<?xml version="1.0" encoding="UTF-8" ?>
<rdf:RDF
 xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
 xmlns="http://purl.org/rss/1.0/"
 xmlns:dc="http://purl.org/dc/elements/1.1/"
 xmlns:cc="http://web.resource.org/cc/"
 >
<!--
  This ontology document is licensed under the Creative Commons
  Attribution License. To view a copy of this license, visit
  http://creativecommons.org/licenses/by/2.0/ or send a letter to
  Creative Commons, 559 Nathan Abbott Way, Stanford, California
  94305, USA.
-->
 <channel rdf:about="http://ebiquity.umbc.edu/tag/natural language processing/">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <image rdf:resource="http://ebiquity.umbc.edu/img/logo.jpg" />  <title><![CDATA[RSS Tag Search]]></title>
  <link>http://ebiquity.umbc.edu/tag/natural language processing/</link>
  <description><![CDATA[RSS Tag Search]]></description>
  <items>
   <rdf:Seq>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/460/Improving-Binary-Classification-on-Text-Problems-using-Differential-Word-Features"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/448/Delta-TFIDF-An-Improved-Feature-Space-for-Sentiment-Analysis"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/431/Using-Wikitology-for-Cross-Document-Entity-Coreference-Resolution"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/423/Knowledge-Base-Evaluation-for-Semantic-Knowledge-Discovery"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/428/An-Investigation-of-Linguistic-Information-for-Speech-Recognition-Error-Detection"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/388/OWL-as-a-Target-for-Information-Extraction-Systems-"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/328/Using-a-Natural-Language-Understanding-System-to-Generate-Semantic-Web-Content"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/301/SemNews-A-Semantic-News-Framework"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/260/Text-understanding-agents-and-the-Semantic-Web"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/261/Integrating-Language-Understanding-Agents-Into-the-Semantic-Web"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/114/The-Integrality-of-Speech-in-Multimodal-Interfaces"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/337/The-Kernel-Natural-Language-Processing-System"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/287/Modeling-the-user-in-natural-language-systems"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/347/Natural-language-interactions-with-artificial-experts"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/285/The-Semantic-Interpretation-of-Nominal-Compounds"/>
    <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/344/Semantic-Interpretation-of-Compound-Nominals-"/>
    <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/156/Integrating-Language-Understanding-Agents-into-the-Semantic-Web"/>
    <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/250/Wikitology-Wikipedia-as-an-ontology"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/319/Generic-knowledge-acquisition-and-representation"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/282/When-is-a-Translation-not-a-Translation-"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/256/Information-Extraction-via-Automatic-Generation-of-Semantic-Classifiers"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/252/Wikitology-Wikipedia-as-an-ontology-"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/249/Using-Automatic-Word-Sense-Discrimination-to-generate-a-Semantic-Lexicon"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/246/Grammatical-Inference-Some-of-the-Questions-Out-There"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/210/When-Will-Computers-Understand-Shakespeare-b-font-color-red-CANCELED-9-10-font-b-"/>
    <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/119/Integrating-Language-Understanding-Agents-Into-the-Semantic-Web"/>
   </rdf:Seq>
  </items>
 </channel>
 <image rdf:about="http://ebiquity.umbc.edu/img/logo.jpg">
  <title>UMBC ebiquity research group</title>
  <link>http://ebiquity.umbc.edu</link>
  <url>http://ebiquity.umbc.edu/img/logo.jpg</url>
 </image>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/460/Improving-Binary-Classification-on-Text-Problems-using-Differential-Word-Features">
  <title><![CDATA[Improving Binary Classification on Text Problems using Differential Word Features]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/460/Improving-Binary-Classification-on-Text-Problems-using-Differential-Word-Features</link>
  <description><![CDATA[We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of problems. The most common text classification approach uses a document's ngrams (words and short phrases) as its features and assigns feature values equal to their frequency or TFIDF score relative to the training corpus. Our approach uses values computed as the product of an ngram's document frequency and the difference o...]]></description>
  <dc:date>2009-11-02</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/448/Delta-TFIDF-An-Improved-Feature-Space-for-Sentiment-Analysis">
  <title><![CDATA[Delta TFIDF: An Improved Feature Space for Sentiment Analysis]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/448/Delta-TFIDF-An-Improved-Feature-Space-for-Sentiment-Analysis</link>
  <description><![CDATA[Mining opinions and sentiment from social networking sites is a popular application for social media systems. Common approaches use a machine learning system with a bag of words feature set. We present Delta TFIDF, an intuitive general purpose technique to efficiently weight word scores before classification. Delta TFIDF is easy to compute, implement, and understand. We use Support Vector Machines to show that Delta TFIDF significantly improves accuracy for sentiment analysis problems using t...]]></description>
  <dc:date>2009-05-17</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/431/Using-Wikitology-for-Cross-Document-Entity-Coreference-Resolution">
