bookmarks (hide)130
- The OWL API is a Java API and reference implmentation for creating, manipulating and serialising OWL Ontologies. The latest version of the API is focused towards OWL 2
- Martyn Plummer April 23, 2009
- OpenMath symbols as an OWL ontology. (MONET project)
- Welcome to the OpenMath website. OpenMath is an extensible standard for representing the semantics of mathematical objects. If you haven't heard about it before you might want to consult the overview.
- This is the report of the W3C Uncertainty Reasoning for the World Wide Web Incubator Group (URW3-XG) as specified in the Deliverables section of its charter. In this report we present requirements for better defining the challenge of reasoning with and representing uncertain information available through the World Wide Web and related WWW technologies. Specifically the report: * identifies and describes situations on the scale of the World Wide Web for which uncertainty reasoning would significantly increase the potential for extracting useful information, * identifies methodologies that can be applied to these situations and the fundamentals of a standardized representation that could serve as the basis for information exchange necessary for these methodologies to be effectively used, * includes a set of use cases illustrating conditions under which uncertainty reasoning is important, * provides an overview and discusses the applicability to the World Wide Web of prominent uncertainty reasoning techniques and the information that needs to be represented for effective uncertainty reasoning to be possible, * includes a bibliography of work relevant to the challenge of developing standardized representations for uncertainty and exploiting them in Web-based services and applications. The report identifies various areas which require further investigation and debate.
- Abstract. The envisioned Semantic Web aims to provide richly annotated and explicitly structured Web pages in XML, RDF, or description logics, based upon underlying ontologies and thesauri. Ideally, this should enable a wealth of query processing and semantic reasoning capabilities using XQuery and logical inference engines. However, we believe that the diversity and uncertainty of terminologies and schema-like annotations will make precise querying on a Web scale extremely elusive if not hopeless, and the same argument holds for large-scale dynamic federations of Deep Web sources. Therefore, ontology-based reasoning and querying needs to be enhanced by statistical means, leading to relevanceranked lists as query results. This paper presents steps towards such a “statistically semantic”Web and outlines technical challenges.We discuss how statistically quantified ontological relations can be exploited in XML retrieval, how statistics can help in making Web-scale search efficient, and how statistical information extracted from users’ query logs and click streams can be leveraged for better search result ranking. We believe these are decisive issues for improving the quality of next-generation search engines for intranets, digital libraries, and the Web, and they are crucial also for peer-to-peer collaborative Web search.
- Bayesian Networks are probabilistic structured representations of domains which have been applied to monitoring and manipulating cause and effects for modelled systems as disparate as the weather, disease and mobile telecommunications networks. Although useful, Bayesian Networks are notoriously difficult to build accurately and efficiently which has somewhat limited their application to real world problems. Ontologies are also a structured representation of knowledge, encoding facts and rules about a given domain. This paper outlines an approach to harness the knowledge and inference capabilities inherent in an ontology model to automate the construction of Bayesian Networks to accurately represent a domain of interest. The approach was implemented in the context of an adaptive, self-configuring network management system in the telecommunications domain. In this system, the ontology model has the dual function of knowledge repository and facilitator of automated workflows and the generated BN serves to monitor effects of management activity, forming part of a feedback look for self-configuration decisions and tasks.
- "a special issue of Nature examines the cultural and technical hurdles that can get in the way of good intentions"
- author: Ole Winther, Technical University of Denmark
- Two-way latent grouping model for user preference prediction Eerika Savia, Kai Puolamäki, Janne Sinkkonen and Samuel Kaski In: UAI 2005, 26-29 July 2005, Edinburgh, Scotland.
