INTRODUCTORY CONCEPTS HYPERGRAPH-BASED Data Structures are built on four fundamental concepts, which taken together are sufficient to describe any real world phenomenon: object, class, attribute, and relation. The concepts combine to form the six basic 'abstract data types' of the HBDS model: object, class, attribute of object, attribute of class, relation between objects, relation between clas...

ion of High Level Concepts from Numerical Values in Databases Wesley W. Chu and Kuorong Chiang y Computer Science Department University of California, Los Angeles Abstract A conceptual clustering method is proposed for discovering high level concepts of numerical attribute values from databases. The method considers both frequency and value distributions of data, thus is able to discover releva...

In this paper, we offer a geometric framework for the computing of a concept’s conceptual vector based on its similarity position with other concepts in a vector space called concept space, which is a set of concept vectors together with a distance function derived from a similarity model. We show that there exists an isometry to map a concept space to a Euclidean space. So, the concept vector ...

This paper describes a simple Prolog-based knowledge representation language called XI – X for cross-classification and I for inheritance – which is designed to represent knowledge about individuals, about classes of individuals, and about inclusion relations between classes of individuals. XI allows for straightforward definitions of cross-classification hierarchies and for the association of ...

This paper presents a conceptual framework and a process model for feature extraction and iconic visualization. Feature extraction is viewed as a process of data abstraction, which can proceed in multiple stages and corresponding data abstraction levels. The features are represented by attribute sets, which play a key role in the visualization process. Icons are symbolic parametric objects, des...

A conceptual clustering program CLUSTER3 is described that, given a set of objects represented by attribute-value tuples, groups them into clusters described by generalized conjunctive descriptions in attributional calculus. The descriptions are optimized according to a user-designed multi-criterion clustering quality measure. The clustering process in CLUSTER3 depends on a viewpoint underlying...

The paper presents a Construction Database Model (CDM) used for the conceptual level modelling of design objects. A primary intention of the CDM model is modelling hierarchically structured objects and construction dependencies among objects. CDM is an attribute based data model. The CDM model represents various abstractions identiied in the semantic database models GSM, IFO, SAM* and FDM by me...

In this paper, we use context to simplify the translation from system's requirements expressed in natural language to conceptual model (Entity-Relationship Model). This translation is made by a tool called Designer Assistant. The goal of the system is to identify entities, attributes and relationships from requirements expressed in natural language (Portuguese Language in our case) of a databas...

Formal Concept Analysis (FCA) is a prominent field of applied mathematics using object-attribute relationships to define formal concepts – groups of objects with common attributes – which can be ordered into conceptual hierarchies, so-called concept lattices. We consider the problem of satisfiability of membership constraints, i.e., to determine if a formal concept exists whose object and attri...

This work presents an application of the highly expressive Attribute-Based Encryption to implement wirelessdelimited Secure Zones for firearms. Within these zones, radiotransmitted local policies based on attributes of the consumer and the firearm are received by embedded hardware in the firearms, which then advises the consumer about safe operations. The Secure Zones utilize Attribute-Based En...