  <title><![CDATA[Using Wikitology for Cross-Document Entity Coreference Resolution]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/431/Using-Wikitology-for-Cross-Document-Entity-Coreference-Resolution</link>
  <description><![CDATA[We describe the use of the Wikitology knowledge base as a resource for a variety of applications with special focus on a cross-document entity coreference resolution task. This task involves recognizing when entities and relations mentioned in different documents refer to the same object or relation in the world. Wikitology is a knowledge base system constructed with material from Wikipedia, DBpedia and Freebase that includes both unstructured text and semi-structured information.  Wikitology...]]></description>
  <dc:date>2009-03-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/423/Knowledge-Base-Evaluation-for-Semantic-Knowledge-Discovery">
  <title><![CDATA[Knowledge Base Evaluation for Semantic Knowledge Discovery]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/423/Knowledge-Base-Evaluation-for-Semantic-Knowledge-Discovery</link>
  <description><![CDATA[Semantic knowledge discovery has traditionally been evaluated at the text level. For example, evaluations such as MUC and ACE evaluate the information extraction of particular types of semantic roles and relations primarily at the mention level. We suggest that evaluating at the level of a knowledge base (KB) extracted from the text has significant advantages over evaluation at the text level. By knowledge base, we mean the combination of a database, a descriptive schema for the contents of t...]]></description>
  <dc:date>2008-11-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/428/An-Investigation-of-Linguistic-Information-for-Speech-Recognition-Error-Detection">
  <title><![CDATA[An Investigation of Linguistic Information for Speech Recognition Error Detection]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/428/An-Investigation-of-Linguistic-Information-for-Speech-Recognition-Error-Detection</link>
  <description><![CDATA[After several decades of effort, signiﬁcant progress has been made in the area of speech recognition technologies, and various speech-based applications have been developed. However, current speech recognition systems still generate erroneous output, which hinders the wide adoption of speech applications. Given that the goal of error-free output can not be realized in near future, mechanisms for automatically detecting and even correcting speech recognition errors may prove useful for amend...]]></description>
  <dc:date>2008-10-20</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/388/OWL-as-a-Target-for-Information-Extraction-Systems-">
  <title><![CDATA[OWL as a Target for Information Extraction Systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/388/OWL-as-a-Target-for-Information-Extraction-Systems-</link>
  <description><![CDATA[Current information extraction systems can do a good job of discovering entities, relations and events in natural language text.  The traditional out- 
put of such systems is XML, with the ACE Pilot Format (APF) schema as a 
common target.  We are developing a system that will take the output of an information extraction system as APF documents and directly populate a knowledge base with the information extracted.  We report on an initial OWL ontology that covers the APF schema, a simple pr...]]></description>
  <dc:date>2008-04-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/328/Using-a-Natural-Language-Understanding-System-to-Generate-Semantic-Web-Content">
  <title><![CDATA[Using a Natural Language Understanding System to Generate Semantic Web Content]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/328/Using-a-Natural-Language-Understanding-System-to-Generate-Semantic-Web-Content</link>
  <description><![CDATA[We describe our research on automatically generating rich semantic 
annotations of text and making it available on the Semantic Web.
In particular, we discuss the challenges 
involved in adapting the OntoSem natural
language processing system for this purpose. OntoSem, an implementation of
the theory of ontological semantics under continuous development for over 
15 years, uses a specially constructed NLP-oriented ontology and an 
ontological-semantic lexicon to translate English
text...]]></description>
  <dc:date>2006-10-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/301/SemNews-A-Semantic-News-Framework">
  <title><![CDATA[SemNews: A Semantic News Framework]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/301/SemNews-A-Semantic-News-Framework</link>
  <description><![CDATA[SemNews is a semantic news service that monitors different
RSS news feeds and provides structured representations of
themeaning of news. As new content appears, SemNews extracts
the summary from the RSS description and processes
it using OntoSem, which is a sophisticated text understanding
system.]]></description>
  <dc:date>2006-02-22</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/260/Text-understanding-agents-and-the-Semantic-Web">
  <title><![CDATA[Text understanding agents and the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/260/Text-understanding-agents-and-the-Semantic-Web</link>
  <description><![CDATA[We discuss the challenges involved in adapting the OntoSem natural
language processing system to the Web.  One set of tasks involves
processing Web documents, translating their computed meaning
representations from the OntoSem's native KR language into the
Semantic Web language OWL, and publishing the results as Web pages and
RSS feeds.  Another set of tasks works in reverse -- querying the Web
for facts needed by OntoSem, translating them from OWL into OntoSem's
native KR language and...]]></description>
  <dc:date>2006-01-04</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/261/Integrating-Language-Understanding-Agents-Into-the-Semantic-Web">
