Network science

Swoogle is a crawler-based indexing and retrieval system for the Semantic Web. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is ontology rank, a measure of the importance of a Semantic Web document.

/pdf/swoogle-a-search-and-metadata-engine-for-the-semantic-web-5cherzfl8h.pdf

Swoogle: a search and metadata engine for the semantic web

Communications of the ACM (CACM for short, not the best sounding acronym around) is the ACM’s flagship magazine. Started in 1957, CACM is handy for keeping up to date on current research being carried out across all topics of computer science and realworld applications. CACM has had an illustrious past with many influential pieces of work and debates started within its pages. These include Hoare’s presentation of the Quicksort algorithm; Rivest, Shamir and Adleman’s description of the first publickey cryptosystem RSA; and Dijkstra’s famous letter against the use of GOTO. In addition to the print edition, which is released monthly, there is a fantastic website (http://cacm.acm. org/) that showcases not only the most recent edition but all previous CACM articles as well, readable online as well as downloadable as a PDF. In addition, the website lets you browse for articles by subject, a handy feature if you want to focus on a particular topic. CACM is really essential reading. Pretty much guaranteed to contain content that is interesting to anyone, it keeps tabs on the latest in computer science. It is a valuable asset for us students, who tend to delve deep into a particular area of CS and forget everything that is happening around us. — Daniel Gooch U ndergraduate research is like a box of chocolates: You never know what kind of project you will get. That being said, there are still a few things you should know to get the most out of the experience.

Communications of the ACM

http://iiseb.knu.ac.kr/Lecture/2012/KSS/p3.pdf

KMPI: measuring knowledge management performance

Richly interlinked, machine-understandable data constitute the basis for the Semantic Web. We provide a framework, S-CREAM, that allows for creation of metadata and is trainable for a specific domain. Annotating web documents is one of the major techniques for creating metadata on the web. The implementation of S-CREAM, OntoMat-Annotizer supports now the semi-automatic annotation of web pages. This semi-automatic annotation is based on the information extraction component Amilcare. OntoMat-Annotizer extract with the help of Amilcare knowledge structure from web pages through the use of knowledge extraction rules. These rules are the result of a learning-cycle based on already annotated pages.

/pdf/s-cream-semi-automatic-creation-of-metadata-2mhlwquwjc.pdf

S-CREAM - Semi-automatic CREAtion of Metadata

A generational cohort is the term used to describe a group of people born within the same time span. Having experienced similar life events during their formative years, these individuals tend to have similar attitudes, adaptabilities and traits. In this paper we look at generational groups, contemporary cohort changes and how technology-savvy Millennial students need a different approach to learning. We also discuss a ubiquitous school system which has the potential to provide individual support in future schools. It offers every child a personal educational assistant - a discreet, unobtrusive helper. The educational assistant will be available through the computer network, both within the school system and externally through the Internet. It will be able to traverse time and space, and be of assistance at any time and any place.

/pdf/future-schools-and-how-technology-can-be-used-to-support-4av5xxp9w0.pdf

Future Schools and How Technology can be used to support Millennial and Generation-Z Students

This article shows how CGLF, CGIF, KIF, Formalized-English and Frame-CG can be used in a panorama of knowledge representation cases. It highlights various inadequacies of CGLF and CGIF, advantages provided by high-level expressive notations, and the KIF translations provide a logical interpretation. Knowledge providers may see this document as a guide for knowledge representation. Developers may see it as a list of cases to take into account for their notations and inferences engines.

/pdf/knowledge-representation-in-cglf-cgif-kif-frame-cg-and-33odsamy5l.pdf

Knowledge Representation in CGLF, CGIF, KIF, Frame-CG and Formalized-English

Des taches courantes lors de la realisation d'un systeme a base de connaissances, sont la recherche et la representation d'informations contenues dans des documents (e. G. Des retranscriptions d'interviews d'experts), la creation et la manipulation de documents (e. G. Documentation technique), la recherche et la manipulation de connaissances dans une base de connaissances (e. G. Pour les valider). Afin de faciliter l'execution de telles taches par un cogniticien, nous avons cree un outil logiciel permettant l'utilisation combinee a) des techniques avancees de structuration et de gestion de documents offertes par l'editeur de documents structures et hypertextes thot, et b) de techniques avancees de representation et d'organisation de connaissances permises par le formalisme des graphes conceptuels. Des representations de connaissances peuvent ainsi a) etre stockees, recherchees et gerees dans des documents via l'editeur thot, et b) etre exploitees pour permettre la recherche des informations qu'elles indexent dans des documents. De telles recherches peuvent s'effectuer par navigation ou par requete et permettre la generation de documents qui sont des vues sur des parties de documents ou de la base selectionnees sur des criteres conceptuels. De plus, afin de guider et faciliter le travail du cogniticien dans la representation et la recherche de connaissances et d'informations, nous avons constitue une ontologie comprenant a) des types de relations elementaires usuelles (relations rhetoriques, mereologiques, spatiales, temporelles, mathematiques, etc. ), et b) des types de concepts generaux que nous avons specialises par les 90. 000 types de concepts de la base generale de connaissances terminologique wordnet. Nous montrons comment l'exploitation de cette ontologie par des cogniticiens permet d'ameliorer la coherence, l'extensibilite et la reutilisabilite de leurs representations de connaissances

Exploitation de graphes conceptuels et de documents structurés et hypertextes pour l'acquisition de connaissances et la recherche d'informations

In the first part of this article, we present the benefits of using a structured document editor for storing, editing, and structuring knowledge representations, and show how this can be done for knowledge represented in the Conceptual Graph (CG) formalism. In structured documents, document elements (DEs) are typed and can be organized by structural or hypertext links. They can also be shared (included) by other DEs. The organization of DEs is specified by structure models (Document Type Definitions (DTDs)). A structured document editor displays documents according to their presentation models and lets the users to edit them and to structure them in accordance with their DTDs. We have defined DTDs and presentation models for allowing the storing and display of a CG, a type definition and a hierarchy of types or CGs. Furthermore, we used the functional interface of the structured document editor Thot (previously named Grif) (Quint & Vatton, 1992) so that when a CG, a type definition or a hierarchy is loaded or built in Thot, a similar element is loaded or built in the base of the CG workbench CoGITo (Haemmerle, 1995).

Conceptual Structures and Structured Documents

The paper argues for the use of general and intuitive knowledge representation lajiguages for indexing the content of Web documents and representing knowledge within them. We believe these languages have advantages over metadata languages based on the Extensible Mark-up Language (XML). Indeed, the representation and retrieval of precise information is better supported by languages designed to represent semantic content and support logical inference, and the readability of such a language eases its exploitation, presentation and direct insertion within a document.To further ease the representation process, we propose techniques allowing users to leave some knowledge terms undeclared. We illustrate these ideas with WebKB, a precision-oriented information retrieval/annotation tool, and show how lexical, structural ajid knowledge-based techniques may be combined to retrieve or generate knowledge or Web documents. Finally, to overcome the scalability problems of storing knowledge within Web documents, we propose some ideas for scalable and cooperatively built knowledge repositories.

Embedding Knowledge in Web Documents: CGs versus XML-based Metadata Languages

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