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      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/482/Kelvin-Information-Extraction-System"/>
      <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/469/Infoboxer-Using-Statistical-and-Semantic-Knowledge-to-Help-Create-Wikipedia-Infoboxes"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/460/Phd-proposal-A-Semantic-Resolution-Framework-for-Manufacturing-Capability-Data-Integration"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/455/Text-and-Ontology-Driven-Clinical-Decision-Support-System"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/393/PowerRelations-A-Question-Answering-System-for-DBPedia"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/391/Extracting-Information-about-Security-Vulnerabilities-from-Web-Text"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/368/Text-Based-Similarity-Metrics-and-Deltas-for-Semantic-Web-Graphs"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/70/CoCoNet-Content-and-Context-Aware-Networking"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/100/Text-and-Ontology-Driven-Clinical-Decision-Support-System"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/57/Text-Mining-Approach-to-Ontology-Enrichment"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1051/A-Practical-Entity-Linking-System-for-Tables-in-Scientific-Literature"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/1069/ProKnow-Process-knowledge-for-safety-constrained-and-explainable-question-generation-for-mental-health-diagnostic-assistance"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/902/Affinity-Propagation-Initialisation-Based-Proximity-Clustering-For-Labeling-in-Natural-Language-Based-Big-Data-Systems"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/857/Automating-Class-Instance-Representational-Choices-in-Knowledge-Bases"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/841/KG-Cleaner-Identifying-and-Correcting-Errors-Produced-by-Information-Extraction-Systems"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/913/On-the-Integration-of-Inconsistent-Knowledge-with-Bayseian-Networks"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/812/Automated-Knowledge-Extraction-from-the-Federal-Acquisition-Regulations-System-FARS-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/817/Participation-in-TAC-KBP-2017-Cold-Start-TEDL-and-Low-resource-EDL"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/780/Cognitive-Assistance-for-Automating-the-Analysis-of-the-Federal-Acquisition-Regulations-System"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/288/Creating-and-Exploiting-a-Web-of-Semantic-Data"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/316/Generating-Linked-Data-by-inferring-the-semantics-of-tables"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/64/Modeling-and-using-trust-and-provenance-in-the-Semantic-Web"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/327/situational-awareness-for-cybersecurity"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/392/Sixty-years-of-knowledge-graphs-for-language-understanding"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/356/Text-and-Ontology-Driven-Clinical-Decision-Support-System"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/300/Text-Based-Similarity-Metrics-and-Delta-for-Semantic-Web-Graphs"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/371/UMBC-IOT-Android-client"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/261/WIkipedia-as-an-ontology"/>
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 <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/482/Kelvin-Information-Extraction-System">
  <title><![CDATA[Kelvin Information Extraction System]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/482/Kelvin-Information-Extraction-System</link>
  <description><![CDATA[I'll describe recent work on the Kelvin information extraction system and its performance in two tasks in the 2015 NIST Text Analysis Conference.  Kelvin has been under development at the JHU Human Language Center of Excellence for several years.  Kelvin reads documents in several languages and extracts entities and relations between them. This year it was used for the Coldstart Knowledge Base Population and Trilingual Entity Discovery and Linking tasks.  Key components in the tasks are a sys...]]></description>
  <dc:date>2015-11-02</dc:date>
 </item>
 <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/469/Infoboxer-Using-Statistical-and-Semantic-Knowledge-to-Help-Create-Wikipedia-Infoboxes">
  <title><![CDATA[Infoboxer: Using Statistical and Semantic Knowledge to Help Create Wikipedia Infoboxes]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/469/Infoboxer-Using-Statistical-and-Semantic-Knowledge-to-Help-Create-Wikipedia-Infoboxes</link>
  <description><![CDATA[Wikipedia infoboxes serve as input in the creation of knowledge bases
such as DBpedia, Yago, and Freebase. Current creation of Wikipedia
infoboxes is manual and based on templates that are created and
maintained collaboratively.  However, these templates pose several
challenges:



Different communities use different infobox templates for the same category articles

Attribute names differ (e.g., date of birth vs. birthdate)

Templates are restricted to a single category, mak...]]></description>
  <dc:date>2014-10-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/460/Phd-proposal-A-Semantic-Resolution-Framework-for-Manufacturing-Capability-Data-Integration">
  <title><![CDATA[Phd proposal: A Semantic Resolution Framework for Manufacturing Capability Data Integration]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/460/Phd-proposal-A-Semantic-Resolution-Framework-for-Manufacturing-Capability-Data-Integration</link>