  <title><![CDATA[Integrating Language Understanding Agents Into the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/261/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 SemanticWeb language OWL. This approach
adds knowledge on the W...]]></description>
  <dc:date>2005-11-04</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/114/The-Integrality-of-Speech-in-Multimodal-Interfaces">
  <title><![CDATA[The Integrality of Speech in Multimodal Interfaces]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/114/The-Integrality-of-Speech-in-Multimodal-Interfaces</link>
  <description><![CDATA[A framework of complementary behavior has been proposed which maintains that direct manipulation and speech interfaces have reciprocal strengths and weaknesses. This suggests that user interface performance and acceptance may increase by adopting a multimodal approach that combines speech and direct manipulation. This effort examined the hypothesis that the speed, accuracy, and acceptance of multimodal speech and direct manipulation interfaces will increase when the modalities match the perce...]]></description>
  <dc:date>1998-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/337/The-Kernel-Natural-Language-Processing-System">
  <title><![CDATA[The Kernel Natural Language Processing System]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/337/The-Kernel-Natural-Language-Processing-System</link>
  <description><![CDATA[This article describes KERNEL, a text understanding system developed at the Unisys
Center for Advanced Information Technology. KERNEL’s design is motivated by the need
to make complex interactions possible among system modules, and to control the amount
of reasoning done by those modules. We will explain how Kernel’s architecture meets these
needs, and how the architectures of similar systems compare in achieving the same goal.]]></description>
  <dc:date>1993-10-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/287/Modeling-the-user-in-natural-language-systems">
  <title><![CDATA[Modeling the user in natural language systems]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/287/Modeling-the-user-in-natural-language-systems</link>
  <description><![CDATA[For intelligent interactive systems to communicate with humans in a natural manner, they must have knowledge about the system users. This paper explores the role of user modeling in such systems. It begins with a characterization of what a user model is and how it can be used. The types of information that a user model may be required to keep about a user are then identified and discussed. User models themselves can vary greatly depending on the requirements of the situation and the implement...]]></description>
  <dc:date>1988-01-23</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/347/Natural-language-interactions-with-artificial-experts">
  <title><![CDATA[Natural language interactions with artificial experts]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/347/Natural-language-interactions-with-artificial-experts</link>
  <description><![CDATA[The aim of this paper is to justify why Natural Language (NL) interaction, of a very rich functionality, is critical to the effective use of Expert Systems and to describe what is needed and what has been done to support such interaction. Interactive functions discussed here include defining terms, paraphrasing, correcting misconceptions, avoiding misconceptions, and modifying questions.]]></description>
  <dc:date>1986-07-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/285/The-Semantic-Interpretation-of-Nominal-Compounds">
  <title><![CDATA[The Semantic Interpretation of Nominal Compounds]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/285/The-Semantic-Interpretation-of-Nominal-Compounds</link>
  <description><![CDATA[This paper briefly introduces an approach to the problem of building semantic interpretations of nominal compounds, i.e., sequences of two or more nouns related through modification.  Examples of the kind of nominal compounds dealt with are: "engine repairs", "aircraft flight arrival", "aluminum water pipe" and "noun noun modification".]]></description>
  <dc:date>1980-08-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/344/Semantic-Interpretation-of-Compound-Nominals-">
  <title><![CDATA[Semantic Interpretation of Compound Nominals]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/344/Semantic-Interpretation-of-Compound-Nominals-</link>
  <description><![CDATA[This thesis deals with one aspect of enabling machines to communicate with people in a natural language. The particular problem which is the focus of this work is the interpretation of nominal compounds , i.e. sequences of two or more nouns related through modification. Examples of the kinds of nominal compounds dealt with are "engine repairs" "air craft flight arrival" "aluminum water pump", and "noun noun modification".]]></description>
  <dc:date>1980-05-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/156/Integrating-Language-Understanding-Agents-into-the-Semantic-Web">
  <title><![CDATA[Integrating Language Understanding Agents into the Semantic Web]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/156/Integrating-Language-Understanding-Agents-into-the-Semantic-Web</link>
  <description><![CDATA[AAAI Fall Symposium session on Agents and Semantic Web presentation at Arlington Virginia Nov 4 2005]]></description>
  <dc:date>2005-11-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/250/Wikitology-Wikipedia-as-an-ontology">
  <title><![CDATA[Wikitology: Wikipedia as an ontology]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/250/Wikitology-Wikipedia-as-an-ontology</link>
  <description><![CDATA[Wikipedia has become an important source of online knowledge for people that is kept up to date and available in many languages. We describe an approach to extracting information from Wikipedia and related sources to construct an ontology and associated knowledge base. The core idea is to use Wikipedia's articles and associated pages as a topic ontology. The benefits of the approach are that the ontology terms are developed through a social process, maintained and kept current by the Wikipedi...]]></description>
