Generalization Per Category: Theory And Application

The concept of Generalization Per Category (GPO is formalized. It is shown that GPC imposes lattice structures on entity types and their subtypes. A high level application oriented data definition language based on the GPC is outlined which allows the system to derive general entity types and organize their instances. Users are freed from undue efforts in the design of databases which are about entity types with rich varieties and high populations. Effective browsing of these databases and efficient execution of frequent queries against them are achieved by using the lattice structures among the entity types and their subtypes

Formal concept matching and reinforcement learning in adaptive information retrieval

The superiority of the human brain in information retrieval (IR) tasks seems to come firstly from its ability to read and understand the concepts, ideas or meanings central to documents, in order to reason out the usefulness of documents to information needs, and secondly from its ability to learn from experience and be adaptive to the environment. In this work we attempt to incorporate these properties into the development of an IR model to improve document retrieval. We investigate the applicability of concept lattices, which are based on the theory of Formal Concept Analysis (FCA), to the representation of documents. This allows the use of more elegant representation units, as opposed to keywords, in order to better capture concepts/ideas expressed in natural language text. We also investigate the use of a reinforcement leaming strategy to learn and improve document representations, based on the information present in query statements and user relevance feedback. Features or concepts of each document/query, formulated using FCA, are weighted separately with respect to the documents they are in, and organised into separate concept lattices according to a subsumption relation. Furthen-nore, each concept lattice is encoded in a two-layer neural network structure known as a Bidirectional Associative Memory (BAM), for efficient manipulation of the concepts in the lattice representation. This avoids implementation drawbacks faced by other FCA-based approaches. Retrieval of a document for an information need is based on concept matching between concept lattice representations of a document and a query. The learning strategy works by making the similarity of relevant documents stronger and non-relevant documents weaker for each query, depending on the relevance judgements of the users on retrieved documents. Our approach is radically different to existing FCA-based approaches in the following respects: concept formulation; weight assignment to object-attribute pairs; the representation of each document in a separate concept lattice; and encoding concept lattices in BAM structures. Furthermore, in contrast to the traditional relevance feedback mechanism, our learning strategy makes use of relevance feedback information to enhance document representations, thus making the document representations dynamic and adaptive to the user interactions. The results obtained on the CISI, CACM and ASLIB Cranfield collections are presented and compared with published results. In particular, the performance of the system is shown to improve significantly as the system learns from experience.The School of Computing, University of Plymouth, UK

Computer-Aided Geometry Modeling

Techniques in computer-aided geometry modeling and their application are addressed. Mathematical modeling, solid geometry models, management of geometric data, development of geometry standards, and interactive and graphic procedures are discussed. The applications include aeronautical and aerospace structures design, fluid flow modeling, and gas turbine design

AiiDA: Automated Interactive Infrastructure and Database for Computational Science

Computational science has seen in the last decades a spectacular rise in the scope, breadth, and depth of its efforts. Notwithstanding this prevalence and impact, it is often still performed using the renaissance model of individual artisans gathered in a workshop, under the guidance of an established practitioner. Great benefits could follow instead from adopting concepts and tools coming from computer science to manage, preserve, and share these computational efforts. We illustrate here our paradigm sustaining such vision, based around the four pillars of Automation, Data, Environment, and Sharing. We then discuss its implementation in the open-source AiiDA platform (http://www.aiida.net), that has been tuned first to the demands of computational materials science. AiiDA's design is based on directed acyclic graphs to track the provenance of data and calculations, and ensure preservation and searchability. Remote computational resources are managed transparently, and automation is coupled with data storage to ensure reproducibility. Last, complex sequences of calculations can be encoded into scientific workflows. We believe that AiiDA's design and its sharing capabilities will encourage the creation of social ecosystems to disseminate codes, data, and scientific workflows.Comment: 30 pages, 7 figure

An Object memory for an object-oriented database management system

Ankara : The Department of Computer Engineering and Information Sciences and the Institute of Engineering and Sciences of Bilkent Univ. , 1988.Thesis (Master's) -- Bilkent University), 1988.Includes bibliographical references leaves 86-89.Object-oriented paradigm is an approach that can be applied in various areas of computing. In this approach, each entity is represented by an object which captures the state and the behaviour of the entity. In this thesis, a focused survey of object-oriented paradigm in general and object-oriented database management systems in particular has been carried out and an object memory module is designed and implemented for an object-oriented database management system prototype. The object memory module handles the representation, access and manipulation of objects in the system and provides the primitive functions that are necessary in the development of the prototype.Kesim, F NihanM.S

Semantic networks

AbstractA semantic network is a graph of the structure of meaning. This article introduces semantic network systems and their importance in Artificial Intelligence, followed by I. the early background; II. a summary of the basic ideas and issues including link types, frame systems, case relations, link valence, abstraction, inheritance hierarchies and logic extensions; and III. a survey of ‘world-structuring’ systems including ontologies, causal link models, continuous models, relevance, formal dictionaries, semantic primitives and intersecting inference hierarchies. Speed and practical implementation are briefly discussed. The conclusion argues for a synthesis of relational graph theory, graph-grammar theory and order theory based on semantic primitives and multiple intersecting inference hierarchies

PolyView : an object-oriented data model for supporting multiple user views

In a typical database application, there are many different users with a great variety of skills, needs and perceptions. The problem of supporting this plethora of user views in a dynamic, data intensive environment is the topic of this dissertation.In traditional record-based systems, all information is represented by an idealized data structure and a set of operations on that structure. User views are defined by simple variations in this structure, such as permuting field names, selecting a subset of the data, or creating links between records. Semantic database models support more complex, "natural" structures. It is often claimed that relativism is supported because semantic schemas can be correctly interpreted (by users) in different ways. The object-oriented paradigm, with its simple and elegant structural semantics, provides both simplicity and richness. Unfortunately, current object-oriented systems only provide a single object interface (or protocol). This dissertation presents PolyView; an object-oriented data model capable of simultaneously supporting many points of view. In PolyView, objects encapsulate a single structure and any number of object interfaces (view instance descriptions). PolyView, therefore, supports distributed mappings from user views to the underlying database structure.Algorithms are presented for generic methods which retrieve and update information through user views. PolyView "colors" queries (messages) by attaching a view identity to them. As messages are propagated through the schema, each receiving object uses the color to determine how the message is to be processed. The color is used to select the user's protocol and allows different user's queries to be processed through apparently different database structures. Because objects act independently, PolyView is a data-driven system; messages are processed without any centralized control or shared memory.Finally, PolyView provides a set of view transformations which allow view administrators to build object interfaces. Since views are supported by both global and localized mechanisms, there are transformations which operate at each of these levels. There are three major categories of transformations presented in this thesis: those which customize the schema as a whole, transformations for changing the structure of the IS-A hierarchy and transformations for customizing attributes