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	This ontology document is licensed under the Creative Commons
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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=similarity+measure">
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  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=similarity+measure]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for similarity measure]]></description>
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      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/466/PhD-defense-Lushan-Han-Schema-Free-Querying-of-Semantic-Data"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/397/Community-Detection-in-Twitter"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/344/A-New-Approach-for-Automatic-Thesaurus-Generation"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/742/Clinico-genomic-Data-Analytics-for-Precision-Diagnosis-and-Disease-Management"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/658/Schema-Free-Querying-of-Semantic-Data"/>
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      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/601/A-Supplier-Discovery-Framework-For-Effective-And-Efficient-Configuration-Of-A-Supply-Chain"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/558/Improving-Word-Similarity-by-Augmenting-PMI-with-Estimates-of-Word-Polysemy"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/555/Community-Detection-in-Twitter"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/531/A-semantic-similarity-analysis-for-data-mappings-between-heterogeneous-XML-schemas"/>
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 <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/397/Community-Detection-in-Twitter">
  <title><![CDATA[Community Detection in Twitter]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/397/Community-Detection-in-Twitter</link>
  <description><![CDATA[Mohit Kewalramani will defend his MS thesis titled "Community Detection in Twitter".
 
Twitter has evolved into a source of social, political and real time information in addition to being a means of mass-communication and marketing. Monitoring and analyzing information on Twitter can lead to invaluable insights, which might otherwise be hard to get using conventional media resources. An important task in analyzing highly networked information sources like twitter is to identify communities...]]></description>
  <dc:date>2011-05-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/344/A-New-Approach-for-Automatic-Thesaurus-Generation">
  <title><![CDATA[A New Approach for Automatic Thesaurus Generation]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/344/A-New-Approach-for-Automatic-Thesaurus-Generation</link>
  <description><![CDATA[Distributional similarity has long been used to determine  how similar two words are and has been used in automatic thesaurus generation. Such distribution similarity measures, however, do not always work well for finding synonyms in a text corpus because synonyms may not necessarily have the most similar contexts. We have developed a novel alternative approach in automatic thesaurus generation using pointwise mutual information (PMI) and by exploiting co-occurrence patterns of synonyms, whic...]]></description>
  <dc:date>2010-05-04</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/915/Deep-Representation-of-Lyrical-Style-and-Semantics-for-Music-Recommendation">
  <title><![CDATA[Deep Representation of Lyrical Style and Semantics for Music Recommendation]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/915/Deep-Representation-of-Lyrical-Style-and-Semantics-for-Music-Recommendation</link>
  <description><![CDATA[In an increasingly mobile and connected world, digital music consumption has rapidly increased. More recently, faster and cheaper mobile bandwidth has given the average mobile user the potential to access large troves of music through streaming services like Spotify and Google Music that boast catalogs with tens of millions of songs. At this scale, effective music recommendation is an important part of user experience and music discovery. Collaborative filtering (CF), a popular technique used...]]></description>
  <dc:date>2017-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/742/Clinico-genomic-Data-Analytics-for-Precision-Diagnosis-and-Disease-Management">
  <title><![CDATA[Clinico-genomic Data Analytics for Precision Diagnosis and Disease Management]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/742/Clinico-genomic-Data-Analytics-for-Precision-Diagnosis-and-Disease-Management</link>
  <description><![CDATA[Patient data can be present in clinical notes, lab results, genomic data sources, environmental and geospatial data sources and tissue banks to name a few. A holistic view of the patient's health can be achieved when relevant data from multiple heterogeneous sources are extracted and analyzed in a personalized manner. Moreover, comparative analysis of patients can be performed when multiple patient records are viewed across these heterogeneous data sources. To address this need, we propose cl...]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/658/Schema-Free-Querying-of-Semantic-Data">
  <title><![CDATA[Schema Free Querying of Semantic Data]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/658/Schema-Free-Querying-of-Semantic-Data</link>
  <description><![CDATA[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. Since such interfaces allow users to freely query data without understanding its schema, knowing how to refer to objects, or mastering the appropriate formal query language, we call them as schema-free query interfaces. Schema-free query interface systems address a fundamental problem in NLP, Database and AI - to bridge the user conceptual ...]]></description>
  <dc:date>2014-08-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/577/Improving-Word-Similarity-by-Augmenting-PMI-with-Estimates-of-Word-Polysemy">
  <title><![CDATA[Improving Word Similarity by Augmenting PMI with Estimates of Word Polysemy]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/577/Improving-Word-Similarity-by-Augmenting-PMI-with-Estimates-of-Word-Polysemy</link>