- Fang Wu and Bernardo A. Huberman HP Laboratories Palo Alto, CA 94304 January 23, 2008 Abstract We analyze the role that popularity and novelty play in attracting the attention of users to dynamic websites. We do so by determining the performance of three different strategies that can be utilized to maximize attention. The first one prioritizes novelty while the second emphasizes popularity. A third strategy looks myopically into the future and prioritizes stories that are expected to generate the most clicks within the next few minutes. We show that the first two strategies should be selected on the basis of the rate of novelty decay, while the third strategy performs sub-optimally in most cases. We also demonstrate that the relative performance of the first two strategies as a function of the rate of novelty decay changes abruptly around a critical value, resembling a phase transition in the physical world.
- Incorporating Evidence in Bayesian Networks with the Select Operator - all 4 versions » CJ Butz, F Fang - Advances in Artificial Intelligence: 18th Conference of the …, 2005 - books.google.com
- Recommendations for learners are different: Applying memory-based recommender system techniques to lifelong learning
- SUGGEST is a Top-N recommendation engine that implements a variety of recommendation algorithms. Top-N recommender systems, a personalized information filtering technology, are used to identify a set of N items that will be of interest to a certain user.
- Building, Sharing, and Merging Ontologies John F. Sowa
- "Information foraging is a theory that applies the ideas from optimal foraging theory to understand how human users search for information."
- Our in intention is to construct a repository that will allow us empirical research within our community by facilitating (1)better reproducibility of results, and (2) better comparisons among competing approach. Both of these are required to measure progress on problems that are commonly agreed upon, such as inference and learning
- "In Semantic Web languages, such as RDF and OWL, a property is a binary relation: it is used to link two individuals or an individual and a value. However, in some cases, the natural and convenient way to represent certain concepts is to use relations to link an individual to more than just one individual or value. These relations are called n-ary relations. For example, we may want to represent properties of a relation, such as our certainty about it, severity or strength of a relation, relevance of a relation, and so on. Another example is representing relations among multiple individuals, such as a buyer, a seller, and an object that was bought when describing a purchase of a book. This document presents ontology patterns for representing n-ary relations in RDF and OWL and discusses what users must consider when choosing these patterns."
- "This page is an ongoing attempt to survey current efforts directed at understanding and improving interfaces for Personal Information Management (PIM for short), defined as: the collecting and handling of information (such as files, email and contacts) by an individual, for that individual's own use."
- Prem Melville and Raymond J. Mooney and Ramadass Nagarajan. Content-Boosted Collaborative Filtering for Improved Recommendations. Proceedings of the Eighteenth National Conference on Artificial Intelligence(AAAI-2002), pp. 187-192, Edmonton, Canada, July 2002
- Social Network Analysis: A Handbook By John Scott
- Buddycast provides decentralized, user-based collaborative filterin
- Recommender Systems 2007 October 19-20, 2007 -- Minneapolis, Minnesota, USA
publications (hide)739
- (2010)cite arxiv:1006.2761.
- BMC Bioinformatics, 11 (1): 255 (2010)
- BMC Bioinformatics, 11 (1): 292 (2010)
- (2010)cite arxiv:1006.0408.
- Nucleic Acids Res, 31 (19): 5789-5804 (October 2003)
- Nucl. Acids Res., 37 (suppl_1): D417-422 (2009)
- PAKDD, volume 5476 of Lecture Notes in Computer Science, page 628-636. Springer, (2009)
- (2010)
- v11, (1771)
- v11, (1709)
- v11, (1663)
- v11, (1643)
- BMC Bioinformatics, 11 (1): 271 (2010)
- Proceedings of the 6th International Semantic Web Conference (ISWC), volume 4825 of Lecture Notes in Computer Science, page 722--735. Springer, (2008)
- Proceedings Thirteenth Conference on Uncertainty in Artificial Intelligence (UAI), page 302--313. (1997)
- Drug Discov Today, 10 (13): 937-942 (July 2005)
- Technical Report, SMI-2001-0880. Stanford Medical Informatics, Stanford, (2001)
- CIMCA '05: Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06), page 457--463. Washington, DC, USA, IEEE Computer Society, (2005)
- Soft Computing in Ontologies and Semantic Web, (2006)
- Journal of Artificial Intelligence Research, (1994)
