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Context as foundation for a semantic desktop
Adoption of semantic web technologies and principles presents an opportunity to change the conceptual model of desktop computing. Moving from a traditional position where the desktop is largely tied to a specific computational device, a semantic desktop could exist as a broad, networked space defined relative to the user. In this position paper we argue that personal, computing, and knowledge contexts are the appropriate means by which to define and shape the desktop space, and that collectively they provide the foundation for novel functionality in a semantic desktop
Semantic disambiguation and contextualisation of social tags
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-28509-7_18This manuscript is an extended version of the paper ‘cTag: Semantic Contextualisation of Social Tags’, presented at the 6th International Workshop on Semantic Adaptive Social Web (SASWeb 2011).We present an algorithmic framework to accurately and efficiently identify the semantic meanings and contexts of social tags within a particular folksonomy. The framework is used for building contextualised tag-based user and item profiles. We also present its implementation in a system called cTag, with which we preliminary analyse semantic meanings and contexts of tags belonging to Delicious and MovieLens folksonomies. The analysis includes a comparison between semantic similarities obtained for pairs of tags in Delicious folksonomy, and their semantic distances in the whole Web, according to co-occurrence based metrics computed with results of a Web search engine.This work was supported by the Spanish Ministry of Science
and Innovation (TIN2008-06566-C04-02), and Universidad Autónoma de Madrid
(CCG10-UAM/TIC-5877
Grammar-Based Random Walkers in Semantic Networks
Semantic networks qualify the meaning of an edge relating any two vertices.
Determining which vertices are most "central" in a semantic network is
difficult because one relationship type may be deemed subjectively more
important than another. For this reason, research into semantic network metrics
has focused primarily on context-based rankings (i.e. user prescribed
contexts). Moreover, many of the current semantic network metrics rank semantic
associations (i.e. directed paths between two vertices) and not the vertices
themselves. This article presents a framework for calculating semantically
meaningful primary eigenvector-based metrics such as eigenvector centrality and
PageRank in semantic networks using a modified version of the random walker
model of Markov chain analysis. Random walkers, in the context of this article,
are constrained by a grammar, where the grammar is a user defined data
structure that determines the meaning of the final vertex ranking. The ideas in
this article are presented within the context of the Resource Description
Framework (RDF) of the Semantic Web initiative.Comment: First draft of manuscript originally written in November 200
Linked Data for the Natural Sciences. Two Use Cases in Chemistry and Biology
Wiljes C, Cimiano P. Linked Data for the Natural Sciences. Two Use Cases in Chemistry and Biology. In: Proceedings of the Workshop on the Semantic Publishing (SePublica 2012). 2012: 48-59.The Web was designed to improve the way people work together. The Semantic Web extends the Web with a layer of Linked Data that offers new paths for scientific publishing and co-operation. Experimental raw data, released as Linked Data, could be discovered automatically, fostering its reuse and validation by scientists in different contexts and across the boundaries of disciplines. However, the technological barrier for scientists who want to publish and share their research data as Linked Data remains rather high. We present two real-life use cases in the fields of chemistry and biology and outline a general methodology for transforming research data into Linked Data. A key element of our methodology is the role of a scientific data curator, who is proficient in Linked Data technologies and works in close co-operation with the scientist
Demonstration of a customizable knowledge graph visualization framework
In the context of the Semantic Web, various visualization methods and tools exist. However, suitable visualizations are highly de-pendent on individual use cases and targeted user groups. Therefore, existing solutions require modifications and adjustments to meet the de-mands of other use cases and user groups. In this demo, we present an approach for a unified framework addressing customizable visual rep-resentations of knowledge graphs. Our approach refines the commonly used steps in the visualization generation process (i.e., data access, map-ping to visual primitives, and rendering) for Semantic Web contexts. Separation of concerns for individual steps and a modular and customiz-able architecture build the foundation for a pipeline-based visualization framework. The framework enables the creation and selection of the right components for the right tasks, realizing a variety of use cases and visual representations in Semantic Web contexts
Semantic Tagging on Historical Maps
Tags assigned by users to shared content can be ambiguous. As a possible
solution, we propose semantic tagging as a collaborative process in which a
user selects and associates Web resources drawn from a knowledge context. We
applied this general technique in the specific context of online historical
maps and allowed users to annotate and tag them. To study the effects of
semantic tagging on tag production, the types and categories of obtained tags,
and user task load, we conducted an in-lab within-subject experiment with 24
participants who annotated and tagged two distinct maps. We found that the
semantic tagging implementation does not affect these parameters, while
providing tagging relationships to well-defined concept definitions. Compared
to label-based tagging, our technique also gathers positive and negative
tagging relationships. We believe that our findings carry implications for
designers who want to adopt semantic tagging in other contexts and systems on
the Web.Comment: 10 page
requirements and use cases
In this report, we introduce our initial vision of the Corporate Semantic Web
as the next step in the broad field of Semantic Web research. We identify
requirements of the corporate environment and gaps between current approaches
to tackle problems facing ontology engineering, semantic collaboration, and
semantic search. Each of these pillars will yield innovative methods and tools
during the project runtime until 2013. Corporate ontology engineering will
improve the facilitation of agile ontology engineering to lessen the costs of
ontology development and, especially, maintenance. Corporate semantic
collaboration focuses the human-centered aspects of knowledge management in
corporate contexts. Corporate semantic search is settled on the highest
application level of the three research areas and at that point it is a
representative for applications working on and with the appropriately
represented and delivered background knowledge. We propose an initial layout
for an integrative architecture of a Corporate Semantic Web provided by these
three core pillars
Semantics of the internet: a political history
The history of the Internet has been narrated many times. However, political histories of the Internet with a non-US-centric focus are still an uncharted research area. This paper contributes to closing that research gap. It reconstructs the Internet’s history in Germany through the lens of semantic changes in press coverage on politics. In our investigation, we sought to analyse semantic change as a political history by drawing on insights concerning the relationship between semantic change and political conflict from the perspective of discourse theory and theoretical reflections on politicisation. The study follows our intuition that semantic struggles of the past leave traces in word contexts. Conversely, it uncovers semantic change by following the traces of semantic struggles in these contexts. In line with this rationale, we conducted a ‘blended reading’ of word contexts that relied on a quantitatively assisted qualitative text analysis. The study finds that the Internet has long been understood predominantly as a tool for politics in the political public. In the late 2000s, its perception as a highly politicised object of governance also became dominant. While the Internet was always associated with a medium and a public sphere, its characterisation changed from ‘web 1.0’ to a ‘web of corporations’
cTag: Semantic Contextualisation of Social Tags
Also published online by CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) Proceedings of the Workshop on Semantic Adaptive Social Web 2011In this paper, we present an algorithmic framework to identify the
semantic meanings and contexts of social tags within a particular folksonomy,
and exploit them for building contextualised tag-based user and item profiles.
We also present its implementation in a system called cTag, with which we
preliminary analyse semantic meanings and contexts of tags belonging to
Delicious and MovieLens folksonomies.This work was supported by the Spanish Ministry of Science and Innovation
(TIN2008-06566-C04-02), and the Regional Government of Madrid (S2009TIC-
1542)
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