  <description><![CDATA[Pointwise mutual information (PMI) is a widely used word similarity measure, but it lacks a clear explanation of how it works. We explore how PMI differs from distributional similarity, and we introduce a novel metric, PMImax, that augments PMI with information about a word's number of senses. The coefficients of PMImax are determined empirically by maximizing a utility function based on the performance of automatic thesaurus generation. We show that it outperforms traditional PMI in the appl...]]></description>
  <dc:date>2013-06-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/601/A-Supplier-Discovery-Framework-For-Effective-And-Efficient-Configuration-Of-A-Supply-Chain">
  <title><![CDATA[A Supplier Discovery Framework For Effective And Efficient Configuration Of A Supply Chain]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/601/A-Supplier-Discovery-Framework-For-Effective-And-Efficient-Configuration-Of-A-Supply-Chain</link>
  <description><![CDATA[A supplier registry can play a central role in configuring a global supply chain for service-oriented enterprise integration by
providing an open platform for publishing and discovering suppliers distributed over Internet. The availability of correct 
classification schemes used to organize suppliers based on their capability descriptions is the key to building an effective 
registry. This paper discusses the clustering-based construction of classification schemes from existing  capability...]]></description>
  <dc:date>2011-11-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/558/Improving-Word-Similarity-by-Augmenting-PMI-with-Estimates-of-Word-Polysemy">
  <title><![CDATA[Improving Word Similarity by Augmenting PMI with Estimates of Word Polysemy]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/558/Improving-Word-Similarity-by-Augmenting-PMI-with-Estimates-of-Word-Polysemy</link>
  <description><![CDATA[Although pointwise mutual information (PMI) has become a commonly used word similarity measure, a clear understanding of how it works has been lacking.  In this paper we explore how PMI differs from distributional similarity, and we introduce a novel metric, PMImax, that augments PMI with information about a word's number of senses.  The coefficients of PMImax are determined empirically by maximizing a utility function based on the performance of automatic thesaurus generation.  We show that ...]]></description>
  <dc:date>2011-06-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/555/Community-Detection-in-Twitter">
  <title><![CDATA[Community Detection in Twitter]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/555/Community-Detection-in-Twitter</link>
  <description><![CDATA[Twitter has recently evolved into a source of social, political and real time information in addition to being a means of mass-communication and marketing. Monitoring
and analyzing information on Twitter can lead to invaluable insights, which might otherwise
be hard to get using conventional media resources. An important task in analyzing highly networked information sources like twitter is to identify communities that are formed. A
community on twitter can be defined as a set of users tha...]]></description>
  <dc:date>2011-05-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/531/A-semantic-similarity-analysis-for-data-mappings-between-heterogeneous-XML-schemas">
  <title><![CDATA[A semantic similarity analysis for data mappings between heterogeneous XML schemas]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/531/A-semantic-similarity-analysis-for-data-mappings-between-heterogeneous-XML-schemas</link>
  <description><![CDATA[One of the most critical steps to integrating heterogeneous e-Business applications using different XML schemas is schema mapping, which is known to be costly and error-prone. Past research on schema mapping has not made full use of semantic information imbedded in the hierarchical structure of the XML schema. In this chapter, we investigate the existing schema mapping approaches and propose an innovative semantic similarity analysis approach to facilitate XML schema mapping, merging and reus...]]></description>
  <dc:date>2010-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/488/Semantic-Similarity-Analysis-of-XML-Schema-using-Grid-Computing">
  <title><![CDATA[Semantic Similarity Analysis of XML Schema using Grid Computing]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/488/Semantic-Similarity-Analysis-of-XML-Schema-using-Grid-Computing</link>
  <description><![CDATA[A growing number of e-businesses have been using XML schemas in recent years. Schema mapping now plays a crucial role in integrating heterogeneous ebusiness applications. Since large-scale XML schema mapping using complex and hybrid similarity measures requires significant amount of processing time, a sophisticated similarity analysis algorithm is needed to handle its complexity and performance. In this paper, we focus on designing a service-oriented architecture (SoA) for schema mapping, bas...]]></description>
  <dc:date>2009-08-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/420/A-Layered-Approach-to-Semantic-Similarity-Analysis-of-XML-Schemas">
  <title><![CDATA[A Layered Approach to Semantic Similarity Analysis of XML Schemas]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/420/A-Layered-Approach-to-Semantic-Similarity-Analysis-of-XML-Schemas</link>
  <description><![CDATA[One of the most critical steps to integrating heterogeneous
e-Business applications using different XML schemas
is schema mapping, which is known to be costly and
error-prone. Past research on schema mapping has not
fully utilized semantic information in the XML schemas.
In this paper, we propose a semantic similarity analysis
approach to facilitate XML schema mapping, merging
and reuse. Several key innovations are introduced to better
utilize available semantic information. These inn...]]></description>
  <dc:date>2008-07-13</dc:date>
 </item>
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