnt-A-Cybersecurity-Domain-Specific-Dataset-for-Named-Entity-Recognition</link>
  <description><![CDATA[Named Entity Recognition (NER) is a critical component of automated knowledge extraction. It allows Natural Language Processing (NLP) models to label instances of real-world entities that are important in the context of the text. To be able to accomplish this, the NLP model needs to be trained on large corpora of human-annotated text. There are examples of general, domain-agonistic text corpora available, but they are not suited for fields such as cybersecurity, that require domain-specific t...]]></description>
  <dc:date>2022-04-18</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/852/Delegated-Authorization-Framework-for-EHR-Services-using-Attribute-Based-Encryption">
  <title><![CDATA[Delegated Authorization Framework for EHR Services using Attribute Based Encryption]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/852/Delegated-Authorization-Framework-for-EHR-Services-using-Attribute-Based-Encryption</link>
  <description><![CDATA[Medical organizations find it challenging to adopt cloud-based Electronic Health Records (EHR) services due to the risk of data breaches and the resulting compromise of patient data. Existing authorization models follow a patient-centric approach for EHR management, where the responsibility of authorizing data access is handled at the patient's end. This creates a significant overhead for the patient who must authorize every access of their health record. This is not practical given that mult...]]></description>
  <dc:date>2021-11-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/988/Secure-Cloud-EHR-with-Semantic-Access-Control-Searchable-Encryption-and-Attribute-Revocation">
  <title><![CDATA[Secure Cloud EHR with Semantic Access Control, Searchable Encryption and Attribute Revocation]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/988/Secure-Cloud-EHR-with-Semantic-Access-Control-Searchable-Encryption-and-Attribute-Revocation</link>
  <description><![CDATA[To ensure a secure Cloud-based Electronic Health Record (EHR) system, we need to encrypt data and impose field-level access control to prevent malicious usage. Since the attributes of the Users will change with time, the encryption policies adopted may also vary. For large EHR systems, it is often necessary to search through the encrypted data in realtime and perform client-side computations without decrypting all patient records. This paper describes our novel cloud-based EHR system that use...]]></description>
  <dc:date>2021-09-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/74/Database-Semanticizer-Presentation">
  <title><![CDATA[Database Semanticizer Presentation]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/74/Database-Semanticizer-Presentation</link>
  <description><![CDATA[The vision of the Semantic web is to give the web a well defined meaning
by representing the same in OWL and linking it to ontologies accepted
commonly by standardization efforts. Most of the formatted data is today
stored in the form of relational databases. We need to RDFize it in order
to use this data on the Semantic Web. The data model behind RDF is a
directed labeled graph, which consists of nodes and labeled directed arcs
linking pairs of nodes. To export data from an RDBMS into ...]]></description>
  <dc:date>2004-12-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/306/Detecting-Domain-Shift">
  <title><![CDATA[Detecting Domain Shift]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/306/Detecting-Domain-Shift</link>
  <description><![CDATA[Machine learning systems are typically trained in the lab and then deployed in the wild. But what happens when the data to which they are exposed in the wild change in a way that hurts accuracy? For example, a system may be trained to classify movie reviews as either positive or negative (i.e., sentiment classification), but over time book reviews get mixed into the data stream. The problem of responding to such changes when they are known to have occurred has been studied extensively. In thi...]]></description>
  <dc:date>2010-09-03</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/238/RDF-Web-service-v1-0-java-servlet-">
  <title><![CDATA[RDF Web service v1.0 (java servlet)]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/238/RDF-Web-service-v1-0-java-servlet-</link>
  <description><![CDATA[RDF123 is an application and web service for converting data in simple spreadsheets to an RDF graph.  The spreadsheets must consist of a single table with or without header rows.  Users control how the spreadsheet's data is converted to RDF by constructing a graphical RDF123 template that specifies how each row in the spreadsheet is converted as well as metadata for the spreadsheet and its RDF translation.  The template can map a spreadsheet cell to a new RDF node or to a literal value. Label...]]></description>
  <dc:date>2007-08-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/237/RDF123-java-application-v1-0">
  <title><![CDATA[RDF123 java application v1.0]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/237/RDF123-java-application-v1-0</link>
  <description><![CDATA[RDF123 is an application and web service for converting data in simple spreadsheets to an RDF graph.  The spreadsheets must consist of a single table with or without header rows.  Users control how the spreadsheet's data is converted to RDF by constructing a graphical RDF123 template that specifies how each row in the spreadsheet is converted as well as metadata for the spreadsheet and its RDF translation.  The template can map a spreadsheet cell to a new RDF node or to a literal value. Label...]]></description>
  <dc:date>2007-08-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/236/RDF123-linux-application-v1-0-With-Java-VM-self-contained-">
  <title><![CDATA[RDF123 linux application v1.0 (With Java VM self-contained)]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/236/RDF123-linux-application-v1-0-With-Java-VM-self-contained-</link>
  <description><![CDATA[RDF123 is an application and web service for converting data in simple spreadsheets to an RDF graph.  The spreadsheets must consist of a single table with or without header rows.  Users control how the spreadsheet's data is converted to RDF by constructing a graphical RDF123 template that specifies how each row in the spreadsheet is converted as well as metadata for the spreadsheet and its RDF translation.  The template can map a spreadsheet cell to a new RDF node or to a literal value. Label...]]></description>
  <dc:date>2007-08-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/233/RDF123-presentation">
  <title><![CDATA[RDF123 presentation]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/233/RDF123-presentation</link>
  <description><![CDATA[RDF123 is an application and web service for converting data in simple spreadsheets to an RDF graph. The spreadsheets must consist of a single table with or without header rows. Users control how the spreadsheet's data is converted to RDF by constructing a graphical RDF123 template that specifies how each row in the spreadsheet is converted as well as metadata for the spreadsheet and its RDF translation. The template can map a spreadsheet cell to a new RDF node or to a literal value. Labels o...]]></description>
  <dc:date>2007-07-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/228/RDF123-windows-application-v1-0-With-Java-VM-self-contained-">
  <title><![CDATA[RDF123 windows application v1.0 (With Java VM self-contained)]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/228/RDF123-windows-application-v1-0-With-Java-VM-self-contained-</link>
  <description><![CDATA[RDF123 is an application and web service for converting data in simple spreadsheets to an RDF graph.  The spreadsheets must consist of a single table with or without header rows.  Users control how the spreadsheet's data is converted to RDF by constructing a graphical RDF123 template that specifies how each row in the spreadsheet is converted as well as metadata for the spreadsheet and its RDF translation.  The template can map a spreadsheet cell to a new RDF node or to a literal value. Label...]]></description>
  <dc:date>2007-08-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/212/Splog-Blog-Dataset">
  <title><![CDATA[Splog Blog Dataset]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/212/Splog-Blog-Dataset</link>
  <description><![CDATA[This dataset consists of 3000 blog homepages, out of which 700 have been labeled as splogs, and another 700 as authentic blogs.


This training set was used in results of three papers, with emphasis on identifying blogs [1], on detecting spam blogs [2], and on analysing the splogosphere [3].


This collection can be used in further experimenting with splogs, or for building filters that could be deployed in real world systems. We, and our academic and industrial collaborators have bee...]]></description>
  <dc:date>2006-11-14</dc:date>
 </item>
</rdf:RDF>
