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 <item rdf:about="http://ebiquity.umbc.edu/conference/html/id/6/Knowledge-Representation-2004">
  <title><![CDATA[Knowledge Representation 2004]]></title>
  <link>http://ebiquity.umbc.edu/conference/html/id/6/Knowledge-Representation-2004</link>
  <description><![CDATA[KR2004 will collocate with the International Conference on Automated Planning and Scheduling (ICAPS-2004), with one day in common. We strongly encourage papers which would be of interest to both communities.]]></description>
  <dc:date>2004-06-02</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/483/From-Strings-to-Things">
  <title><![CDATA[From Strings to Things]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/483/From-Strings-to-Things</link>
  <description><![CDATA[The Web is the greatest source of general knowledge available today. Its current form, however, suffers from two limitations.  The first is that text and multimedia objects on the Web are easy for people to understand but difficult for machines to interpret and use.  The second is that the Web's access paradigm remains dominated by information retrieval, where keyword queries produce a ranked list of documents that must be read to find the desired information.  I'll discuss research in natura...]]></description>
  <dc:date>2016-07-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/262/How-To-Tell-Stuff-To-Your-Computer-The-Enigmatic-Art-of-Knowledge-Representation">
  <title><![CDATA[How To Tell Stuff To Your Computer- The Enigmatic Art of Knowledge Representation]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/262/How-To-Tell-Stuff-To-Your-Computer-The-Enigmatic-Art-of-Knowledge-Representation</link>
  <description><![CDATA[Have you ever wondered how we take information from the "real world" and put it into our computers? When we do this, do we lose parts of the information? Are some concepts just too hard to turn into ones and zeroes? How is our ability to enter information limited by the data structures we use inside of our computers? These questions enter into a science that is rarely discussed: The science of Knowledge Representation.

My presentation on KR will include some navel gazing, but also some nit...]]></description>
  <dc:date>2008-10-17</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/119/Integrating-Language-Understanding-Agents-Into-the-Semantic-Web">
  <title><![CDATA[Integrating Language Understanding Agents Into the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/119/Integrating-Language-Understanding-Agents-Into-the-Semantic-Web</link>
  <description><![CDATA[Many intelligent agents need knowledge and information to support
their reasoning and problem solving. The World Wide Web is a vast,
open, accessible and free source of knowledge, but virtually all of it
is encoded as natural language text -- a form difficult for most
agents to directly understand.  We describe initial work on adapting a
mature language understanding agent to process Web text and publish
its output in the Semantic Web language OWL.  This approach adds
knowledge on the ...]]></description>
  <dc:date>2005-10-26</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/23/UMBC-and-IBM-collaborate-on-autonomic-computing">
  <title><![CDATA[UMBC and IBM collaborate on autonomic computing]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/23/UMBC-and-IBM-collaborate-on-autonomic-computing</link>
  <description><![CDATA[University of Maryland, Baltimore County and IBM Collaborate on 
Autonomic Computing Research

BALTIMORE, February 24, 2005 - IBM today announced a new Shared University Research (SUR) grant awarded a group of faculty researchers of the eBiquity research group at the University of Maryland, Baltimore County to help build a major new center for high performance computational research. 

