Enabling Context-aware Smart Home with Semantic Web
Technologies
Daqing Zhang, Tao Gu, Xiaohang Wang
Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613
{daqing, tgu, xwang}@i2r.a-star.edu.sg
Abstract. Context-awareness has emerged as a key enabling technology for
future smart homes. In this paper, we propose a generic layered model (the
Context Stack) to guide the context-aware system design. We investigate the
use of Semantic Web technologies in context modeling and reasoning. A Web
Ontology based context model (CONON) is defined to facilitate explicit context
representation, semantic context sharing, and logic reasoning. We show how the
use of logic reasoning enables context-aware services to deduce high-level,
implicit context from low-level, explicit context. In particular, we integrate the
temporal ontology into our ontology model to facilitate annotating and
reasoning about temporal context information. Following the general layered
model, we present an OSGi-based context-aware service architecture for smart
homes. We also build the smart home prototype with context-aware services.
Index Terms:. Context-awareness, smart home, semantic web, ontology
Mining the Web to Create Specialized Glossaries
An Ontological Software Comprehension Process Model
An ontology for software component matching
Technologies
Daqing Zhang, Tao Gu, Xiaohang Wang
Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613
{daqing, tgu, xwang}@i2r.a-star.edu.sg
Abstract. Context-awareness has emerged as a key enabling technology for
future smart homes. In this paper, we propose a generic layered model (the
Context Stack) to guide the context-aware system design. We investigate the
use of Semantic Web technologies in context modeling and reasoning. A Web
Ontology based context model (CONON) is defined to facilitate explicit context
representation, semantic context sharing, and logic reasoning. We show how the
use of logic reasoning enables context-aware services to deduce high-level,
implicit context from low-level, explicit context. In particular, we integrate the
temporal ontology into our ontology model to facilitate annotating and
reasoning about temporal context information. Following the general layered
model, we present an OSGi-based context-aware service architecture for smart
homes. We also build the smart home prototype with context-aware services.
Index Terms:. Context-awareness, smart home, semantic web, ontology
Mining the Web to Create Specialized Glossaries
Presenter: TBD
Glossaries are helpful for integrating information, reducing semantic heterogeneity, and facilitating communication between information systems. Commercial publishers charge lexicographers with building glossaries, but this isn't appropriate when a domain's semantics are continuously evolving rather than precisely characterized, as in emerging Web communities and interest groups. In emerging domains, glossary building is the cooperative effort of a team of domain experts. It involves several steps, including identifying the domain-relevant terminology, defining each term, and harmonizing the results. This is a time-consuming, costly process that often requires support from a collaborative platform to facilitate shared decisions and validation. TermExtractor and GlossExtractor, two Web applications based on Web mining techniques, support this complete glossary-building procedure. The tools exploit the Web's evolving nature, allowing one to continually update the emerging community's vocabulary. TermExtractor and GlossExtractor, which were used in the European project Interop, are freely available and are being used in experiments in different domains across the world. This article is part of a special issue on Natural Language Processing and the Web.
Learning to Tag and Tagging to Learn: A Case Study on Wikipedia
Presenter: TBD
Natural language technologies have long been envisioned to play a crucial role in developing a Semantic Web. Textual content's significance on the Web has increased with the rise of Web 2.0 and mass participation in content generation. Yet, natural language technologies face great challenges in dealing with Web content's heterogeneity: key among these is domain and task adaptation. To address this challenge, the authors consider the problem of semantically annotating Wikipedia. Specifically, they investigate a method for dealing with domain and task adaptation of semantic taggers in cases where parallel text and metadata are available. By creating a semantic mapping among vocabularies from two sources: Wikipedia and the original annotated corpus, they improve their tagger on Wikipedia. Moreover, by applying their tagger and mapping between sources, they significantly extend the metadata currently available in the DBpedia collection. This article is part of a special issue on Natural Language Processing and the Web.
Linking Documents to Encyclopedic Knowledge
Presenter: TBD
Wikipedia can support the development of automatic methods for keyword extraction and word-sense disambiguation. The Wikify system combines these two methods to automatically enrich a text with links to Wikipedia content. The system identifies the important concepts in a given document and automatically links these concepts to the corresponding Wikipedia pages. An evaluation of the system using a Turing-like test shows that the automatic annotations are hardly distinguishable from manual annotations. A second evaluation in an educational environment shows that enriching educational materials with such annotations can improve the learning process by allowing faster access to background knowledge. This article is part of a special issue on Natural Language Processing and the Web.
