KMi Planet: a web based news server

Domingue, John; Scott, Phillip

doi:10.1109/apchi.1998.704450

Cited by 5 publications

(1 citation statement)

References 3 publications

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“…Through a plug-in mechanism, MnM currently interfaces to the WebOnto [6] ontology server and is also able to read web accessible ontologies written in RDFS or DAML+OIL. MnM has been used to populate our ontology from our web based newsletter, KMi Planet [8]. KMi Planet contains stories about interesting events within our lab.…”

Section: Before Deploying Magpiementioning

confidence: 99%

Semantic Layering with Magpie

Domingue

Džbor

Motta

2004

Handbook on Ontologies

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Browsing the web involves two main tasks: finding the right web page and then making sense of its content. A significant amount of research has gone into supporting the task of finding web resources through 'standard' information retrieval mechanisms, or semantics-enhanced search. Much less attention has been paid to the second problem. In this paper we describe Magpie, a tool which supports the interpretation of web pages. Magpie acts as a complementary knowledge source, which a reader can call upon to quickly gain access to any background knowledge relevant to a web resource. Magpie works by automatically associating an ontology based semantic layer to web resources, allowing relevant services to be directly invoked within a standard web browser. The functionality of Magpie is illustrated using examples of how it has been integrated with our lab's web resources.

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Section: Before Deploying Magpiementioning

confidence: 99%

Semantic Layering with Magpie

Domingue

Džbor

Motta

2004

Handbook on Ontologies

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On the application of personalization techniques to news servers on the WWW

Ardissono

Console

Torre

2000

AI*IA 99: Advances in Artificial Intelligence

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This paper describes how the generation of hypertexts for accessing on-line news servers can be tailored to different users. News servers contain huge amounts of information, concerning different topics. The aim of our system is to present the most appropriate set of news (and advertisements) to each user, choosing the “right” level of detail for each news item. This is obtained by using knowledge representation, user modeling and exible hypermedia techniques

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