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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=entity+linking">
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  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=entity+linking]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for entity linking]]></description>
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    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/478/Topic-Modeling-for-RDF-Graphs"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/439/Cluster-based-Instance-Consolidation-For-Subsequent-Matching"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/420/Masters-Thesis-Research-Update-Anurag-Dibjyajyoti-and-Sumit"/>
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      <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/360/Using-linked-data-to-interpret-tables"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/351/T2LD-An-automatic-framework-for-extracting-interpreting-and-representing-tables-as-linked-data"/>
      <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/1028/Recognizing-and-Extracting-Cybersecurity-Entities-from-Text"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/884/Improving-Neural-Named-Entity-Recognition-with-Gazetteers"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/730/HLTCOE-Participation-in-TAC-KBP-2015-Cold-Start-and-TEDL"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/714/Topic-Modeling-for-RDF-Graphs"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/637/HLTCOE-Participation-at-TAC-2013"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/603/Cluster-based-Instance-Consolidation-For-Subsequent-Matching"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/616/HLTCOE-Participation-at-TAC-2012-Entity-Linking-and-Cold-Start-Knowledge-Base-Construction"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/596/A-Domain-Independent-Framework-for-Extracting-Linked-Semantic-Data-from-Tables"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/592/Evaluating-the-Quality-of-a-Knowledge-Base-Populated-from-Text"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/316/Generating-Linked-Data-by-inferring-the-semantics-of-tables"/>
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/478/Topic-Modeling-for-RDF-Graphs">
  <title><![CDATA[Topic Modeling for RDF Graphs]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/478/Topic-Modeling-for-RDF-Graphs</link>
  <description><![CDATA[Topic models are widely used to thematically describe a collection of
text documents and have become an important technique for systems that
measure document similarity for classification, clustering,
segmentation, entity linking and more.  While they have been applied
to some non-text domains, their use for semi-structured graph data,
such as RDF, has been less explored.  We present a framework for
applying topic modeling to RDF graph data and describe how it can be
used in a number o...]]></description>
  <dc:date>2015-09-21</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/439/Cluster-based-Instance-Consolidation-For-Subsequent-Matching">
  <title><![CDATA[Cluster-based Instance Consolidation For Subsequent Matching]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/439/Cluster-based-Instance-Consolidation-For-Subsequent-Matching</link>
  <description><![CDATA[In this week's lab meeting Jennifer Sleaman will present "Cluster-based Instance Consolidation For Subsequent Matching"

Instance consolidation is a way to merge instances that are thought to be the same or closely related that can be used to support coreference resolution and entity linking. For Semantic Web data, consolidating instances can be as simple as relating instances using owl:sameAs, as is the case in linked data, or merging instances that could then be used to populate or enrich...]]></description>
  <dc:date>2012-10-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/420/Masters-Thesis-Research-Update-Anurag-Dibjyajyoti-and-Sumit">
  <title><![CDATA[Masters Thesis Research Update - Anurag, Dibjyajyoti and Sumit]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/420/Masters-Thesis-Research-Update-Anurag-Dibjyajyoti-and-Sumit</link>
  <description><![CDATA[In this week's lab meeting, Anurag Korde, Dibyajyoti Ghosh and Sumit More will give an update on how their Masters thesis research is progressing. 

