Friday, September 17, 2004

Acquiring Word-Meaning Mappings for Natural Language Interfaces 

Acquiring Word-Meaning Mappings for Natural Language Interfaces PDF
"Abstract:
This paper focuses on a system, WOLFIE (WOrd Learning From Interpreted Examples), that acquires a semantic lexicon from a corpus of sentences paired with semantic representations. The lexicon learned consists of phrases paired with meaning representations. WOLFIE is part of an integrated system that learns to transform sentences into representations such as logical database queries. Experimental results are presented demonstrating WOLFIE's ability to learn useful lexicons for a database interface in four different natural languages. The usefulness of the lexicons learned by WOLFIE are compared to those acquired by a similar system, with results favorable to WOLFIE. A second set of experiments demonstrates WOLFIE's ability to scale to larger and more difficult, albeit artificially generated, corpora. In natural language acquisition, it is difficult to gather the annotated data needed for supervised learning; however, unannotated data is fairly plentiful. Active learning methods attempt to select for annotation and training only the most informative examples, and therefore are potentially very useful in natural language applications. However, most results to date for active learning have only considered standard classification tasks. To reduce annotation effort while maintaining accuracy, we apply active learning to semantic lexicons. We show that active learning can significantly reduce the number of annotated examples required to achieve a given level of performance."

Thursday, September 16, 2004

Semantic XML Web Services Community of Practice 

Semantic XML Web Services Community of Practice

KM.gov - Knowledge Management in Government 

KM.gov - Knowledge Management in Government
"Knowledge management is the discipline dedicated to more deliberate means of people creating and sharing knowledge - data, information, and understanding in a social context - to make the right decisions and take the right actions.
From our Charter:
Federal Chief Information Officers Council, (the CIO Council) establishes the Knowledge Management Working Group ... as an interagency body to bring the benefits of the government's intellectual assets to all Federal organizations, customers, and partners... "


Mapping WordNet to the SUMO Ontology 

Mapping WordNet to the SUMO Ontology
"Introduction
Ontologies are becoming extremely useful tools for sophisticated software engineering. Designing applications, databases, and knowledge bases with reference to a common ontology can mean shorter development cycles, easier and faster integration with other software and content, and a more scalable product. Although ontologies are a very promising solution to some of the most pressing problems that confront software engineering, they also raise some issues and difficulties of their own. Consider, for example, the questions below:

SUMO (Suggested Upper Merged Ontology), which has been proposed as the initial version of an eventual Standard Upper Ontology (SUO). We will then describe the popular, free, and structured WordNet lexical database. After this preliminary discussion, we will describe the methodology that we are using to align WordNet with the SUMO. Finally, we will close this paper by demonstrating how this alignment of WordNet with SUMO will provide answers to the questions posed above."

Towards a Standard Upper Ontology 

Towards a Standard Upper Ontology is a paper about SUMO (Standard Upper Merged Ontology).

XML.com: Uncle Sam's Semantic Web 

XML.com: Uncle Sam's Semantic Web "From the EPA to the Navy, the United States government is coming to see the Semantic Web as a solution to huge data-processing problems. XML.com columnist Paul Ford gets the scoop at the 2004 Semantic Technologies for e-Government Conference.
"

Suggested Upper Merged Ontology 

Suggested Upper Merged Ontology

Model-Theoretic Semantics for the Web 

Model-Theoretic Semantics for the Web: "The word 'model' is not always defined the same way by logicians who study model theory, though the variability in these definitions is rather slight. Consider the following two definitions, the first taken from an introductory article on model theory, and the second from a textbook on mathematical logic.

