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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/466/PhD-defense-Lushan-Han-Schema-Free-Querying-of-Semantic-Data"/>
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      <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/399/Context-Aware-Middleware-for-Activity-Recognition"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/381/Domain-Independent-Sentiment-Analysis"/>
      <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/event/html/id/327/A-Schema-Based-Approach-Combined-with-Inter-Ontology-Reasoning-to-Construct-Consensus-Ontologies"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/33/SemNews-news-text-to-Semantic-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/95/Graph-of-Relations"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/101/MTLD-Interpreting-Medical-Tables-as-Linked-Data"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/56/Semantic-Discovery-Discovering-Complex-Relationships-in-Semantic-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1222/Ontology-Driven-Agentic-System-for-Automating-Security-Compliance-in-Medical-Cyber-Physical-WBANs"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1214/Measuring-the-Compliance-Costs-of-Exchanging-Part-2-Healthcare-Claims-Data-Through-Blockchain"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1217/Deontic-Knowledge-Graphs-for-Privacy-Compliance-in-Multimodal-Disaster-Data-Sharing"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1207/LLM-based-Knowledge-Graph-Approach-to-Automating-Medical-Device-Regulatory-Compliance"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1210/Security-Compliance-for-Smart-Manufacturing-using-Knowledgegraph-based-Digital-Twin"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1203/DUNE-A-Machine-Learning-Deep-UNET-based-ensemble-Approach-to-Monthly-Seasonal-and-Annual-Climate-Forecasting"/>
      <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/1177/FABULA-Intelligence-Report-Generation-Using-Retrieval-Augmented-Narrative-Construction"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1078/Semantically-informed-Hierarchical-Event-Modeling"/>
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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/466/PhD-defense-Lushan-Han-Schema-Free-Querying-of-Semantic-Data">
  <title><![CDATA[PhD defense: Lushan Han, Schema Free Querying of Semantic Data]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/466/PhD-defense-Lushan-Han-Schema-Free-Querying-of-Semantic-Data</link>
  <description><![CDATA[Schema Free Querying of Semantic Data

Lushan Han

Developing interfaces to enable casual, non-expert users to query complex structured data has been the subject of much research over the past forty years. We refer to them as as schema-free query interfaces, since they allow users to freely query data without understanding its schema, knowing how to refer to objects, or mastering the appropriate formal query language. Schema-free query interfaces address fundamental problems in natural la...]]></description>
  <dc:date>2014-05-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/447/Generating-Linked-Data-from-Tables-">
  <title><![CDATA[Generating Linked Data from Tables.]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/447/Generating-Linked-Data-from-Tables-</link>
  <description><![CDATA[Large amounts of information is stored in tables, spreadsheets, CSV files and databases for a number of domains, including the Web, healthcare, e-science and public policy. The tables' structure facilitates human understanding, yet this very structure makes it difficult for machine understanding. This talk will focus on describing our work on making the intended meaning of tabular data explicit by representing it as RDF linked data, potentially making large amounts of scientific and medical d...]]></description>
  <dc:date>2013-03-24</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/442/Cloud-based-Active-Archiving-Solution-for-Databases">
  <title><![CDATA[Cloud based Active Archiving Solution for Databases]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/442/Cloud-based-Active-Archiving-Solution-for-Databases</link>
  <description><![CDATA[In the second talk of the UMBC ACM Student Chapter's Tech Talk Series, ACM Distinguished Speaker Dr. Mukesh Mohania will visit UMBC and talk about "Cloud based Active Archiving Solution for Databases".