Web Semantics in the Clouds
Presenter: TBD
Cloud Computing refers to the use of large-scale computer clusters often built from low-cost hardware and network equipment, where resources are allocated dynamically among users of the cluster. While the paradigm is not entirely novel, recent developments in software frameworks for Cloud Computing are making it increasingly easy for programmers to parallelize and thereby scale-up complex data-processing tasks. This article investigates how this trend is impacting the Semantic Web field and shows how Cloud Computing can be used to analyze, query, and reason with the massive amounts of metadata handled by semantic search engines.
Presenter: TBD
Comprehension is an essential part of software maintenance. Only software that is well understood can evolve in a controlled manner. In this paper, we present a formal process model to support the comprehension of software systems by using Ontology and Description Logic. This formal representation supports the use of reasoning services across different knowledge resources and therefore, enables us to provide users with guidance during the comprehension process that is context sensitive to their particular comprehension task.
@InProceedings{MRZWC_ATEM2006,
author = {Wen Jun Meng and Juergen Rilling and Yonggang Zhang
and Ren{\'e} Witte and Philippe Charland},
title = {{An Ontological Software Comprehension Process Model}},
booktitle = {3rd Int.\ Workshop on Metamodels, Schemas, Grammars,
and Ontologies for Reverse Engineering (ATEM 2006)},
year = {2006},
address = {Genoa, Italy},
month = {October 1st}
}An ontology for software component matching
Presenter: CRAP
Matching is a central activity in the discovery and assembly of reusable software components. We investigate how ontology technologies can be utilised to support software component development. We use description logics, which underlie Semantic Web ontology languages, such asOWL, to develop an ontology for matching requested and provided components. A link between modal logic and description logics will prove invaluable for the provision of reasoning support for component behaviour.
@article{1230650,
author = {Claus Pahl},
title = {An ontology for software component matching},
journal = {Int. J. Softw. Tools Technol. Transf.},
volume = {9},
number = {2},
year = {2007},
issn = {1433-2779},
pages = {169--178},
doi = {http://dx.doi.org/10.1007/s10009-006-0015-9},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
}
Presenter: TBD
Date: Monday, 22 September 2008
Many real-world tasks require the acquisition and integration of information from a distributed set of heterogeneous sources. Hence, there’s no shortage of opportunities for applications using Semantic Web (SW) technologies. The power of publishing and linking data in a way that machines can automatically interpret through ontologies is beginning to materialize. 1 However, market penetration level is relatively low, and it’s still no routine matter for an enterprise, organization, governmental agency, or business with large distributed databases to add them to the Web of linked and semantically enriched data. It’s also probably fair to say that many organizations still view the SW with some skepticism. In part, they may suspect that they’re expected to pioneer an approach in which quick wins are few. Moreover, cost and privacy issues arise when ever-increasing amounts of information are linked into the Web.
@article{10.1109/MIS.2008.42,
author = {Harith Alani and Peter Chandler and Wendy Hall and Kieron O'Hara and Nigel Shadbolt and Martin Szomszor},
title = {Building a Pragmatic Semantic Web},
journal = {IEEE Intelligent Systems},
volume = {23},
number = {3},
year = {2008},
issn = {1541-1672},
pages = {61-68},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
Efficient Content Creation on the Semantic Web Using
Presenter: TBD
Metadata creation is one of the major challenges in developing the Semantic Web. This paper discusses how to make provision of metadata easier and costeffective by an annotation editor combined with shared ontology services. We have developed an annotation system supporting distributed collaboration in creating annotations, and hiding the complexity of the annotation schema and the domain ontologies from the annotators. Our system adapts flexibly to different metadata schemas, which makes it suitable for different applications. Support for using ontologies is based on ontology services, such as concept searching and browsing, concept URI fetching, semantic autocompletion and linguistic concept extraction. The system is being tested in various practical semantic portal projects.
Empowering Software Maintainers
Presenter: TBD
From Reality to Programs and (Not Quite) Back Again
Presenter: TBD
Integrating Folksonomies with the Semantic Web
Presenter: TBD
Interlinking the Social Web with Semantics
Presenter: CRAP -- but had very nice graphics!