Definition 1: 'Sometimes we write or speak a sentence S that expresses nothing either true or false, because some crucial information is missing about what the words mean. If we go on to add this information, so that S comes to express a true or false statement, we are said to interpret S, and the added information is called an interpretation of S. If the interpretation I happens to make S state something true, we say that I is a model of S, or that I satisfies S, in symbols I |= S '

Definition 2: 'Now, using induction on formulas f, we give a definition of the relation I is a model of f, where I is an arbitrary interpretation. If I is a model of f we also say that I satisfies f or that f holds in I, and we write I |= f ... [the long, inductive definition follows]'

Definition 3: "Intuitively a model is a situation. That is, it is a semantic entity: it contains the kinds of things we want to talk about. Thus a model for a given vocabulary gives us two pieces of information. First, it tells us which collection of entities we are talking about; this collection is usually called the domain. Second, for each symbol in the vocabulary, it gives us an appropriate semantic entity, built from the items in D [the domain]. This task is carried out by a function F which specifies, for each symbol in the vocabulary, an appropriate semantic value; we call such functions interpretation functions. Thus, in set theoretic terms, a model M is an ordered pair (D, F) consisting of a domain D and an interpretation function F specifying semantic values in D"

RDFS(FA) and RDF MT: Two Semantics for RDFS 

RDFS(FA) and RDF MT: Two Semantics for RDFS
"Abstract. RDF Schema (RDFS) has a non-standard metamodeling architecture, which makes some elements in the model have dual roles in the RDFS specification. As a result, this can be confusing and difficult to understand and, more importantly, the specification of its semantics requires a non-standard model theory. This leads to semantic problems when trying to layer conventional first order languages, like DAML+OIL, on top of RDFS. In this paper we will first demonstrate how this problem with RDFS can be solved in a sub-language of RDFS - RDFS(FA), which introduces a Fixed layer metamodeling Architecture to RDFS, based on a (relatively) standard model-theoretic semantics. Logical layer Semantic Web languages such as DAML+OIL and OWL can, therefore, be built on top of both the syntax and semantics of RDFS(FA). We will also compare this approach with the existing RDF Model Theory and discuss the
advantages and disadvantages of the two approaches."

Running Lucene Search on WebLogic Portal 8.1 

Running Lucene Search on WebLogic Portal 8.1

WebLogic Portal 8.1 

WebLogic Portal 8.1 This is the home for documentation on this product.

WSRP-HOWTO.TXT 

WSRP How To

In order to get a quick understanding on how WSRP works from the Admin Portal, follow the steps below:

1. Launch the Portal samples domain and login to the Administration Portal under: http://localhost:7001/portalAppAdmin .
2. Under the Portals tab, click on the Library which is on the left hand side.
3. After the tree expands, click on the Portlet Producers icon.
4. Once the Producer Resources panel shows up on the right side, click on the "Browse/Add Producers" tab.
5. Under the "Enter Producer to Browse" box, enter: http://localhost:7001/tutorial/producer?wsdl . Click "OK".
6. At this point you should see a list of Producer's properties including available portlets. Click "Add Producer" and fill in the registration fields.
7. After registering, you will be at the "Available Producers" window. From the "Available Producers" box, click the "Register" button. On the dialog box, click "Save".
8. Click the Producer that you registered and pick a portlet such as the "Process Form" portlet.

At this point you can click on "All Portlets" in the library tree and you should see the remote portlet you just added. There is also a convenient portlet category, "All Remote Portlets," created under the "Category" drop-down menu in the "Available Portlets" box. Now you can add the remote portlet to a page and make them available to users.

From the WebLogic Workshop, you can also bring in remote portlets by following the steps below:

1. Launch the Portal samples domain. Open the Sampleportal project under bea\weblogic81\samples\portal\portalApp
2. Create a new directory under the Sampleportal project called "RemotePortlets" .
3. Right click on the new directory you just created and select " New" and then the option to create a new portlet.
4. When the Portlet Wizard comes up, select the "Remote Portlet" option and click " Next".
5. Paste the Producer URL "http://localhost:7001/tutorial/producer?wsdl" and click "Retrieve".
6. Next click "Register" and fill in the blanks for the registration. At this point you should see the "Producer Details".
7. Click "Next" and add a portlet, like the "wizard - process form" portlet (last in the list).
8. Click "Next" again and review the details of the Proxy Portlet Details and click "Finish".

