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Of 9 Creator In NET Framework Using Barcode maker for 4 the use of natural language generation to describe ontological knowledge in a more natural format and the delivery of knowledge to the user in a format appropriate to he terminal device to which they currently have access In this section, we describe a semantic search agent, SEKTAgent, which brings together the exploitation of an ontological knowledge base, natural language generation and device independence to proactively deliver relevant information to its users Search agents can reduce the overhead of completing a manual search for information The best known commercial search agent is perhaps Google Alerts , based on syntactic queries of the Google index Using an API provided by the KIM system (see Section 825 above), SEKTAgent allows users to associate with each agent a semantic query based upon the PROTON ontology (see 7).

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Some examples of agent queries that could be made would be for documents mentioning: A named person holding a particular position, within a certain organisation A named organisation located at a particular location A particular person and a named location A named company, active in a particular industry sector This mode of searching for types of entity can be complemented with a full text search, allowing the user to specify terms which should occur in the text of the retrieved documents In addition to the use of subsumption reasoning provided by KIM, it is also planned that SEKTAgent will incorporate the use of explicitly de ned domain-speci c rules The SEKT search tool uses KAON29 as its reasoning engine KAON2 is an infrastructure for managing OWL-DL ontologies It provides an API for the programmatic management of OWL-DL and an inference engine for answering conjunctive queries expressed using SPARQL10 syntax.

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In this section, we describe a semantic search agent SEKTAgent, which brings together the exploitation of an ontological knowledge base, natural language generation and device independence to proactively deliver relevant information to its users Search agents can reduce the overhead of completing a manual search for information The best known commercial search agent is perhaps Google Alerts , based on syntactic queries of the Google index Using an API provided by the KIM system (see Section 825 above), SEKTAgent allows users to associate with each agent a semantic query based upon the PROTON ontology (see 7) Some examples of agent queries that could be made would be for documents mentioning: A named person holding a particular position, within a certain organisation A named organisation located at a particular location A particular person and a named location A named company, active in a particular industry sector.

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Code 39 In Visual Studio .NET Using Barcode printer for VS . Code39 Encoder In VB.NET Using Barcode creation for .Now that we've identified the elements we want to represent, we move on to step two in the process and define an XDR schema that models them We could do this by hand, and SQL Server Books nline can instruct you in all of the fine details of how to build the most exquisite XDR schemas known to man Or, we can do it the easy way and finish in five minutes If we were building an XDR schema by hand, we would essentially be building an XML document because XDR schemas, unlike their cousins, DTDs, are themselves XML documents They just happen to represent the structure of other XML documents However, we're going to save time and use a simple coding trick to define our schema quickly and accurately.Related: Print Data Matrix .NET , .NET WinForms Code 128 Generation , Print ITF-14 Java

This mode of searching for types of entity can be complemented with a full text search, allowing the user to specify terms which should occur in the text of the retrieved documents In addition to the use of subsumption reasoning provided by KIM, it is also planned that SEKTAgent will incorporate the use of explicitly de ned domain-speci c rules The SEKT search tool uses KAON29 as its reasoning engine KAON2 is an infrastructure for managing OWL-DL ontologies It provides an API for the programmatic management of OWL-DL and an inference engine for answering conjunctive queries expressed using SPARQL10 syntaxRelated: EAN-13 Creating C# , QR Code Printing Java , Codabar Generation ASPNET.

This chapter has offered a quick tour of basic LINQ to SQL features In a nutshell, LINQ to SQL lets you uery relational data as objects using the LINQ query pattern It provides a simple but expressive API to save the changed objects It works with entity classes mapped to tables and relationships between classes mapped to foreign keys in the database You can. C Encoder In Visual Basic .NET Using Barcode printer for .NET .Related: C# PDF417 Generator , EAN-8 Printing .NET WinForms , Create Codabar ASP.NET

Additional Reading. QR Code Printer In Visual Basic .NET Using Barcode maker for . Goldstein, Jackie Microsoft SQL Server 2005 Express Edition Step by Step icrosoft Press, 2006 Teach yourself how to get a data-intensive application up and running quickly with SQL Server Express Edition one step at a time With this book, you work at your own pace through hands-on, learn-by-doing exercises Whether you re new to database programming or new to SQL Server, you ll learn how, when, and why to use speci c features of this simple but powerful database development environment Each chapter.Related: EAN-8 Printing C# , Print Data Matrix Java , Intelligent Mail Creating ASP.NET

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