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      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/473/Taming-Wild-Big-Data"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/469/Infoboxer-Using-Statistical-and-Semantic-Knowledge-to-Help-Create-Wikipedia-Infoboxes"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/967/Query-Expansion-for-Cross-Language-Question-Re-Ranking"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/722/UCO-A-Unified-Cybersecurity-Ontology"/>
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 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/473/Taming-Wild-Big-Data">
  <title><![CDATA[Taming Wild Big Data]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/473/Taming-Wild-Big-Data</link>
  <description><![CDATA[In this week's Ebiquity meeting, Jennifer Sleeman will talk about "Taming Wild Big Data".

Wild Big Data is data that is hard to extract, understand, and use due to its heterogeneous nature and volume. It typically comes without a schema, is obtained from multiple sources and provides a challenge for information extraction and integration. We describe a way to subduing Wild Big Data that uses techniques and resources that are popular for processing natural language text. The approach is...]]></description>
  <dc:date>2014-11-12</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/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/417/Semantic-Web-Meetup">
  <title><![CDATA[Semantic Web Meetup]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/417/Semantic-Web-Meetup</link>
  <description><![CDATA[The UMBC Ebiquity Lab is hosting the November meeting of the Lotico Central Maryland Semantic Web Meetup from 6:00-8:00 pm in room 456 of the ITE building (directions).  All are welcome.  If you want to attend, please join the  Central MD Semantic Web Meetup group and RSVP.  The meeting will start with a pizza social from 6:00pm to 6:45pm and then continue with a series of short presentations of current Semantic Web research being done in our lab.