  <description><![CDATA[Building flexible manufacturing supply chains requires interoperable and accurate manufacturing service capability (MSC) information of all supply chain participants. Today, MSC information, which is typically published either on the supplier’s web site or registered at an e-marketplace portal, has been shown to fall short of the interoperability and accuracy requirements. This issue can be addressed by annotating the MSC information using shared ontologies. However, ontology-based approach...]]></description>
  <dc:date>2013-05-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/458/A-Collaborative-Approach-to-Situational-Awareness-for-CyberSecurity">
  <title><![CDATA[A Collaborative Approach to Situational Awareness for CyberSecurity]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/458/A-Collaborative-Approach-to-Situational-Awareness-for-CyberSecurity</link>
  <description><![CDATA[Traditional intrusion detection and prevention systems (IDPSs) have well known limitations that decrease their utility against many kinds of attacks.  Current state-of-the-art IDPSs are point based solutions that perform a simple analysis of host or network data and then flag an alert.  Only known attacks whose signatures have been identified and stored in some form can be discovered by most of these systems.  They cannot detect attacks that use low-and-slow vectors.  Many times an attack is ...]]></description>
  <dc:date>2013-04-29</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/455/Text-and-Ontology-Driven-Clinical-Decision-Support-System">
  <title><![CDATA[Text and Ontology Driven Clinical Decision Support System]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/455/Text-and-Ontology-Driven-Clinical-Decision-Support-System</link>
  <description><![CDATA[This thesis discusses our ongoing research in the domain of text and ontology driven clinical decision support system. The proposed framework uses text analytics to extract clinical entities from electronic health records and semantic web analytics to generate a domain specific knowledge base (KB) of patients’ clinical facts. Clinical Rules expressed in the Semantic Web Language OWL are used to reason over the KB to infer additional facts about the patient. The KB is then queried to provide...]]></description>
  <dc:date>2013-04-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/393/PowerRelations-A-Question-Answering-System-for-DBPedia">
  <title><![CDATA[PowerRelations: A Question Answering System for DBPedia]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/393/PowerRelations-A-Question-Answering-System-for-DBPedia</link>
  <description><![CDATA[Large amounts of structured and semi-structured semantic data are available on the Web. A well-known example is DBpedia, which extracts data from Wikipedia, encodes it in the Semantic Web language RDF, and stores it in a triplestore. Although a formal query language, SPARQL, is available for accessing such data, it remains challenging for users to query the knowledge unless they are familiar with SPARQL and the particular ontologies used. We have developed an intuitive system for users to ex...]]></description>
  <dc:date>2011-04-26</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/391/Extracting-Information-about-Security-Vulnerabilities-from-Web-Text">
  <title><![CDATA[Extracting Information about Security Vulnerabilities from Web Text]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/391/Extracting-Information-about-Security-Vulnerabilities-from-Web-Text</link>
  <description><![CDATA[The Web has rapidly grown into a source for disseminating information related to computer security threats, vulnerabilities and cyber-attacks. We present initial work on developing a framework to detect and extract descriptions of vulnerabilities and attacks from Web text. Our prototype system uses Wikitology, a general purpose knowledge base based on Wikipedia, to extract concepts that describe specific vulnerabilities and attacks, map them to related concepts from DBpedia and generate mac...]]></description>
  <dc:date>2011-04-19</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/368/Text-Based-Similarity-Metrics-and-Deltas-for-Semantic-Web-Graphs">
  <title><![CDATA[Text Based Similarity Metrics and Deltas for Semantic Web Graphs]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/368/Text-Based-Similarity-Metrics-and-Deltas-for-Semantic-Web-Graphs</link>
  <description><![CDATA[Recognizing that two Semantic Web documents or graphs are similar and characterizing their differences is useful in many tasks, including retrieval, updating, version control and knowledge base editing. I will describe several text-based similarity metrics that characterize the relation between Semantic Web graphs and evaluate these metrics for three specific cases of similarity: similarity in classes and properties, similarity disregarding differences in base-URIs, and versioning relationshi...]]></description>
  <dc:date>2010-10-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/70/CoCoNet-Content-and-Context-Aware-Networking">
  <title><![CDATA[CoCoNet: Content and Context Aware Networking]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/70/CoCoNet-Content-and-Context-Aware-Networking</link>
  <description><![CDATA[The current Internet was originally designed to provide best-effort data
transport over a wired infrastructure with end hosts utilizing a layered
network stack to provide reliability, quality of service, security etc.