Cloud computing offers an exciting opportunity to bring on-demand applications to customers and is being used for delivering hosted services over the Internet and/or processing massive amount of data for business intelligence. In this talk, we will discuss the architecture of cloud computing...]]></description>
  <dc:date>2012-11-30</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/400/Generating-Linked-Data-by-inferring-the-semantics-of-tables">
  <title><![CDATA[Generating Linked Data by inferring the semantics of tables]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/400/Generating-Linked-Data-by-inferring-the-semantics-of-tables</link>
  <description><![CDATA[Ph.D. Preliminary Examination
A vast amount of information is encoded in tables on the web, spreadsheets and databases. Considerable work has been focused on exploiting unstructured free text; however techniques that are effective for documents and free text do not work well with tables. In this research we present techniques to generate high quality linked data from tables by jointly inferring the semantics of column headers, table cell values (e.g., strings and numbers), relations between ...]]></description>
  <dc:date>2011-05-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/399/Context-Aware-Middleware-for-Activity-Recognition">
  <title><![CDATA[Context-Aware Middleware for Activity Recognition]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/399/Context-Aware-Middleware-for-Activity-Recognition</link>
  <description><![CDATA[Smartphones and other mobile devices have a simple notion of context largely restricted to temporal and spatial coordinates. Service providers and enterprise administrators can deploy systems incorporating activity and relations context to enhance the user experience, but this raises considerable collaboration, trust and privacy issues between different service providers. Our work is an initial step toward enabling devices themselves to represent, acquire and use a richer notion of context th...]]></description>
  <dc:date>2011-05-19</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/381/Domain-Independent-Sentiment-Analysis">
  <title><![CDATA[Domain Independent Sentiment Analysis]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/381/Domain-Independent-Sentiment-Analysis</link>
  <description><![CDATA[Domain independent sentiment signals are words or word pairs that are present and have the same sentimental orientation in multiple domains. These words can be easily identified if you have an accurate representation of their in-domain sentimental orientation. If you also have an accurate representation of their sentimental strength then you can use them to correctly classify out of domain documents with reasonable accuracy. In this talk I will present a method to identify domain independent ...]]></description>
  <dc:date>2011-03-01</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/event/html/id/327/A-Schema-Based-Approach-Combined-with-Inter-Ontology-Reasoning-to-Construct-Consensus-Ontologies">
  <title><![CDATA[A Schema-Based Approach Combined with Inter-Ontology Reasoning to  Construct Consensus Ontologies]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/327/A-Schema-Based-Approach-Combined-with-Inter-Ontology-Reasoning-to-Construct-Consensus-Ontologies</link>
  <description><![CDATA[As the Semantic Web gains attention as the next generation of the Web, the issue of reconciling different views of independently developed and exposed data sources becomes increasingly important. Ontology integration serves as a basis for solving this problem. In this paper, we describe an approach to construct a consensus ontology from numerous, independently designed ontologies.

Our method has the following features: i) the matching is carried out at the schema level; ii) the alignment o...]]></description>
  <dc:date>2009-11-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/33/SemNews-news-text-to-Semantic-Web">
  <title><![CDATA[SemNews: news text to Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/33/SemNews-news-text-to-Semantic-Web</link>
  <description><![CDATA[SemNews Understands the News 

 Prototype UMBC system interprets online news stories  and  publishes text meaning on the Semantic Web

      SemNews is a prototype
application being developed by UMBC Ph.D. student Akshay Java that
uses a sophisticated text understanding system to interpret summaries
of news stories, publishes the results on the semantic web and
provides browsing and query services over them.  The project is the
result of a collaboration between the UMBC's Institute ...]]></description>
  <dc:date>2006-01-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/95/Graph-of-Relations">
  <title><![CDATA[Graph of Relations]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/95/Graph-of-Relations</link>
  <description><![CDATA[ 
Users need better ways to explore linked open data collections and obtain information from it. Using SPARQL requires not only mastering its syntax and semantics but also understanding the RDF data model, the ontology used by the DBpedia, and URIs for entities of interest.  Natural language question answering systems solve the problem, but these are still subjects of research. We are developing a compromise approach in which non-experts specify a graphical ``skeleton'' for a query and anno...]]></description>
  <dc:date>2010-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/101/MTLD-Interpreting-Medical-Tables-as-Linked-Data">