Anurag will talk about "Entity Linking and Disambiguation for Smartphone platforms". With increasing number of social networks, smartphones and applications there is a need of creating a framework for information integration across social networks and applications and create an unified record for each person/entity. The problem in information i...]]></description>
  <dc:date>2011-12-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/413/Masters-Thesis-Research-Proposal-Entity-Linking-and-Disambiguation-for-Smartphone-platforms">
  <title><![CDATA[Masters Thesis Research Proposal : Entity Linking and Disambiguation for Smartphone platforms]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/413/Masters-Thesis-Research-Proposal-Entity-Linking-and-Disambiguation-for-Smartphone-platforms</link>
  <description><![CDATA[With increasing number of social networks, smartphones and applications there is a need of creating a framework for information integration across social networks and applications and create an unified record for each person/entity. The problem in information integration is that of entity disambiguation. It determines whether two objects in an ontology refer to same real world object. This will enable system to learn a large amount of contextual information. I will be extending]]></description>
  <dc:date>2011-10-11</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/360/Using-linked-data-to-interpret-tables">
  <title><![CDATA[Using linked data to interpret tables]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/360/Using-linked-data-to-interpret-tables</link>
  <description><![CDATA[Vast amount of information is available in structured forms like spreadsheets, database relations, and tables found in documents and on the Web. In today’s talk I will describe an approach that uses linked data to interpret such tables and associate their components with nodes in a reference linked data collection. Our proposed framework assigns a class (i.e. type) to table columns, links table cells to entities, and inferred relations between columns to properties. The resulting interpreta...]]></description>
  <dc:date>2010-09-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/351/T2LD-An-automatic-framework-for-extracting-interpreting-and-representing-tables-as-linked-data">
  <title><![CDATA[T2LD – An automatic framework for extracting,            interpreting and representing tables as linked data]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/351/T2LD-An-automatic-framework-for-extracting-interpreting-and-representing-tables-as-linked-data</link>
  <description><![CDATA[MS Thesis Defense


We present an automatic framework for extracting, interpreting and
generating linked data from tables. In the process of representing
tables as linked data, we assign every column header a class label
from an appropriate ontology, link table cells (if appropriate) to an
entity from the Linked Open Data cloud and identify relations between
various columns in the table, which helps us to build an overall
interpretation of the table. Using the limited evidence provid...]]></description>
  <dc:date>2010-06-29</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/1028/Recognizing-and-Extracting-Cybersecurity-Entities-from-Text">
  <title><![CDATA[Recognizing and Extracting Cybersecurity Entities from Text]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1028/Recognizing-and-Extracting-Cybersecurity-Entities-from-Text</link>
  <description><![CDATA[Cyber Threat Intelligence (CTI) is information describing threat vectors, vulnerabilities, and attacks and is often used as training data for AI-based cyber defense systems such as Cybersecurity Knowledge Graphs (CKG). There is a strong need to develop community-accessible datasets to train existing AI-based cybersecurity pipelines to efficiently and accurately extract meaningful insights from CTI. We have created an initial unstructured CTI corpus from a variety of open sources that we are u...]]></description>
  <dc:date>2022-07-17</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/884/Improving-Neural-Named-Entity-Recognition-with-Gazetteers">
  <title><![CDATA[Improving Neural Named Entity Recognition with Gazetteers]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/884/Improving-Neural-Named-Entity-Recognition-with-Gazetteers</link>
  <description><![CDATA[The goal of this work is to improve the performance of a neural named entity recognition system by adding input features that indicate a word is part of a name included in a gazetteer. This article describes how to generate gazetteers from the Wikidata knowledge graph as well as how to integrate the information into a neural NER system. Experiments reveal that the approach yields performance gains in two distinct languages: a high-resource, word-based language, English, and a high-resource, c...]]></description>
  <dc:date>2020-03-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/730/HLTCOE-Participation-in-TAC-KBP-2015-Cold-Start-and-TEDL">
  <title><![CDATA[HLTCOE Participation in TAC KBP 2015: Cold Start and TEDL]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/730/HLTCOE-Participation-in-TAC-KBP-2015-Cold-Start-and-TEDL</link>
  <description><![CDATA[The JHU HLTCOE participated in the Cold Start and the Trilingual Entity Linking and Discovery tasks of the 2015 Text Analysis Conference Knowledge Base Population evaluation. For our fourth 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 and adding additional relations.  This is our first year of participation in EDL. We used KELVIN in three runs and experimented with an alternate ...]]></description>