for user applications.  However, the proliferation of inelastic
applications, coupled with wide spread migration towards hybrid networks
utilizing wired and wireless links and the plethora of end host variants
ranging from cell phones to enterprise servers necessitates the...]]></description>
  <dc:date>2005-07-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/100/Text-and-Ontology-Driven-Clinical-Decision-Support-System">
  <title><![CDATA[Text and Ontology Driven Clinical Decision Support System]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/100/Text-and-Ontology-Driven-Clinical-Decision-Support-System</link>
  <description><![CDATA[In this work, we discuss our ongoing research in the domain of text and ontology driven clinical
decision support system. The proposed framework uses text analytics to extract clinical entities
from electronic health records and semantic web analytics to generate a domain specific
knowledge base (KB) of patients‟ clinical facts. Clinical Rules expressed in the Semantic Web
Language OWL are used to reason over the KB to infer additional facts about the patient. The
KB is then queried to...]]></description>
  <dc:date>2012-08-01</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/1051/A-Practical-Entity-Linking-System-for-Tables-in-Scientific-Literature">
  <title><![CDATA[A Practical Entity Linking System for Tables in Scientific Literature]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1051/A-Practical-Entity-Linking-System-for-Tables-in-Scientific-Literature</link>
  <description><![CDATA[Entity linking is an important step towards constructing knowledge graphs that facilitate advanced question answering over scientific documents—including the retrieval of relevant information included in tables within these documents. This paper introduces a general-purpose system for linking entities to items in the Wikidata knowledge base. It describes how we adapt this system for linking domain-specific entities, especially for those entities embedded within tables drawn from COVID-19-re...]]></description>
  <dc:date>2023-02-14</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/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/902/Affinity-Propagation-Initialisation-Based-Proximity-Clustering-For-Labeling-in-Natural-Language-Based-Big-Data-Systems">
  <title><![CDATA[Affinity Propagation Initialisation Based Proximity Clustering For Labeling in Natural Language Based Big Data Systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/902/Affinity-Propagation-Initialisation-Based-Proximity-Clustering-For-Labeling-in-Natural-Language-Based-Big-Data-Systems</link>
  <description><![CDATA[A key challenge for natural language based large text data is automatically extracting knowledge, in terms of entities and relations, embedded in it. State of the art relation extraction systems requires large amounts of labeled data, which is costly and very difficult, especially in industrial settings, due to time constraints of subject matter experts. Techniques like distant supervision require the availability of a related knowledge base, which is rarely possible. We have developed a nove...]]></description>
  <dc:date>2020-05-26</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/857/Automating-Class-Instance-Representational-Choices-in-Knowledge-Bases">
  <title><![CDATA[Automating Class/Instance Representational Choices in Knowledge Bases]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/857/Automating-Class-Instance-Representational-Choices-in-Knowledge-Bases</link>
  <description><![CDATA[We present a method for making decisions as to whether an entity in a knowledge base should be a class or an instance based on external evidence in the form of corresponding textual corpora such as Wikipedia articles. The approach, based on machine classification of the text, avoids the need for feature engineering and provides valuable guidance when building or refining large knowledge bases. The approach works well over different domains and outperforms a variety of other state-of-the-art a...]]></description>
  <dc:date>2018-10-31</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/841/KG-Cleaner-Identifying-and-Correcting-Errors-Produced-by-Information-Extraction-Systems">
  <title><![CDATA[KG Cleaner: Identifying and Correcting Errors Produced by Information Extraction Systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/841/KG-Cleaner-Identifying-and-Correcting-Errors-Produced-by-Information-Extraction-Systems</link>
  <description><![CDATA[KG Cleaner is a framework to identify and correct errors in data produced and delivered by an information extraction system. These tasks have been understudied and KG Cleaner is the first to address both. We introduce a multi-task model that jointly learns to predict if an extracted relation is credible and repair it if not. We evaluate our approach and other models as instance of our framework on two collections: a Wikidata corpus of nearly 700K facts and 5M fact-relevant sentences and a col...]]></description>
  <dc:date>2018-08-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/913/On-the-Integration-of-Inconsistent-Knowledge-with-Bayseian-Networks">