  Tim Finin: introduction and overview

...]]></description>
  <dc:date>2011-11-15</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/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/event/html/id/216/Linked-Data">
  <title><![CDATA[Linked Data]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/216/Linked-Data</link>
  <description><![CDATA[Linked Data refers to a collection of best practices for publishing data on the semantic web. It is also, in part, a re-branding of the semantic web itself, with less emphasis on semantics, and more on RDF linkages amongst data sources. Also heavily emphasized is the proper role of web architecture (http requests and responses; 303 redirects; etc.), and the distinction between information resources (those that physically reside on the web), and non-information resources (those that exist in t...]]></description>
  <dc:date>2007-10-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/103/Automatic-Interpretation-of-Log-Files">
  <title><![CDATA[Automatic Interpretation of Log Files]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/103/Automatic-Interpretation-of-Log-Files</link>
  <description><![CDATA[Log files comprise of different events happening in various applications, operating systems and even in network devices. Originally they were used to record information for diagnostic and debugging purposes. Nowadays, logs are also used to track events which can be used in auditing and forensics in case of malicious activities or systems attacks. Various softwares like intrusion detection systems, webservers, anti-virus and anti-malware systems, firewalls and network devices generate logs wit...]]></description>
  <dc:date>2013-08-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/104/Automatic-Interpretation-of-Log-Files">
  <title><![CDATA[Automatic Interpretation of Log Files]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/104/Automatic-Interpretation-of-Log-Files</link>
  <description><![CDATA[Log files comprise of different events happening in various applications, operating systems and even in network devices. Originally they were used to record information for diagnostic and debugging purposes. Nowadays, logs are also used to track events which can be used in auditing and forensics in case of malicious activities or systems attacks. Various softwares like intrusion detection systems, webservers, anti-virus and anti-malware systems, firewalls and network devices generate logs wit...]]></description>
  <dc:date>2013-08-01</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/paper/html/id/957/Fine-and-Ultra-Fine-Entity-Type-Embeddings-for-Question-Answering">
  <title><![CDATA[Fine and Ultra-Fine Entity Type Embeddings  for Question Answering]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/957/Fine-and-Ultra-Fine-Entity-Type-Embeddings-for-Question-Answering</link>
  <description><![CDATA[We describe our system for the SeMantic AnsweR (SMART) Type prediction task 2020 for both the DBpedia and Wikidata Question Answer Type datasets. The SMART task challenge introduced fine-grained and ultra-fine entity typing to question answering by releasing two datasets for question classification using DBpedia and Wikidata classes. We propose a flexible framework for both entity types using paragraph vectors and word embeddings to obtain high-quality contextualized question representations....]]></description>
  <dc:date>2020-11-02</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/967/Query-Expansion-for-Cross-Language-Question-Re-Ranking">
  <title><![CDATA[Query Expansion for Cross-Language Question Re-Ranking]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/967/Query-Expansion-for-Cross-Language-Question-Re-Ranking</link>
  <description><![CDATA[Community question-answering (CQA) platforms have become very popular forums for asking and answering questions daily.  While these forums are rich repositories of community knowledge, they present challenges for finding relevant answers and similar questions, due to the open-ended nature of informal discussions.  Further, if the platform allows questions and answers in multiple languages, we are faced with the additional challenge of matching cross-lingual information. In this work, we focus...]]></description>
  <dc:date>2019-04-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/749/Semantic-Interpretation-of-Structured-Log-Files">
  <title><![CDATA[Semantic Interpretation of Structured Log Files]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/749/Semantic-Interpretation-of-Structured-Log-Files</link>
  <description><![CDATA[Data from computer log files record traces of events involving user activity, applications, system software and network traffic. Logs are usually intended for diagnostic and debugging purposes, but their data can be extremely useful in system audits and forensic investigations. Logs created by intrusion detection systems, web servers, anti-virus and anti-malware systems, firewalls and network devices have information that can reconstruct the activities of malware or a malicious agent, help pl...]]></description>
  <dc:date>2016-07-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/722/UCO-A-Unified-Cybersecurity-Ontology">
  <title><![CDATA[UCO: A Unified Cybersecurity Ontology]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/722/UCO-A-Unified-Cybersecurity-Ontology</link>
  <description><![CDATA[In this paper, we describe the Unified Cybersecurity Ontology (UCO) that is intended to support information integration and cyber situational awareness in cybersecurity systems. The ontology integrates heterogeneous data and knowledge schemas from different cybersecurity systems, as well as the most commonly used cybersecurity standards for information sharing and exchange. The UCO ontology has also been mapped to a number of existing cybersecurity ontologies as well as concepts in the Linked...]]></description>
  <dc:date>2016-02-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/720/Supporting-Situationally-Aware-Cybersecurity-Systems">
  <title><![CDATA[Supporting Situationally Aware Cybersecurity Systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/720/Supporting-Situationally-Aware-Cybersecurity-Systems</link>
  <description><![CDATA[In this report, we describe the Unified Cyber Security ontology (UCO) to support situational awareness in cyber security systems. The ontology is an effort to incorporate
and integrate heterogeneous information available from different cyber security systems and most commonly used cyber security standards for information sharing and exchange. The ontology has also been mapped to a number of existing cyber security
ontologies as well as concepts in the Linked Open Data cloud. Similar to DBpe...]]></description>
  <dc:date>2015-09-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/721/Semantic-Interpretation-of-Structured-Log-Files">
  <title><![CDATA[Semantic Interpretation of Structured Log Files]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/721/Semantic-Interpretation-of-Structured-Log-Files</link>
  <description><![CDATA[Log files comprise a record of different events happening in various applications, operating systems and even in network devices. Originally they were used to record in- formation for diagnostic and debugging purposes. Nowadays, logs are also used to track events which can be used in auditing and forensics in case of malicious activities or sys- tems attacks. Various softwares like intrusion detection systems, webservers, anti-virus and anti-malware systems, firewalls and network devices gene...]]></description>
  <dc:date>2015-08-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/701/Querying-RDF-Data-with-Text-Annotated-Graphs">
  <title><![CDATA[Querying RDF Data with Text Annotated  Graphs]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/701/Querying-RDF-Data-with-Text-Annotated-Graphs</link>
  <description><![CDATA[Scientists and casual users need better ways to query RDF databases or Linked Open Data. Using the SPARQL query language requires not only mastering its syntax and semantics but also understanding the RDF data model, the ontology used, and URIs for entities of interest. Natural language query systems are a powerful approach, but current techniques are brittle in addressing the ambiguity and complexity of natural language and require expensive labor to supply the extensive domain knowledge the...]]></description>
  <dc:date>2015-06-29</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/665/Entity-Type-Recognition-for-Heterogeneous-Semantic-Graphs">
  <title><![CDATA[Entity Type Recognition for Heterogeneous Semantic Graphs]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/665/Entity-Type-Recognition-for-Heterogeneous-Semantic-Graphs</link>
  <description><![CDATA[We describe an approach for identifying fine-grained entity types in heterogeneous data graphs that is effective for unstructured data or when the underlying ontologies or semantic schemas are unknown. Identifying fine-grained entity types, rather than a few high-level types, supports coreference resolution in heterogeneous graphs by reducing the number of possible coreference relations that must be considered.  Big Data problems that involve integrating data from multiple sources can benefit...]]></description>
  <dc:date>2015-03-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/672/Taming-Wild-Big-Data">
  <title><![CDATA[Taming Wild Big Data]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/672/Taming-Wild-Big-Data</link>
  <description><![CDATA[Wild Big Data is data that is hard to extract, understand, and use due to its heterogeneous nature and volume. It typically comes without a schema, is obtained from multiple sources, and provides a challenge for information extraction and integration. We describe a way to subdue Wild Big Data that uses techniques and resources that are popular for processing natural language text. The approach is applicable to data that is presented as a graph of objects and relations between them and to tabu...]]></description>
  <dc:date>2014-11-13</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/668/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/paper/html/id/668/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, making it harder to f...]]></description>
  <dc:date>2014-10-21</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/331/GoRelations-an-Intuitive-Query-System-for-DBPedia-and-LOD-">
  <title><![CDATA[GoRelations: an Intuitive Query System for DBPedia (and LOD)]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/331/GoRelations-an-Intuitive-Query-System-for-DBPedia-and-LOD-</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 annotat...]]></description>
  <dc:date>2011-11-15</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/307/Using-linked-data-to-interpret-tables">
  <title><![CDATA[Using linked data to interpret tables]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/307/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/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>
