Cluster ensemble is an effective method to improve the effect in data clustering, but the results of the existing cluster ensemble algorithms are usually not so good when they process the mixed attributes datas, the main reason is that the results of the algorithms are still dispersed. To solve this problem, this paper presents a new weighted cluster ensemble algorithm based on graph theory. It first clusters the datasets and gets cluster members, and then sets weights to each data object with a proposed ensemble function, and determines the relationship between the data-pair by setting weights to the edges between them, so it can get a weighted nearest neighbor graph. At last it does a last-clustering based on graph theory. Experiments show that the accuracy and stability of this cluster ensemble algorithm is better than other clustering ensemble algorithms.

In this article, we present a new fingerprint classification algorithm. Singular points are first extracted from enhanced fingerprint direction images with a resolution of 2 × 2 pixels by the modified SEA algorithm. Based on the number of singular points, fingerprints are categorized into types of "arch", "whorl", and "solitary". Solitary fingerprints are properly rotated and then further processed to generate direction patterns that lead to establishment of individual direction template. Direction constraints are formed and derived from pattern descriptors by their structural layout. Decision rules are then established and pattern templates are classified into three more types: "right loop", "left loop", and "tented arch". NIST-4 database was used for an experimental test, and our classification accuracy was 91.62% with 1.55% rejection on the five-class system (94.38% on the four-class system), which is the best result on the five-class system to-date. An additional experiment on NIST-14 database reports 89.15% accuracy with 3.07% rejection.

Abstract A semantic relationship is a data modeling construct that connects a pair of classes or categories and has inherent constraints and other functionalities that precisely reflect the characteristics of the specific relationship in an application domain. Examples of semantic relationships include part–whole, ownership, materialization and role‐of. Such relationships are important in the construction of information models for advanced applications, whether one is employing traditional data‐modeling techniques, knowledge‐representation languages or object‐oriented modeling methodologies. This paper focuses on the issue of providing built‐in support for such constructs in the context of object‐oriented database (OODB) systems. Most of the popular object‐oriented modeling approaches include some semantic relationships in their repertoire of data‐modeling primitives. However, commercial OODB systems, which are frequently used as implementation vehicles, tend not to do the same. We will present two frameworks by which a semantic relationship can be incorporated into an existing OODB system. The first only requires that the OODB system support manifest type with respect to its instances. The second assumes that the OODB system has a special kind of metaclass facility. The two frameworks are compared and contrasted. In order to ground our work in existing systems, we show the addition of a part–whole semantic relationship both to the ONTOS DB/Explorer OODB system and the VODAK Model Language. Copyright © 2003 John Wiley & Sons, Ltd.

Abstract In previous work, we have modeled a vocabulary given as a semantic network by an object‐oriented database (OODB). The OODB schema thus obtained provides a compact abstract view of the vocabulary. This enables the fast traversal of the vocabulary by a user. In the semantic network vocabulary, the IS‐A relationships express the specialization hierarchy. In our OODB modeling of the vocabulary, the SUBCLASS relationship expresses the specialization hierarchy of the classes and supports the inheritance of their properties. A typical IS‐A path in the vocabulary has a corresponding shorter SUBCLASS path in the OODB schema. In this paper we expose several cases where the SUBCLASS hierarchy fails to fully correspond to the IS‐A hierarchy of the vocabulary. In these cases there exist traversal paths in the semantic network for which there are no corresponding traversal paths in the OODB schema. The reason for this failure is the existence of some IS‐A relationships between concepts of two classes, which are not connected by a SUBCLASS relationship. This phenomenon weakens the accuracy of our modeling. To rectify the situation we introduce a new OODB semantic relationship IS‐A$'$ to represent the existence of IS‐A relationships between concepts of a pair of classes which are not connected via a SUBCLASS relationship. The resulting schema contains both SUBCLASS relationships and IS‐A$'$ relationships which completely model the IS‐A hierarchy of the vocabulary. We define a mixed‐class level traversal path to contain either SUBCLASS or IS‐A$'$ relationships. Consequently, each traversal path in the semantic network has a corresponding mixed traversal path in the OODB schema. Hence the introduction of the semantic OODB IS‐A$'$ relationship improves the modeling of semantic network vocabularies by OODBs. Copyright © 2003 John Wiley & Sons, Ltd.

Controlled vocabularies (CVs) are networks of concepts that unify disparate terminologies and facilitate the process of information sharing within an application domain. We describe a general methodology for representing an existing CV as an object-oriented database (OODB), called an object-oriented vocabulary repository (OOVR). A formal description of the OOVR methodology, which is based on a structural abstraction technique, is given, along with an algorithmic description and a number of theorems pertaining to some of the methodology's formal characteristics. An OOVR offers a two-level (concept level and schema level) view of a CV, with the schema-level view serving as an important abstraction that can aid in orientation to the CV's contents. While an OOVR can also assist in traversals of the CV, we have identified certain special CV configurations where such traversals can be problematic. To address this, we introduce - based on the original methodology - an enhanced OOVR methodology that utilizes both structural and semantic features to partition and model a CV's constituent concepts. With its basis in the notions of area and the recursively defined articulation concept, an enhanced OOVR representation provides users with an improved CV view comprising groups of concepts that are uniform both in their structure and semantics. An algorithmic description of the singly-rooted OOVR methodology and theorems describing some of its formal properties are given. The results of applying it to a large existing CV are discussed.

OBJECTIVE: The Unified Medical Language System (UMLS) combines many well-established authoritative medical informatics terminologies in one knowledge representation system. Such a resource is very valuable to the health care community and industry. However, the UMLS is very large and complex and poses serious comprehension problems for users and maintenance personnel. The authors present a representation to support the user's comprehension and navigation of the UMLS. DESIGN: An object-oriented database (OODB) representation is used to represent the two major components of the UMLS-the Metathesaurus and the Semantic Network-as a unified system. The semantic types of the Semantic Network are modeled as semantic type classes. Intersection classes are defined to model concepts of multiple semantic types, which are removed from the semantic type classes. RESULTS: The authors provide examples of how the intersection classes help expose omissions of concepts, highlight errors of semantic type classification, and uncover ambiguities of concepts in the UMLS. The resulting UMLS OODB schema is deeper and more refined than the Semantic Network, since intersection classes are introduced. The Metathesaurus is classified into more mutually exclusive, uniform sets of concepts. The schema improves the user's comprehension and navigation of the Metathesaurus. CONCLUSIONS: The UMLS OODB schema supports the user's comprehension and navigation of the Metathesaurus. It also helps expose and resolve modeling problems in the UMLS.

Controlled vocabularies have been used as the means for unifying disparate terminologies found within an application field. This unification leads to better administration of information and enhanced communication among various parties. Semantic networks have been shown to be excellent vehicles for modeling controlled vocabularies. However, they often lack the necessary access flexibility and robustness required by external agents such as intelligent information-locators and decision-support systems. In this paper, we describe the process of mapping an existing medical vocabulary based on a semantic network model into an Object-Oriented Database (OODB) system. We first consider two straightforward approaches to carrying out this task and describe their deficiencies. We then present a new approach which yields a very compact OODB schema for the representation of the vocabulary's entire hierarchy and inter-connectivity. We refer to the resulting OODB as the Object-Oriented Healthcare Voc...