At this point a .portlet file will be created that represents the remote portlet you developed . You can then use the portlet in your project.

For documentation on WSRP, please visit:

http://dev2dev.bea.com

Portal Team

Create Adobe PDF Online 

Create Adobe PDF Online

Ringlord Technologies Publications: LaTeX-to-PDF - How-To 

Ringlord Technologies Publications: LaTeX-to-PDF - How-To
"...the purpose of this document: how to create high-quality (e.g. fast-displaying) PDF documents from your LaTeX sources. These documents will offer the following benefits to those who read your work; all of that capability is available completely free of charge. I've done all the work for you with this comprehensive how-to document:

The combination of tools available allows you to generate documents whose visual quality and feature-completeness can rival anything you can get out of commercial tools on other platforms. What's more, few of the documents created with Adobe Distiller are as feature-rich as what you get with these tools. And with Linux it's all free. No surprise at all."

Top 10 Open Source Tools for eActivism 

Top 10 Open Source Tools for eActivism

Guidelines for assigning identifiers to metadata terms 

Guidelines for assigning identifiers to metadata terms
"Description of Document: This document provides some simple guidelines for assigning identifiers to non-DCMI metadata terms (elements, element refinements, encoding schemes and vocabulary terms). "

Wednesday, September 15, 2004

Full Abstraction and Semantic Equivalence - The MIT Press 

Full Abstraction and Semantic Equivalence - The MIT Press

CERT Coordination Center 

CERT Coordination Center is all about internet security.

International Organization for Standardization - ISO's Developement 

International Organization for Standardization - ISO's Developement

ISO - Stages of the development of International Standards 

ISO - Stages of the development of International Standards

FW: Security Advisories (BEA04-65.00, BEA04-66.00, BEA04-67.00, BEA04-68.00, BEA04-69.00, BEA04-70.00, BEA04-71.00, BEA04-72.00, BEA04-73.00) 



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Sent: Monday, September 13, 2004 9:38 PM
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Google Search: Normative Standardization process 

Google Search: Normative Standardization process

Tuesday, September 14, 2004

Corese 

Corese " stands for Conceptual Resource Search Engine. It is an RDF engine based on Conceptual Graphs (CG). It enables the processing of RDF Schema and RDF statements within the CG formalism (see a note http://www.w3.org/DesignIssues/CG.html from T. Berners-Lee on the subject).

Corese has support from INRIA for a two years (2002-2004) software development support action."

ALVIS - Superpeer Semantic Search Engine 

ALVIS - Superpeer Semantic Search Engine"Welcome to the growing home of the ALVIS Consortium. We are building an Open Source searche engine using new technologies.

Motivation: The new economy is based on innovation, and innovation is based on up-to-date information. The semi-static Internet alone has in the order of 1000 million pages of information, and search has become a fundamental service required both by individual citizens and businesses alike. Search facilities have an impact on almost any task related to the information society. Reports indicate that European consumers are dismayed with the US saturation of existing services (as reported by the BBC, May 2, 2002). Moreover, only a few corporations have broad access to rich terabyte repositories of web data that can be used to provide unique value-added services in areas such as shopping, human resources, and business intelligence.