One of the most visible trends on the Web is the emergence of Social Web sites, which help people create and gather knowledge by simplifying user contributions via blogs, tagging and folksonomies, wikis, podcasts, and online social networks. Current online-community sites are isolated from one another, like islands in a sea. Various discussions might contain complementary knowledge and discussions—parts of the answer a person is looking for—but people participating in one discussion can't readily access information about related discussions elsewhere. The potential synergies among many sites, communities, and services are expensive to exploit, and their data are difficult and cumbersome to link and reuse. The main reason for this lack of interoperation is that for the most part in the Social Web, common standards still don't exist for knowledge and information exchange and interoperation. However, the Semantic Web effort aims to provide the tools needed to define extensible, flexible standards for this purpose. The Semantic Web technology stack is well defined, enabling the creation of metadata and associated vocabularies. The Semantic Web effort is in an ideal position to make Social Web sites interoperable. Applying Semantic Web frameworks including SIOC (Semantically Interlinked Online Communities) and FOAF (Friend-of-a-Friend) to the Social Web can lead to a Social Semantic Web, creating a network of interlinked and semantically rich knowledge. This article is part of a special issue called Semantic Web Update.
@article{10.1109/MIS.2008.50,
author = {Uldis Bojārs and John G. Breslin and Vassilios Peristeras and Giovanni Tummarello and Stefan Decker},
title = {Interlinking the Social Web with Semantics},
journal = {IEEE Intelligent Systems},
volume = {23},
number = {3},
year = {2008},
issn = {1541-1672},
pages = {29-40},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
Media, Politics and the Semantic Web
Presenter: TBD
Owl for the Novice- a Logical Perspective
Presenter: TBD
Ontological Text Mining of Software Documents
Presenter: Parisa Rashidi
Ontology- Use and Abuse
Presenter: TBD
Semantic Web- The Story So Far
Presenter: CRAP (somebody's keynote address) 
Semantic web services selection improved by application ontology with multiple concept
relations
Semantics and CBIR- a medical imaging perspective
Presenter: Parisa Rashidi
Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes. On the other hand, semantics in the medical domain is much better defined and there is a vast accumulation of formal knowledge representations that could be exploited to support semantic search for any specialty areas in medicine.
In this paper, however, we will not dwell on any one particular specialty area, but rather address the question of how to support scalable semantic search across the whole of medical CBIR field: what are the advantages to take and gaps to fill, what are the key enabling technologies, and the critical success factor from an industrial point of view. In terms of enabling technologies, we discuss three aspects: 1. anatomical, disease, and contextual semantics, and their representations using ontologies; 2. scalable image analysis and tagging algorithms; and 3. ontological reasoning and its role in guiding and improving image analysis and retrieval. More specifically, for ontological representation of medical imaging semantics, we discuss the potential use of FMA, RadLex, ICD, and AIM. For scalable image analysis we present a learning-based anatomy detection and segmentation framework using distribution-free priors. It is easily adaptable to different anatomies and different imaging modalities.
Similarity of Semantic Relations
Presenter: TBD
Software maintenance seen as a knowledge management issue
Presenter: TBD
Ontology- Use and Abuse
Presenter: TBD
Supporting online problem-solving communities with the semantic web
Presenter: Rasika Mudumbai Chakravarthy
Symbol Grounding for the Semantic Web
Presenter: TBD
Techniques for Ontology Visualization
Presenter: TBD
The Evaluation of Ontologies
Presenter: TBD
The Semantic Web: Apotheosis of Annotation, but What Are Its Semantics?
Presenter: TBD
@article{10.1109/MIS.2008.53,
author = {Yorick Wilks},
title = {The Semantic Web: Apotheosis of Annotation, but What Are Its Semantics?},
journal = {IEEE Intelligent Systems},
volume = {23},
number = {3},
year = {2008},
issn = {1541-1672},
pages = {41-49},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
Toward a New Generation of Semantic Web Applications
Presenter: TBD
@article{10.1109/MIS.2008.54,
author = {Mathieu d'Aquin and Enrico Motta and Marta Sabou and Sofia Angeletou and Laurian Gridinoc and Vanessa Lopez and Davide Guidi},
title = {Toward a New Generation of Semantic Web Applications},
journal = {IEEE Intelligent Systems},
volume = {23},
number = {3},
year = {2008},
issn = {1541-1672},
pages = {20-28},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
Towards Semantic Social Networks
Presenter: TBD
Presenter : Rasika Mudumbai Chakravarthy