  <title><![CDATA[On the Integration of Inconsistent Knowledge with Bayseian Networks]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/913/On-the-Integration-of-Inconsistent-Knowledge-with-Bayseian-Networks</link>
  <description><![CDATA[Incorporating or integrating new knowledge into existing knowledge bases (KBs) is critical for developing and maintaining the reliability and accuracy thereof. This thesis focuses on integrating pieces of discrete probabilistic knowledge, represented as low dimensional distributions (also called constraints), into an existing Bayesian network (BN) where the probabilistic dependency relations among the variables in these constraints are inconsistent with those captured by the network structure...]]></description>
  <dc:date>2018-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/812/Automated-Knowledge-Extraction-from-the-Federal-Acquisition-Regulations-System-FARS-">
  <title><![CDATA[Automated Knowledge Extraction from the Federal Acquisition Regulations System (FARS)]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/812/Automated-Knowledge-Extraction-from-the-Federal-Acquisition-Regulations-System-FARS-</link>
  <description><![CDATA[With increasing regulation of Big Data, it is becoming essential for organizations to ensure compliance with various data protection standards. The Federal Acquisition Regulations System (FARS) within the Code of Federal Regulations (CFR) includes facts and rules for individuals and organizations seeking to do business with the US Federal government. Parsing and gathering knowledge from such lengthy regulation documents is currently done manually and is time and human intensive.Hence, develop...]]></description>
  <dc:date>2017-12-11</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/817/Participation-in-TAC-KBP-2017-Cold-Start-TEDL-and-Low-resource-EDL">
  <title><![CDATA[Participation in TAC KBP 2017: Cold Start TEDL and Low-resource EDL]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/817/Participation-in-TAC-KBP-2017-Cold-Start-TEDL-and-Low-resource-EDL</link>
  <description><![CDATA[The JHU HLTCOE participated in the Cold Start and the edl tasks of the 2017 Text Analysis Conference Knowledge Base Population evaluation.  For our sixth year of participation in Cold Start we continued our research with the kelvin system.  We submitted experimental variants that explore use of linking to Freebase across English and Chinese languages and add relations beyond those required by Cold Start.  This is our third year of participation in Tri-lingual EDL and first year for the EDL Pi...]]></description>
  <dc:date>2017-11-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/780/Cognitive-Assistance-for-Automating-the-Analysis-of-the-Federal-Acquisition-Regulations-System">
  <title><![CDATA[Cognitive Assistance for Automating the Analysis of the Federal Acquisition Regulations System]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/780/Cognitive-Assistance-for-Automating-the-Analysis-of-the-Federal-Acquisition-Regulations-System</link>
  <description><![CDATA[Government regulations are critical to understanding how to do business with a government entity and receive other beneﬁts. However, government regulations are also notoriously long and organized in ways that can be confusing for novice users. Developing cognitive assistance tools that remove some of the burden from human users is of potential beneﬁt to a variety of users. The volume of data found in United States federal government regulation suggests a multiple-step approach to process ...]]></description>
  <dc:date>2017-11-11</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/288/Creating-and-Exploiting-a-Web-of-Semantic-Data">
  <title><![CDATA[Creating and Exploiting a Web of Semantic Data]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/288/Creating-and-Exploiting-a-Web-of-Semantic-Data</link>
  <description><![CDATA[Twenty years ago Tim Berners-Lee proposed a distributed hypertext system based on standard Internet proto-cols. The Web that resulted fundamentally changed the ways we share information and services, both on the public Internet and within organizations. That original proposal contained the seeds of another effort that has not yet fully blossomed: a Semantic Web designed to enable computer programs to share and understand structured and semi-structured information easily. We will review the ev...]]></description>
  <dc:date>2010-01-24</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/369/From-Strings-to-Things-Populating-Knowledge-Bases-from-Text">
  <title><![CDATA[From Strings to Things: Populating Knowledge Bases from Text]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/369/From-Strings-to-Things-Populating-Knowledge-Bases-from-Text</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>2016-06-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/316/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/resource/html/id/316/Generating-Linked-Data-by-inferring-the-semantics-of-tables</link>