This SUR grant is part of the latest series of Shared University Research (SUR) awards, bringing IBM's ...]]></description>
  <dc:date>2005-02-24</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/project/html/id/57/Text-Mining-Approach-to-Ontology-Enrichment">
  <title><![CDATA[Text Mining Approach to Ontology Enrichment]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/57/Text-Mining-Approach-to-Ontology-Enrichment</link>
  <description><![CDATA[Ontologies have been widely accepted as the most advanced knowledge representation model. They are among the most important building blocks of semantic web, hence, very crucial for the success of semantic web. Huge effort is needed from the domain expert in order to construct ontologies manually. There is a need for semi-automatic approach in ontology building which will help the domain expert in constructing extensive domain ontologies efficiently. We propose the use of text mining technique...]]></description>
  <dc:date>2003-10-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1212/TRUCE-TRUsted-Compliance-Enforcement-Service-for-Secure-Health-Data-Exchange">
  <title><![CDATA[TRUCE: TRUsted Compliance Enforcement Service for Secure Health Data Exchange]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1212/TRUCE-TRUsted-Compliance-Enforcement-Service-for-Secure-Health-Data-Exchange</link>
  <description><![CDATA[Organizations are increasingly sharing large volumes of sensitive Personally Identifiable Information (PII), like health records, with each other to better manage their services. Protecting PII data has become increasingly important in today's digital age, and several regulations have been formulated to ensure the secure exchange and management of sensitive personal data. However, at times some of these regulations are at loggerheads with each other, like the Health Insurance Portability and ...]]></description>
  <dc:date>2025-12-09</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1073/An-Overview-of-Cybersecurity-Knowledge-Graphs-Mapped-to-the-MITRE-ATT-CK-Framework-Domains">
  <title><![CDATA[An Overview of Cybersecurity Knowledge Graphs Mapped to the MITRE ATT&CK Framework Domains]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1073/An-Overview-of-Cybersecurity-Knowledge-Graphs-Mapped-to-the-MITRE-ATT-CK-Framework-Domains</link>
  <description><![CDATA[A large volume of cybersecurity-related data sets
are generated daily from systems following disparate protocols
and standards. It is humanly impossible for cybersecurity experts
to manually sieve through these large data sets, with different
schema and metadata, to determine potential attacks or issues.
A myriad of applications and tool sets are offered to automate
the analysis of large cyber data sets. Semantic Web’s community
has been studying the field of cybersecurity for over a...]]></description>
  <dc:date>2023-10-03</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1048/TDLR-Top-Semantic-Down-Syntactic-Language-Representation">
  <title><![CDATA[TDLR: Top (Semantic)-Down (Syntactic) Language Representation]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1048/TDLR-Top-Semantic-Down-Syntactic-Language-Representation</link>
  <description><![CDATA[Language understanding involves processing text with both the grammatical and common-sense contexts of the text fragments. The text “I went to the grocery store and brought home a car” requires both the grammatical context (syntactic) and common-sense context (semantic) to capture the oddity in the sentence. Contextualized text representations learned by Language Models (LMs) are expected to capture a variety of syntactic and semantic contexts from large amounts of training data corpora. ...]]></description>
  <dc:date>2022-11-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/995/Semantically-Rich-Framework-to-Automate-Cyber-Insurance-Services">
  <title><![CDATA[Semantically Rich Framework to Automate Cyber Insurance Services]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/995/Semantically-Rich-Framework-to-Automate-Cyber-Insurance-Services</link>
  <description><![CDATA[With the rapid enhancements in technology and the adoption of web services, there has been a significant increase in cyber threats
faced by organizations in cyberspace. It has become essential to get financial cover to mitigate the expenses due to a security incident.
Organizations want to purchase adequate cyber insurance to safeguard against the third-party services they use. However, cyber insurance policies describe their coverages and exclusions using legal jargon that can be difficult...]]></description>
  <dc:date>2021-11-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/975/Automated-Compliance-of-Mobile-Wallet-Payments-for-Cloud-Services">
  <title><![CDATA[Automated Compliance of Mobile Wallet Payments for Cloud Services]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/975/Automated-Compliance-of-Mobile-Wallet-Payments-for-Cloud-Services</link>
  <description><![CDATA[Mobile payments are on the rise, and as their popularity is emerging, providers must adhere to security regulations to ensure consumer confidence. There is currently no single regulation specific to mobile wallets, so existing banking transactions are used to secure mobile payment transactions. These financial regulations are large textual documents and require significant manual effort to comprehend and ensure compliance adherence. Thus, it is difficult for both the consumers and providers t...]]></description>
  <dc:date>2021-05-17</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/963/A-Semantically-Rich-Framework-for-Knowledge-Representation-of-Code-of-Federal-Regulations-CFR-">