  <title><![CDATA[MTLD: Interpreting Medical Tables as Linked Data]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/101/MTLD-Interpreting-Medical-Tables-as-Linked-Data</link>
  <description><![CDATA[Evidence-based medicine is the application of current medical evidence
to patient care and typically uses quantitative data from research
studies.  It is increasingly driven by data on the efficacy of drug
dosages and the correlation between various medical factors that is
assembled and integrated through meta--analyses (i.e., systematic
reviews) of data in tables from publications and clinical trial
studies.  We describe a a key component of a system to produce
evidence reports that p...]]></description>
  <dc:date>2014-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/56/Semantic-Discovery-Discovering-Complex-Relationships-in-Semantic-Web">
  <title><![CDATA[Semantic Discovery: Discovering Complex Relationships in Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/56/Semantic-Discovery-Discovering-Complex-Relationships-in-Semantic-Web</link>
  <description><![CDATA[Research in search techniques was a critical component of the first generation of the Web, and has gone from academe to mainstream. A second generation Semantic Web will be built by adding semantic annotations that software can understand and from which humans can benefit. Modeling, discovering and reasoning about complex relationships on the Semantic Web will enable this vision and transform the hunt for documents into a more automated analysis enabled by semantic technology. The beginnings ...]]></description>
  <dc:date>2003-10-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1222/Ontology-Driven-Agentic-System-for-Automating-Security-Compliance-in-Medical-Cyber-Physical-WBANs">
  <title><![CDATA[Ontology Driven Agentic System for Automating Security Compliance in Medical Cyber-Physical WBANs]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1222/Ontology-Driven-Agentic-System-for-Automating-Security-Compliance-in-Medical-Cyber-Physical-WBANs</link>
  <description><![CDATA[Medical Wireless Body Area Networks (WBANs)
operate as medical cyber-physical systems (MCPS) that continuously
sense and transmit sensitive patient health data, creating
significant security, privacy, and regulatory challenges. Traditional
WBAN protections focus on lightweight cryptography but
lack semantic reasoning and automated compliance of data regulations
such as Health Insurance Portability and Accountability
Act (HIPAA) and General Data Protection Regulation (GDPR).
We have de...]]></description>
  <dc:date>2026-07-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1214/Measuring-the-Compliance-Costs-of-Exchanging-Part-2-Healthcare-Claims-Data-Through-Blockchain">
  <title><![CDATA[Measuring the Compliance Costs of Exchanging Part 2 Healthcare Claims Data Through Blockchain]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1214/Measuring-the-Compliance-Costs-of-Exchanging-Part-2-Healthcare-Claims-Data-Through-Blockchain</link>
  <description><![CDATA[Patient selections for keeping data confidential may differ between healthcare organizations, creating conflicts
in confidentiality for how sensitive and demographic data is linked and merged. Validating that patient data
exchange between organizations adheres to healthcare regulations, like the Health Insurance Portability and
Accountability Act (HIPAA), is challenging and time-consuming and relies upon organizational due diligence
to validate data upon receipt, or in the case of breache...]]></description>
  <dc:date>2026-03-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1217/Deontic-Knowledge-Graphs-for-Privacy-Compliance-in-Multimodal-Disaster-Data-Sharing">
  <title><![CDATA[Deontic Knowledge Graphs for Privacy Compliance in Multimodal Disaster Data Sharing]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1217/Deontic-Knowledge-Graphs-for-Privacy-Compliance-in-Multimodal-Disaster-Data-Sharing</link>
  <description><![CDATA[Disaster response requires sharing heterogeneous artifacts, from tabular assistance records to UAS imagery, under overlapping privacy mandates. Operational systems often reduce compliance to binary access control, which is brittle in time-critical workflows. We present a novel deontic knowledge graph-based framework that integrates a Disaster Management Knowledge Graph (DKG) with a Policy Knowledge Graph (PKG) derived from IoT-Reg and FEMA/DHS privacy drivers. Our release decision function su...]]></description>
  <dc:date>2026-01-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1207/LLM-based-Knowledge-Graph-Approach-to-Automating-Medical-Device-Regulatory-Compliance">
  <title><![CDATA[LLM based Knowledge Graph Approach to Automating Medical Device Regulatory Compliance]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1207/LLM-based-Knowledge-Graph-Approach-to-Automating-Medical-Device-Regulatory-Compliance</link>
  <description><![CDATA[Advanced medical devices increasingly rely on AI driven frameworks to automate compliance processes, ensuring safety and efficacy while reducing regulatory burdens. In the US, software-based medical devices, including those utilizing AI/ML models, are regulated by the FDA’s Center for Devices and Radiological Health (CDRH) under the Code of Federal Regulations (CFR) Title 21. These regulations are extensive, cross-referenced documents that require significant human effort to parse, leading ...]]></description>
  <dc:date>2025-12-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1210/Security-Compliance-for-Smart-Manufacturing-using-Knowledgegraph-based-Digital-Twin">