  <dc:date>2008-08-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/319/Generic-knowledge-acquisition-and-representation">
  <title><![CDATA[Generic knowledge: acquisition and representation]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/319/Generic-knowledge-acquisition-and-representation</link>
  <description><![CDATA[AI is beginning to make some dents in the "knowledge acquisition bottleneck", the problem of acquiring large amounts of general world knowledge to support language understanding and commonsense reasoning. Two text-based approaches to the problem are (1) to abstract such knowledge from patterns of predication and modification in miscellaneous texts, and (2) to derive such knowledge by direct interpretation of general statements in ordinary language, such as are found in lexicons and resources ...]]></description>
  <dc:date>2009-10-06</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/282/When-is-a-Translation-not-a-Translation-">
  <title><![CDATA[When is a Translation not a Translation?]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/282/When-is-a-Translation-not-a-Translation-</link>
  <description><![CDATA[A translation is generally taken to be a text that expresses the same
meaning as another text in a different language. But the products of
the best translators reflects a different, if more illusive, goal. I
will seek a somewhat more adequate characterization of translation as
it is actually practiced and discuss its consequences for machine
translation.]]></description>
  <dc:date>2009-02-03</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/256/Information-Extraction-via-Automatic-Generation-of-Semantic-Classifiers">
  <title><![CDATA[Information Extraction via Automatic Generation of Semantic Classifiers]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/256/Information-Extraction-via-Automatic-Generation-of-Semantic-Classifiers</link>
  <description><![CDATA[Information extraction is an important unsolved problem of natural
language processing (NLP). It is the problem of extracting entities
(such as people, organizations or locations) and named relations
between entities (such as "People born-in Country") from text
documents. An important challenge in information extraction is the
labeling of training data which is usually done manually and is
therefore very expensive.

This talk introduces a new "model" to generate training data with
le...]]></description>
  <dc:date>2008-09-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/252/Wikitology-Wikipedia-as-an-ontology-">
  <title><![CDATA[Wikitology: Wikipedia as an ontology]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/252/Wikitology-Wikipedia-as-an-ontology-</link>
  <description><![CDATA[Wikipedia has become an important source of online knowledge for people
that is kept up to date and available in many languages.  We describe
an approach to extracting information from Wikipedia and related
sources to construct an ontology and associated knowledge base. The
core idea is to use Wikipedia's articles and associated pages as a
topic ontology. The benefits of the approach are that the ontology
terms are developed through a social process, maintained and kept
current by the ...]]></description>
  <dc:date>2008-08-28</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/249/Using-Automatic-Word-Sense-Discrimination-to-generate-a-Semantic-Lexicon">
  <title><![CDATA[Using Automatic Word Sense Discrimination to generate a  Semantic Lexicon]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/249/Using-Automatic-Word-Sense-Discrimination-to-generate-a-Semantic-Lexicon</link>
  <description><![CDATA[Automatic word sense discrimination is the process of distinguishing the 
number of unique senses of a target word in a given corpus. This work 
approaches word sense discrimination as an unsupervised clustering 
problem on the context of the target word in web documents.
Using the features from the computed clusters, the system constructs a 
new lexicon entry for the target word which includes the semantic and 
syntactic constraints for each discriminated sense. The lexicon entries 
a...]]></description>
  <dc:date>2008-07-07</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/246/Grammatical-Inference-Some-of-the-Questions-Out-There">
  <title><![CDATA[Grammatical Inference: Some of the Questions Out There]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/246/Grammatical-Inference-Some-of-the-Questions-Out-There</link>
  <description><![CDATA[Grammatical Inference is a field concerned with learning
grammars given data about a language.  In this talk we
survey some of the questions being addressed by researchers
in the field.  Some of these are now classical and have been
looked into for some time, others are more recent:

understanding the models and the paradigms:
what does polynomial language learning mean?

learning more complex families of languages

scaling up and using grammatical inference in applications]]></description>
  <dc:date>2008-06-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/210/When-Will-Computers-Understand-Shakespeare-b-font-color-red-CANCELED-9-10-font-b-">
  <title><![CDATA[When Will Computers Understand Shakespeare? CANCELED 9/10]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/210/When-Will-Computers-Understand-Shakespeare-b-font-color-red-CANCELED-9-10-font-b-</link>
  <description><![CDATA[CANCELED 9/10 In this talk I will examine problems encountered in coming to some kind of understanding of one sonnet by Shakespeare (his 64th), ask what it would take to solve these problems computationally, and suggests routes to the solution. The general conclusion is that we are closer to this goal as one might think. Or are we? CANCELED 9/10]]></description>
  <dc:date>2007-09-11</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>
</rdf:RDF>