  <dc:date>2015-11-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/714/Topic-Modeling-for-RDF-Graphs">
  <title><![CDATA[Topic Modeling for RDF Graphs]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/714/Topic-Modeling-for-RDF-Graphs</link>
  <description><![CDATA[Topic models are widely used to thematically describe a collection of text documents and have become an important technique for systems that measure document similarity for classification, clustering, segmentation, entity linking, and more.  While they have been applied to some non-text domains, their use for semi-structured graph data, such as RDF, has been less explored.  We present a framework for applying topic modeling to RDF graph data and describe how it can be used in a number of link...]]></description>
  <dc:date>2015-10-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/637/HLTCOE-Participation-at-TAC-2013">
  <title><![CDATA[HLTCOE Participation at TAC 2013]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/637/HLTCOE-Participation-at-TAC-2013</link>
  <description><![CDATA[The JHU HLTCOE participated in the Entity Linking and Cold Start Knowledge Base tasks in this year’s Text Analysis Conference Knowledge Base Population evaluation.  We have previously participated in TAC-KBP evaluations in 2009, 2010, 2011, and 2012. Our primary focus this year was on the Cold Start task; improvements to our existing KELVIN system included consolidating slot values for an entity, removal of suspect intra-document conference chains, streamlined cross-document entity corefere...]]></description>
  <dc:date>2013-11-18</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/603/Cluster-based-Instance-Consolidation-For-Subsequent-Matching">
  <title><![CDATA[Cluster-based Instance Consolidation For Subsequent Matching]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/603/Cluster-based-Instance-Consolidation-For-Subsequent-Matching</link>
  <description><![CDATA[Instance consolidation is a way to merge instances that are thought to be the same or closely related that can be used to support coreference resolution and entity linking. For Semantic Web data, consolidating instances can be as simple as relating instances using owl:sameAs, as is the case in linked data, or merging instances that could then be used to populate or enrich a knowledge model. In many applications, systems process data incrementally over time and as new data is processed, the st...]]></description>
  <dc:date>2012-11-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/616/HLTCOE-Participation-at-TAC-2012-Entity-Linking-and-Cold-Start-Knowledge-Base-Construction">
  <title><![CDATA[HLTCOE Participation at TAC 2012: Entity Linking and Cold Start Knowledge Base Construction]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/616/HLTCOE-Participation-at-TAC-2012-Entity-Linking-and-Cold-Start-Knowledge-Base-Construction</link>
  <description><![CDATA[Our team from the JHU HLTCOE participated in the Entity Linking and Cold Start Knowledge Base tasks in this year’s Text Analysis Conference Knowledge Base Population evaluation. We have previously participated in TAC-KBP entity linking evaluations in 2009, 2010, and 2011. This year we developed two new systems: CALE (Context Aware Linker of Entities) and KELVIN (Knowledge Extraction, Linking, Validation, and INference) to support our research for this year’s exciting tasks.]]></description>
  <dc:date>2012-11-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/596/A-Domain-Independent-Framework-for-Extracting-Linked-Semantic-Data-from-Tables">
  <title><![CDATA[A Domain Independent Framework for Extracting Linked Semantic Data from Tables]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/596/A-Domain-Independent-Framework-for-Extracting-Linked-Semantic-Data-from-Tables</link>
  <description><![CDATA[Vast amounts of information is encoded in tables found in documents, on the Web, and in spreadsheets or databases. Integrating or searching over this information benefits from understanding its intended meaning and making it explicit in a semantic representation language like RDF.  Most current approaches to generating Semantic Web representations from tables require human input to create schemas and often result in graphs that do not follow best practices for linked data.  Evidence for a tab...]]></description>
  <dc:date>2012-07-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/592/Evaluating-the-Quality-of-a-Knowledge-Base-Populated-from-Text">
  <title><![CDATA[Evaluating the Quality of a Knowledge Base Populated from Text]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/592/Evaluating-the-Quality-of-a-Knowledge-Base-Populated-from-Text</link>
  <description><![CDATA[The steady progress of information extraction systems has been helped by sound methodologies for evaluating their performance in controlled experiments.  Annual events like MUC, ACE and TAC have developed evaluation approaches enabling researchers to score and rank their systems relative to reference results.  Yet these evaluations have only assessed component technologies needed by a knowledge base population system; none has required the construction of a knowledge base that is then evaluat...]]></description>
  <dc:date>2012-06-07</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>
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