An intelligent design retrieval system for module-based products

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file viewed on (June 30, 2006)Includes bibliographical references.Vita.Thesis (Ph. D.) University of Missouri-Columbia 2004.Dissertations, Academic -- University of Missouri--Columbia -- Industrial engineering.The manufacturing industry has shifted its approach from traditional manufacturing to agile manufacturing. The production of customized products will increase in response to the individual demands of customers. In exploring various industry trends, researchers have developed different approaches to designing structural products. The most popular and most commonly used approach in contending with structural products is the modularity approach. Moreover, there are several studies that address modularity with respect to structural representations. Even so, there is not yet a unified method for supporting product structure development and for integrating information. Another aspect that current research has not yet adequately addressed is product information retrieval. Those studies that did contend with product information retrieval, addressed one-level retrieval models, while ignoring structural products. Thus, limitations persist in current intelligent retrieval systems. To answer the aforementioned difficulty, a unified indexing scheme is introduced. In this study, the information can be put into numerical form as the proposed unified indexing scheme, which is represented by a component and structure matrix. The component and structure matrix is the way to achieve an application of modular design retrieval because (1) it is a unique presentation of a structural product and provides a uniform representation; and (2) it lists all modules, as well as all components, in one representation. As a result of the proposed method, an intelligent retrieval system will give an enterprise the ability to communicate with its partners efficiently. Therefore, the aim of this research is to develop a system that will enable more efficient and more effective product-design retrieval systems for structural products, and to demonstrate this framework through a Web-based application using Web technology. To obtain reference designs after utilizing the unified indexing scheme, a Fuzzy-ART neural network is implemented in order to handle retrieval tasks

TREE-D-SEEK: A Framework for Retrieving Three-Dimensional Scenes

In this dissertation, a strategy and framework for retrieving 3D scenes is proposed. The strategy is to retrieve 3D scenes based on a unified approach for indexing content from disparate information sources and information levels. The TREE-D-SEEK framework implements the proposed strategy for retrieving 3D scenes and is capable of indexing content from a variety of corpora at distinct information levels. A semantic annotation model for indexing 3D scenes in the TREE-D-SEEK framework is also proposed. The semantic annotation model is based on an ontology for rapid prototyping of 3D virtual worlds. With ongoing improvements in computer hardware and 3D technology, the cost associated with the acquisition, production and deployment of 3D scenes is decreasing. As a consequence, there is a need for efficient 3D retrieval systems for the increasing number of 3D scenes in corpora. An efficient 3D retrieval system provides several benefits such as enhanced sharing and reuse of 3D scenes and 3D content. Existing 3D retrieval systems are closed systems and provide search solutions based on a predefined set of indexing and matching algorithms Existing 3D search systems and search solutions cannot be customized for specific requirements, type of information source and information level. In this research, TREE-D-SEEK—an open, extensible framework for retrieving 3D scenes—is proposed. The TREE-D-SEEK framework is capable of retrieving 3D scenes based on indexing low level content to high-level semantic metadata. The TREE-D-SEEK framework is discussed from a software architecture perspective. The architecture is based on a common process flow derived from indexing disparate information sources. Several indexing and matching algorithms are implemented. Experiments are conducted to evaluate the usability and performance of the framework. Retrieval performance of the framework is evaluated using benchmarks and manually collected corpora. A generic, semantic annotation model is proposed for indexing a 3D scene. The primary objective of using the semantic annotation model in the TREE-D-SEEK framework is to improve retrieval relevance and to support richer queries within a 3D scene. The semantic annotation model is driven by an ontology. The ontology is derived from a 3D rapid prototyping framework. The TREE-D-SEEK framework supports querying by example, keyword based and semantic annotation based query types for retrieving 3D scenes

A unified logical-linguistic indexing for search engines and question answering.

Conventional information representation models used in the search engines rely on an extensive use of keywords and their frequencies in storing and retrieving information. It is believed that such an approach has reached its upper limit of retrieval effectiveness, and therefore, new approaches should be investigated for the development of future engines which will be more effective. Logical-linguistic model is an alternative to conventional approach where logic and linguistic formalism are used in providing mechanism for computer to understand the contents of the source and deduce answers to questions. The capability of deduction is much depended on the knowledge representation framework used. We propose a unified logical-linguistic model as knowledge representation framework as a basis for indexing of documents as well as deduction capability to provide answers to queries. The approach applies semantic analysis in transforming and normalising information from natural language texts into a declarative knowledge based representation of first order predicate logic. Retrieval of relevant information can then be performed through plausible logical implication and answer to query is carried out using theorem proving technique. This paper elaborates on the model and how it is used in search engine and question answering system as one unified model

An Approach to Automatic Indexing of Scientific Publications in High Energy Physics for Database SPIRES HEP

We introduce an approach to automatic indexing of e-prints based on a pattern-matching technique making extensive use of an Associative Patterns Dictionary (APD), developed by us. Entries in the APD consist of natural language phrases with the same semantic interpretation as a set of keywords from a controlled vocabulary. The method also allows to recognize within e-prints formulae written in TeX notations that might also appear as keywords. We present an automatic indexing system, AUTEX, which we have applied to keyword index e-prints in selected areas in high energy physics (HEP) making use of the DESY-HEPI thesaurus as a controlled vocabulary.Comment: 23 pages, 4 figure