  <title><![CDATA[Security Compliance for Smart Manufacturing using Knowledgegraph based Digital Twin]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1210/Security-Compliance-for-Smart-Manufacturing-using-Knowledgegraph-based-Digital-Twin</link>
  <description><![CDATA[The combination of Information Technology (IT) and Operational Technology (OT) in smart manufacturing, driven by smart factory innovations and Internet of Things (IoT) devices, generates vast, diverse, and rapidly evolving Big Data, which in turn increases cybersecurity and compliance issues. Adherence to security standards, such as NIST SP 800-171, which requires rigorous access control and audit reporting, is currently obstructed by the resource-intensive and error-prone aspects of manual e...]]></description>
  <dc:date>2025-12-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1203/DUNE-A-Machine-Learning-Deep-UNET-based-ensemble-Approach-to-Monthly-Seasonal-and-Annual-Climate-Forecasting">
  <title><![CDATA[DUNE: A Machine Learning Deep UNET++ based ensemble Approach to Monthly, Seasonal and Annual Climate Forecasting]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1203/DUNE-A-Machine-Learning-Deep-UNET-based-ensemble-Approach-to-Monthly-Seasonal-and-Annual-Climate-Forecasting</link>
  <description><![CDATA[Capitalizing on the recent availability of ERA5 monthly averaged, long-term data records of mean atmospheric and climate fields derived from the high-resolution reanalysis, deep learning architectures provide an alternative to physics-based daily numerical weather predictions for subseasonal to seasonal (S2S) and annual forecasts. A novel deep U-Net++-based ensemble (DUNE) neural architecture is introduced, incorporating encoder–decoder structures with residual blocks. When initialized with...]]></description>
  <dc:date>2025-10-01</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/1177/FABULA-Intelligence-Report-Generation-Using-Retrieval-Augmented-Narrative-Construction">
  <title><![CDATA[FABULA: Intelligence Report Generation Using Retrieval-Augmented Narrative Construction]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1177/FABULA-Intelligence-Report-Generation-Using-Retrieval-Augmented-Narrative-Construction</link>
  <description><![CDATA[Narrative construction is the process of representing disparate event information into a logical plot structure that models an end-to-end story. Intelligence analysis is an example of a domain that can benefit tremendously from narrative construction techniques, particularly in aiding analysts during the largely manual and costly process of synthesizing event information into comprehensive intelligence reports. Manual intelligence report generation is often prone to challenges such as integra...]]></description>
  <dc:date>2023-11-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1078/Semantically-informed-Hierarchical-Event-Modeling">
  <title><![CDATA[Semantically-informed Hierarchical Event Modeling]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1078/Semantically-informed-Hierarchical-Event-Modeling</link>
  <description><![CDATA[Prior work has shown that coupling sequential latent variable models with semantic ontological knowledge can improve the representational capabilities of event modeling approaches.  In this work, we present a novel, doubly hierarchical, semi-supervised event modeling framework that provides structural hierarchy while also accounting for ontological hierarchy. Our approach consists of multiple layers of structured latent variables, where each successive layer compresses and abstracts the previ...]]></description>
  <dc:date>2023-07-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1069/ProKnow-Process-knowledge-for-safety-constrained-and-explainable-question-generation-for-mental-health-diagnostic-assistance">
  <title><![CDATA[ProKnow: Process knowledge for safety constrained and explainable question generation for mental health diagnostic assistance]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1069/ProKnow-Process-knowledge-for-safety-constrained-and-explainable-question-generation-for-mental-health-diagnostic-assistance</link>
  <description><![CDATA[Virtual Mental Health Assistants (VMHAs) are utilized in health care to provide patient services such as counseling and suggestive care. They are not used for patient diagnostic assistance because they cannot adhere to safety constraints and specialized clinical process knowledge (ProKnow) used to obtain clinical diagnoses. In this work, we define ProKnow as an ordered set of information that maps to evidence-based guidelines or categories of conceptual understanding to experts in a domain. W...]]></description>
  <dc:date>2023-01-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/283/A-Schema-Based-Approach-Combined-with-Inter-Ontology-Reasoning-to-Construct-Consensus-Ontologies">
  <title><![CDATA[A Schema-Based Approach Combined with Inter-Ontology Reasoning to Construct Consensus Ontologies]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/283/A-Schema-Based-Approach-Combined-with-Inter-Ontology-Reasoning-to-Construct-Consensus-Ontologies</link>
  <description><![CDATA[As the Semantic Web gains attention as the next generation of the Web, the issue of reconciling different views of independently developed and exposed data sources becomes increasingly important. Ontology integration serves as a basis for solving this problem. In this paper, we describe an approach to construct a consensus ontology from numerous, independently designed ontologies.