  <title><![CDATA[A Semantically Rich Framework for Knowledge Representation of Code of Federal Regulations (CFR)]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/963/A-Semantically-Rich-Framework-for-Knowledge-Representation-of-Code-of-Federal-Regulations-CFR-</link>
  <description><![CDATA[Federal government agencies and organizations doing business with them have to adhere to the Code of Federal Regulations (CFR). The CFRs are currently available as large text documents that are not machine-processable and so require extensive manual effort to parse and comprehend, especially when sections cross-reference topics spread across various titles. We have developed a novel framework to automatically extract knowledge from CFRs and represent it using a semantically rich knowledgegrap...]]></description>
  <dc:date>2020-12-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/910/Joint-Models-to-Refine-Knowledge-Graphs">
  <title><![CDATA[Joint Models to Refine Knowledge Graphs]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/910/Joint-Models-to-Refine-Knowledge-Graphs</link>
  <description><![CDATA[A knowledge graph can be viewed as a structural representation of beliefs with nodes and edges in which the nodes represent real-world entities or events and the edges are relations believed to hold between pairs of entities. Multiple levels of processes are involved in extracting such knowledge graphs from natural language text, starting with reading and understanding the text, then constructing a graph of the entities found and the relations between them, and inferring missing relations tha...]]></description>
  <dc:date>2019-12-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1059/Cyber-All-Intel-An-AI-for-Security-Related-Threat-Intelligence">
  <title><![CDATA[Cyber-All-Intel: An AI for Security Related Threat Intelligence]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1059/Cyber-All-Intel-An-AI-for-Security-Related-Threat-Intelligence</link>
  <description><![CDATA[Keeping up with threat intelligence is a must for a security analyst today. There is a volume of information present in `the wild' that affects an organization. We need to develop an artificial intelligence system that scours the intelligence sources to keep the analyst updated about various threats that pose a risk to her organization. A security analyst who is better `tapped in' can be more effective. This paper presents Cyber-All-Intel, an artificial intelligence system to aid a security a...]]></description>
  <dc:date>2019-05-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/912/Knowledge-for-Cyber-Threat-Intelligence">
  <title><![CDATA[Knowledge for Cyber Threat Intelligence]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/912/Knowledge-for-Cyber-Threat-Intelligence</link>
  <description><![CDATA[Keeping up with threat intelligence is a must for a security analyst today. There is a volume of information present in 'the wild' that affects an organization. We need to develop an artificial intelligence system that scours the intelligence sources, to keep the analyst updated about various threats that pose a risk to her organization. A security analyst who is better 'tapped in' can be more effective.

In this thesis, we present, Cyber-All-Intel an artificial intelligence system to aid a...]]></description>
  <dc:date>2019-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/1134/Knowledge-for-Cyber-Threat-Intelligence">
  <title><![CDATA[Knowledge for Cyber Threat Intelligence]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1134/Knowledge-for-Cyber-Threat-Intelligence</link>
  <description><![CDATA[Keeping up with threat intelligence is a must for a security analyst today.
There is a volume of information present in 'the wild' that affects an organization.
We need to develop an artificial intelligence system that scours the intelligence
sources, to keep the analyst updated about various threats that pose a risk to her
organization. A security analyst who is better 'tapped in' can be more effective.
In this thesis, we present, Cyber-All-Intel an artificial intelligence system to
ai...]]></description>
  <dc:date>2019-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/research/area/id/15/Knowledge-Representation-and-Reasoning">
  <title><![CDATA[Knowledge Representation and Reasoning]]></title>
  <link>http://ebiquity.umbc.edu/research/area/id/15/Knowledge-Representation-and-Reasoning</link>
  <description><![CDATA[Knowledge representation and reasoning  refers to the general topic of how information can be appropriately encoded and used in computational systems.  Many intelligent systems have explicit knowledge bases they use to represent and manipulate their model of the word.]]></description>
  <dc:date>2026-05-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/392/Sixty-years-of-knowledge-graphs-for-language-understanding">
  <title><![CDATA[Sixty years of knowledge graphs for language understanding]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/392/Sixty-years-of-knowledge-graphs-for-language-understanding</link>
  <description><![CDATA[There is a long history of using structured knowledge of one kind or another to support AI tasks, especially ones involving natural language understanding. Over the years, the names and details have changed, from semantic networks to frames to logic programs to databases to expert systems to knowledge bases to the semantic web and currently to knowledge graphs. However, a common thread is that an organized representation of knowledge that can be queried and evolved is a core component of many...]]></description>
  <dc:date>2019-09-19</dc:date>
 </item>
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