The vast quantity of information sets new challenges for even the best commercial search engines. Building next generation search engines is not just a question of scaling existing techniques. What is needed is a departure from the existing keyword search that has made current search cumbersome even for the skilled. Qualitatively better ways are needed to allow more meaningful, semantically aware queries, and new delivery modes are needed to make search another common resource in the spirit of the web itself, to make search peer to peer. "

Overcoming Ontology Mismatches in Transactions with Self-Describing service Agents 

Overcoming Ontology Mismatches in Transactions with Self-Describing service Agents
"Abstract.
One vision of the “Semantic Web” of the future is that software agents will interact with each other using formal metadata that reveal their interfaces. We examine one plausible paradigm, where agents provide service descriptions that tell how they can be used to accomplish other agents’ goals. From the point of view of these other agents, the problem of deciphering a service description is quite similar to the standard AI planning problem, with some interesting twists. Two such twists are the possibility of having to reconcile contradictory ontologies— or conceptual frameworks — used by the agent, and having to rearrange the data structures of a message-sending agent so they match the expectations of the recipient. We argue that the former problem requires human intervention and maintenance, but that the latter can be fully automated."

The Future of Software Integration: Self-integrating Systems 

The Future of Software Integration: Self-integrating Systems
"Abstract
This paper outlines a visionary research program for systems integration that will improve the reliability and robustness of complex “systems of systems.” This program, self-integrating systems, will significantly advance the science underlying computer communication and the engineering of software for network-centric systems. Key concepts representative of the notion of self-integrating systems include semantic interoperability, knowledge representation, information theory, and coordination models."

Google Search: automated standards consensus agreement 

Google Search: automated standards consensus agreement

Interoperability Standards in the Semantic Web 

Interoperability Standards in the Semantic Web"The growth in the use of the Internet brings with it an increase in the number of interconnections among information systems supporting the manufacturing supply chain as well as other businesses. Each of these interconnections must be carefully prescribed to ensure interoperability. However, the sheer number of interconnections and the resulting complexity threaten to overwhelm the ability of the standards community or industry to provide the necessary specifications—a way out of this impasse must be found. This paper outlines the elements of an approach and the technology to move toward self-integrating systems, wherein the systems negotiate meaningful interfaces as needed in a dynamic environment."

Monday, September 13, 2004

Google Search: "peer-to-peer" "common knowledge" 

Google Search: "peer-to-peer" "common knowledge"

Peer-to-Peer Data Sharing Among LabVIEW Nodes Sadia Malik CS 395T- Grid Computing Project Report 12/13/03 

Peer-to-Peer Data Sharing Among LabVIEW Nodes Sadia Malik CS 395T- Grid Computing Project Report 12/13/03

Project JXTA 2.0 Super-Peer Virtual Network 

Project JXTA 2.0 Super-Peer Virtual Network

Snort.org 

Snort.org"Snort is an open source network intrusion detection system, capable of performing real-time traffic analysis and packet logging on IP networks. It can perform protocol analysis, content searching/matching and can be used to detect a variety of attacks and probes, such as buffer overflows, stealth port scans, CGI attacks, SMB probes, OS fingerprinting attempts, and much more.

Snort uses a flexible rules language to describe traffic that it should collect or pass, as well as a detection engine that utilizes a modular plugin architecture. Snort has a real-time alerting capability as well, incorporating alerting mechanisms for syslog, a user specified file, a UNIX socket, or WinPopup messages to Windows clients using Samba's smbclient.

Snort has three primary uses. It can be used as a straight packet sniffer like tcpdump(1), a packet logger (useful for network traffic debugging, etc), or as a full blown network intrusion detection system. "

Sunday, September 12, 2004

bibTeX Definition in Web Ontology Language (OWL) Version 0.1 

bibTeX Definition in Web Ontology Language (OWL) Version 0.1

Intellidimension Semantic Web Search 

Intellidimension Semantic Web Search

Bicycle Repair Man, a Refactoring Browser for Python 

Bicycle Repair Man, a Refactoring Browser for Python is a "... Refactoring Browser is an editor that automates Refactorings. The first Refactoring Browser was written by Dr. Don Roberts and Dr. John Brant at the University of Illinois in Urbana-Champagne. Dr. Don Roberts wrote his Ph.D. thesis on the design and implementation of the Refactoring Browser. For more detail, read the aforementioned thesis."

Mathematical Illustrations 

Mathematical Illustrations

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