Our method has the following features: i) the matching is carried out at the schema level; ii) the alignment o...]]></description>
  <dc:date>2009-11-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/379/Cybersecurity-embeddings">
  <title><![CDATA[Cybersecurity embeddings]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/379/Cybersecurity-embeddings</link>
  <description><![CDATA[This is a word embedding model produced by Dr. Youngja Park of IBM Research using word2vec applied to a collection of one million documents found on the Web relevant to cybersecurity.  Tokenization was done using whitespace, resulting in 917,213,530 tokens of which 6,417,554 were unique. The word2 vec model has 100 dimensions and a vocabulary of 1,013,092 terms.  If you use this model in your research, please cite this document to refer to the model.

Ankur Padia, Arpita Roy, Taneeya Satyap...]]></description>
  <dc:date>2018-04-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/190/Detecting-Spam-Blogs-A-Machine-Learning-Approach">
  <title><![CDATA[Detecting Spam Blogs: A Machine Learning Approach]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/190/Detecting-Spam-Blogs-A-Machine-Learning-Approach</link>
  <description><![CDATA[Weblogs or blogs are an important new way to publish information, engage in discussions, and form communities on the Internet. The Blogosphere has unfortunately been infected by several varieties of spam-like content. Blog search engines, for example, are inundated by posts from splogs – false blogs with machine generated or hijacked content whose sole purpose is to host ads or raise the PageRank of target sites. We discuss how SVM models based on local and link-based features can be used t...]]></description>
  <dc:date>2006-07-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/254/Video-Segmentation-Critical-View">
  <title><![CDATA[Video Segmentation -- Critical View]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/254/Video-Segmentation-Critical-View</link>
  <description><![CDATA[Laparoscopic surgery is a minimally invasive technique with unique training requirements. Video-assisted evaluation is one method that surgical residents can use to demonstrate competence. Automated video summarization can increase the efficiency of evaluations by directing the senior surgeon to key portions of a surgical procedure. We are using image classification techniques to segment videos of laparoscopic cholecystectomies to assist with surgical training and evaluation.]]></description>
  <dc:date>2008-11-04</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/387/What-generative-AI-systems-know-about-cybersecurity">
  <title><![CDATA[What generative AI systems know about cybersecurity]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/387/What-generative-AI-systems-know-about-cybersecurity</link>
  <description><![CDATA[The public release of OpenA's ChatGPT system in November 2022 signaled an inflection point for AI technology and its applications. While these AI systems have well-known shortcomings, they have the potential to help in many ways. After describing the technology, I  report on a recent evaluation of OpenAI's ChatGPT and Google's Bard ability to solve cybersecurity problems using two datasets designed to test students' knowledge: the Cybersecurity Concept Inventory (CCI) and the Cybersecurity Cu...]]></description>
  <dc:date>2023-10-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/390/What-generative-AI-systems-know-about-cybersecurity">
  <title><![CDATA[What generative AI systems know about cybersecurity]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/390/What-generative-AI-systems-know-about-cybersecurity</link>
  <description><![CDATA[The public release of OpenAI's ChatGPT system eight months ago signaled an inflection point for AI technology and its applications. While these AI systems have well-known shortcomings, they have the potential to help in many ways. After describing the technology, I will report on a recent evaluation of OpenAI's ChatGPT and Google's Bard ability to solve cybersecurity problems using two datasets designed to test students' knowledge: the Cybersecurity Concept Inventory (CCI) and the Cybersecuri...]]></description>
  <dc:date>2023-09-07</dc:date>
 </item>
</rdf:RDF>