  <description><![CDATA[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. Early work in table interpretation in the field of document analysis and later on the Web, focused mainly on understanding and extracting tables from scanned documents and html web pages. Relatively little work has addressed the understan...]]></description>
  <dc:date>2011-05-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/64/Modeling-and-using-trust-and-provenance-in-the-Semantic-Web">
  <title><![CDATA[Modeling and using trust and provenance in the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/64/Modeling-and-using-trust-and-provenance-in-the-Semantic-Web</link>
  <description><![CDATA[This is Li Ding' proposal preview, and some parts are not finished yet. This proposal shows how to model trust and provenance to make the semantic web a useful real world knowledge base. It first positions trust and provenance in the big picture of semantic web research. Then some important reasearch problems along this line are listed with preliminary work.]]></description>
  <dc:date>2004-10-20</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/327/situational-awareness-for-cybersecurity">
  <title><![CDATA[situational awareness for cybersecurity]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/327/situational-awareness-for-cybersecurity</link>
  <description><![CDATA[We describe a current project    aimed at developing a situational awareness framework to (1) detect potential new vulnerabilities from Web descriptions and discussions, extract information and map to IDS knowledge base, (2) recognize potential attacks and intrusions in data from low level intrusion detection systems and map to IDS knowledge base, and (3) integrate and reason over results of (1) and (2) to identify actual attacks.]]></description>
  <dc:date>2011-10-21</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>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/356/Text-and-Ontology-Driven-Clinical-Decision-Support-System">
  <title><![CDATA[Text and Ontology Driven Clinical Decision Support System]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/356/Text-and-Ontology-Driven-Clinical-Decision-Support-System</link>
  <description><![CDATA[In this work, we discuss our ongoing research in the domain of text and ontology driven clinical
decision support system. The proposed framework uses text analytics to extract clinical entities
from electronic health records and semantic web analytics to generate a domain specific
knowledge base (KB) of patients‟ clinical facts. Clinical Rules expressed in the Semantic Web
Language OWL are used to reason over the KB to infer additional facts about the patient. The
KB is then queried to...]]></description>
  <dc:date>2013-05-31</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/300/Text-Based-Similarity-Metrics-and-Delta-for-Semantic-Web-Graphs">
  <title><![CDATA[Text Based Similarity Metrics and Delta for Semantic Web Graphs]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/300/Text-Based-Similarity-Metrics-and-Delta-for-Semantic-Web-Graphs</link>
  <description><![CDATA[Recognizing that two semantic web documents or graphs are similar, and characterizing their differences is useful in many tasks, including retrieval, updating, version control and knowledge base editing. We describe a number of text based similarity metrics that characterize the relation between semantic web graphs and evaluate these metrics for three specific cases of similarity that we have identified: similarity in classes and properties used while differing only in literal content, differ...]]></description>
  <dc:date>1999-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/371/UMBC-IOT-Android-client">
  <title><![CDATA[UMBC IOT Android client]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/371/UMBC-IOT-Android-client</link>
  <description><![CDATA[UMBC IoT Project Android Client
Install a latest version of the app from release list link from webpage below. In the current mode of deployment, the app will work, if you are near one of our beacons in the Information Technology and Engineering building at UMBC. If you are near one of them, you will be able to query our Knowledge Base using voice commands or through text input. It's an AMA app, enabling you to ask queries about any organization (for example UMBC).]]></description>
  <dc:date>2017-04-04</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/261/WIkipedia-as-an-ontology">
  <title><![CDATA[WIkipedia as an ontology]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/261/WIkipedia-as-an-ontology</link>
  <description><![CDATA[There is a lot of 'semantic information' on the Web, the vast
majority of which is encoded as human language text. This is
especially true for content found on the social web, consisting
of blogs, Wikis, forums, and many other social media systems. One
way to accelerate the realization of the Semantic Web's vision of
a web of machine understandable data is to extract semantic
information from this text and publish it in structured or
semi-structured forms (e.g., RDF) using appropriate ...]]></description>
  <dc:date>2009-03-24</dc:date>
 </item>
</rdf:RDF>
