2672581
Debugging OWL-DL Ontologies: A Heuristic Approach
After becoming a W3C Recommendation, OWL is becoming increasingly widely accepted and used. However most people still find it difficult to create and use OWL ontologies. On major difficulty is “debugging” the ontologies – discovering why a reasoners has inferred that a class is “unsatisfiable” (inconsistent). Even for people who do understand OWL and the logical meaning of the underlining description logic, discovering why concepts are unsatisfiable can be difficult. Most modern tableaux reasoners do not provide any explanation as to why the classes are unsatisfiable. This paper presents a ‘black boxed' heuristic approach based on identifying common errors and inferences.
134895
TCOZ approach to semantic web services design
Complex Semantic Web (SW) services may have intricate data state, autonomous process behavior and concurrent interactions. The design of such SW service systems requires precise and powerful modelling techniques to capture not only the ontology domain properties but also the services' process behavior and functionalities. In this paper we apply an integrated formal modeling language, Timed Communicating Object Z (TCOZ), to design SW services. Furthermore, the paper presents the development of the systematic translation rules and tools which can automatically extract the SW ontology and services semantic markup from the formal TCOZ design model.
28149553
Fingerprint Indexing Based On Symmetrical Measurement
Due to the small number of classes and uneven distribution, the Henry's fingerprint classification approach is not able to provide an efficient way to narrow down the search when identifying a person in a large database. In this paper, three symmetrical filters are used to measure different orientation structures. We proposed a new fingerprint indexing approach based on these three symmetrical measurements. Experiments conducted on the NIST database 4 show the effectiveness of the proposed approach
611504
Utilizing histogram information
Many commercial database management systems (e.g., DB2, Oracle, etc.) make use of histograms of the value distribution of individual attributes of relations in order to make good selections of query execution plans. These histograms contain partial information about the actual distribution, such as which attribute values occur most frequently, and how often each one occurs, and what value occurs at the kth quantile when the values are sorted.In this paper, we quantitatively assess the information gain (or uncertainty reduction) due to each of these types of histogram information both individually and in combination. Correspondingly, we observe how the accuracy of estimating frequencies of individual values improves with the availability of each of these types of histogram information. We suggest guidelines for constructing histograms tailored to each individual attribute depending on the characteristics of its attribute value distribution.
5368193
Progressive modeling
Presently, inductive learning is still performed in a frustrating batch process. The user has little interaction with the system and no control over the final accuracy and training time. If the accuracy of the produced model is too low, all the computing resources are misspent. In this paper we propose a progressive modeling framework. In progressive modeling, the learning algorithm estimates online both the accuracy of the final model and remaining training time. If the estimated accuracy is far below expectation, the user can terminate training prior to completion without wasting further resources. If the user chooses to complete the learning process, progressive modeling will compute a model with expected accuracy in expected time. We describe one implementation of progressive modeling using ensemble of classifiers.
1927942
Tracking and segmenting people with occlusions by a sample consensus based method
One of the most difficult issues in visual tracking is to track people in groups, especially under occlusions. In this paper, we present a novel sample consensus based method, which utilizes both color and spatial information of human bodies, to model the appearance of people. We use this appearance model to segment and track people through occlusions. We show experimental results in several video sequences to validate the effectiveness of the proposed method.
9329231
Idea Storming Cube: A Game-based System to Support Creative Thinking
This paper describes a collaborative game-based creativity support system, idea storming cube, in support of creative thinking. It aims to make people form a creative and perspective-shift thinking habit. The system acquires knowledge from domain expert, user inputs history, and individuals in the current brainstorming group, and then provides user-, goal- and context-sensitive supports. Comparing to classic tutoring systems, it focuses more on stimulating divergent thinking. The system can be put into the basic mode or the idea generation mode in order to support different gaming objectives. A case study for preliminary evaluation of the proposed HCI tool for collaborative idea generation is also reported in this paper.