448895
Search on the Semantic Web
To help human users and software agents find relevant knowledge on the Semantic Web, the Swoogle search engine discovers, indexes, and analyzes the ontologies and facts that are encoded in Semantic Web documents.
7138939
A probabilistic extension to ontology language OWL
To support uncertain ontology representation and ontology reasoning and mapping, we propose to incorporate Bayesian networks (BN), a widely used graphic model for knowledge representation under uncertainty and OWL, the de facto industry standard ontology language recommended by W3C. First, OWL is augmented to allow additional probabilistic markups, so probabilities can be attached with individual concepts and properties in an OWL ontology. Secondly, a set of translation rules is defined to convert this probabilistically annotated OWL ontology into the directed acyclic graph (DAG) of a BN. Finally, the BN is completed by constructing conditional probability tables (CPT) for each node in the DAG. Our probabilistic extension to OWL is consistent with OWL semantics, and the translated BN is associated with a joint probability distribution over the application domain. General Bayesian network inference procedures (e.g., belief propagation or junction tree) can be used to compute P(C/spl bsol/e): the degree of the overlap or inclusion between a concept C and a concept represented by a description e. We also provide a similarity measure that can be used to find the most similar concept that a given description belongs to.
1517191
Semantic resolution for e-commerce
We describe a research project on resolving semantic differences for multi-agent systems (MAS) in electronic commerce. The approach can be characterized as follows: (1) agents in a MAS may have their own specific ontologies defined on top of a shared base ontology; (2) concepts in these ontologies are represented as frame-like structures based on DAML+OIL language; (3) the semantic differences between agents are resolved at runtime through inter-agent communication; and (4) the resolution is viewed as an abductive inference process, and thus necessarily involves approximate reasoning.
183316
Modifying Bayesian Networks by Probability Constraints
This paper deals with the following problem: modify a Bayesian network to satisfy a given set of probability constraints by only change its conditional probability tables, and the probability distribution of the resulting network should be as close as possible to that of the original network. We propose to solve this problem by extending IPFP (iterative proportional fitting procedure) to probability distributions represented by Bayesian networks. The resulting algorithm E-IPFP is further developed to D-IPFP, which reduces the computational cost by decomposing a global E-IPFP into a set of smaller local E-IPFP problems. Limited analysis is provided, including the convergence proofs of the two algorithms. Computer experiments were conducted to validate the algorithms. The results are consistent with the theoretical analysis.
47142619
Semantic Resolution for E-commerce
We describe a research project on resolving semantic differences for multi-agent systems (MAS) in electronic commerce. The approach can be characterized as follows: (1) agents in a MAS may have their own specific ontologies defined on top of a shared base ontology; (2) concepts in these ontologies are represented as frame-like structures based on DAML+OIL language; (3) the semantic differences between agents are resolved at runtime through inter-agent communication; and (4) the resolution is viewed as an abductive inference process, and thus necessarily involves approximate reasoning.
723568
A Bayesian Network Approach to Ontology Mapping
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs. Probabilities needed for constructing conditional probability tables (CPT) during translation and for measuring semantic similarity during mapping are learned using text classification techniques where each concept in an ontology is associated with a set of semantically relevant text documents, which are obtained by ontology guided web mining. The basic ideas of this approach are validated by positive results from computer experiments on two small real-world ontologies.
42745
The chromaticity of s-bridge graphs and related graphs
Abstract The graph consisting of s paths joining two vertices is called s -bridge graph. In this paper, we discuss the chromaticity of some families of s -bridge graphs, especially 4-bridge graphs, and some graphs related to s -bridge graphs.
36490919
Estimating baseline distribution in proportional hazards cure models
Semiparametric proportional hazards cure models have been proposed recently for survival data from some clinical trials where cure is a possibility. However, it is known that the estimated baseline distribution in the proposed methods will not be proper if there is no restriction on the tail of the distribution, which leads to the identifiability problem. In this work, we investigate several methods that impose restrictions on the tail of the baseline distribution. A simulation study shows that the proposed methods are useful in reducing estimation errors in the cure models. The impact of the different methods on the estimation of regression parameters and survival probabilities of patients who are not cured is detailed in the paper. The results provide useful guidelines for practitioners to select appropriate estimation methods for the semiparametric cure model. The application of the results is illustrated with a real data set from a clinical trial of breast cancer.
18522080
Example of supersonic solutions to a steady state Euler-Poisson system
Abstract We give an example of supersonic solutions to a one-dimensional steady state Euler–Poisson system arising in the modeling of plasmas and semiconductors. The existence of the supersonic solutions which correspond to large current density is proved by Schauder’s fixed point theorem. We show also the uniqueness of solutions in the supersonic region.
18457324
On the higher-order edge toughness of a graph
For an integer c, 1?c??V(G)??1, we define the cth-order edge toughness of a graph G as tc(G)=min|X|?(G?X)?cX?E(G) & ?(G?X)>c The objective of this paper is to study this generalized concept of edge toughness. Besides giving the of the cth-order edge toughness ?c(G) of a graph G, we prove that `?c(G)?k if and only if G has k edge-disjoint spanning forests with exactly c components?. We also study the `balancity? of a graph G of order p and size q, which is defined as the smallest positive integer c such that ?c(G) = p/(p?c).
14722098
TCS-Chord: An Improved Routing Algorithm to Chord Based on the Topology-aware Clustering in Self-organizing Mode
The study on semantic routing efficiency of DHTP2P networks is a key element to promote the development of P2P networks, it is critical for a P2P routing algorithm to be aware of the network physical topology, which leads to improvement of the routing efficiency. By analyzing the Hashing function's properties, some novel logical connections are presented among the destination node, the Chord semantic routing relay node sequence, and the ID of clustering neighbor nodes. This paper describes TCS-Chord (an improved routing algorithm to Chord based on the Topology-aware Clustering in Self-organizing mode) to improve the efficiency of Chord routing. Since the clustering nodes only have local views in the self-organizing mode, some rules are applied for a node to learn other nodes' physical topology-aware locations. The TCS-Chord's routing algorithm is described completely, and our experiments also indicate that TCS-Chord can improve the Chord semantic routing efficiently.