Search results

The integration and retrieval of the vast data have attracted sufficient attention, thus the W3C workgroup releases R2RML to standardize the transformation from relational data to semantic-aware data. However, it only provides a data transform mechanism to resource description framework (RDF). The generation of mapping alignments still needs manual work or other algorithms. Therefore, the purpose of this paper is to propose a domain-oriented automatic mapping method and an application of the R2RML standard.

In this paper, materials science is focussed to show an example of domain-oriented mapping. source field concept and M3B2 (Metal Materials Mapping Background Base) knowledge bases are established to support the auto-recommending algorithm. As for the generation of RDF files, the idea is to generate the triples and the links, respectively. The links of the triples follow the object-subject relationship, and the links of the object properties can be achieved by the range individuals and the trail path.

Consequently based on the previous work, the authors proposed Engine for Metal Materials Mapping Background Base (EM3B2), a semantic integration engine for materials science. EM3B2 not only offers friendly graphical interfaces, but also provides auto-recommending mapping based on materials knowledge to enable users to avoid vast manually work. The experimental result indicates that EM3B2 supplies accurate mapping. Moreover, the running time of E3MB2 is also competitive as classical methods.

This paper proposed EM3B2 semantic integration engine, which contributes to the relational database-to-RDF mapping by the application of W3C R2RML standard and the domain-oriented mapping.

Tree pattern is at the core of XML queries. The tree patterns in XML queries typically contain redundancies, especially when broad integrity constraints (ICs) are present and considered. Apparently, tree pattern minimization has great significance for efficient XML query processing. Although various minimization schemes/algorithms have been proposed, none of them can exploit broad ICs for thoroughly minimizing the tree patterns in XML queries. The purpose of this research is to develop an innovative minimization scheme and provide a novel implementation algorithm.

Query augmentation/expansion was taken as a necessary first‐step by most prior approaches to acquire XML query pattern minimization under the presence of certain ICs. The adopted augmentation/expansion is also the course for the typical O(n⁴) time‐complexity of the proposed algorithms. This paper presents an innovative approach called allying to effectively circumvent the otherwise necessary augmentation step and to retain the time complexity of the implementation algorithm within the optimal, i.e. O(n²). Meanwhile, the graph simulation concept is adapted and generalized to a three‐tier definition scheme so that broader ICs are incorporated.

The innovative allying minimization approach is identified and an effective implementation algorithm named AlliedMinimize is developed. This algorithm is both runtime optimal – taking O(n²) time – and most powerful in terms of the broadness of constraints it can exploit for XML query pattern minimization. Experimental study confirms the validity of the proposed approach and algorithm.

Though the algorithm AlliedMinimize is so far the most powerful XML query pattern minimization algorithm, it does not incorporate all potential ICs existing in the context of XML. Effectively integrating this innovative minimization scheme into a fully‐fledged XML query optimizer remains to be investigated in the future.

In practice, Allying and AlliedMinimize can be used to achieve a kind of quick optimization for XML queries via fast minimization of the tree patterns involved in XML queries under broad ICs.

This paper presents a novel scheme and an efficient algorithm for XML query pattern minimization under broad ICs.

This study explores the effects of cognitive load on the propensity to reformulate queries during information seeking on the web.

This study employs an experimental design to analyze the effect of manipulations of cognitive load on the propensity for query reformulation between experimental and control groups. In total, three affective components that contribute to cognitive load were manipulated: mental demand, temporal demand and frustration.

A significant difference in the propensity of query reformulation behavior was found between searchers exposed to cognitive load manipulations and searchers who were not exposed. Those exposed to cognitive load manipulations made half as many search query reformulations as searchers not exposed. Furthermore, the National Aeronautical and Space Administration Task Load Index (NASA-TLX) cognitive load scores of searchers who were exposed to the three cognitive load manipulations were higher than those of searchers who were not exposed indicating that the manipulation was effective. Query reformulation behavior did not differ across task types.

The findings suggest that a dual-task method and NASA-TLX assessment serve as good indicators of cognitive load. Because the findings show that cognitive load hinders a searcher's interaction with information search tools, this study provides empirical support for reducing cognitive load when designing information systems or user interfaces.

Future developments in methodology have the potential to improve management research and better couple it to management practice. These developments are on six fronts: (1) computer technology, (2) data capture and experimentation, (3) privacy, confidentiality, and data access, (4) causation, (5) modeling and simulation, and (6) Bayesian statistics. The potential of each is explored, and problems, both technical and administrative, in fulfilling this potential are identified. On the computer and communications front, the key elements are the use of relational database management systems, increased computing power for analysis purposes, and computer networking. On the privacy, confidentiality, and data access front, the key elements are new capabilities for data capture through real‐time surveillance, inferential disclosure threats in computer databases, the demand for more access to detailed data, and public concerns for privacy invasion. Management research is a search for causal mechanisms that can be investigated through empirical studies and that facilitate control of complex processes. In the modeling area, there will be (1) greater use of computing power, (2) less use of model‐independent statistical hypothesis testing, and (3) easier to use computer software for modeling and simulation. The Bayesian perspective of consistently expressing uncertainty through probability distributions will become more widely used in management research.

This paper presents hyper‐lib, a model for an electronic library. The hyper‐lib philosophy is based on reproducing the spatial environment of a physical library, in order to exploit users' knowledge of the physical domain in using the electronic system. In the library environment, rooms, shelves, books and services are reproduced by simulating a three‐dimensional environment, where the user can interact with a collection of documents as if he or she were in a physical library. In addition to the physical library features, the hyper‐lib introduces a number of new properties, which result from its non‐physical nature and allow some of the limitations of traditional libraries, such as availability of books and delivery time, to be overcome. The hyper‐lib books are available in electronic form, following the hyper‐book model, which is based on the book metaphor. A formal definition of the hyper‐lib model as a dynamic system is given. The hyper‐lib model is defined in terms of structural and functional components. Moreover, the functional behaviour, i.e. how the system evolves under the effects of the functional components, is presented. The library structural components include the book collection, the librarian, the access mechanisms etc. The functional aspect is indispensable for describing the use of a dynamic and interactive system. In particular, a number of operators, which represent user services, allow the user to change the system state. We distinguish among general services, which are offered in any room of the library, and specific services, which are specific to a particular object or room in the library, such as the librarian, the catalogues, the hyper‐books, the book shelves etc.

The intelligent agent object (IAO) system is a multi‐paradigm development environment which can be used to create intelligent agent systems for manufacturing or other domains. The IAO system was developed from the rule‐based object (RBO) system which is a programming environment integrating both the rule‐based and object‐oriented paradigms. Propagation‐oriented programming, access‐oriented programming and group‐oriented programming are among the extensions included in the IAO system. Its most unusual contribution is the propagation‐oriented programming paradigm which is not found in most systems. A key application is the messenger inferencing structure which is a user‐extendable framework supporting multiple knowledge representation, meta‐inference control, and distributed inference. This allows the IAO system to go beyond predicate logic based production rule programming. New developments are also introduced for access‐oriented programming. The IAO system can be used to develop integrated manufacturing systems such as the prototype automated guided vehicle planning and control system, which is briefly described.

At the heart of successful automated manufacturing systems lies the idea of effective integration of various functions. In any sizeable application of a Computer Integrated Manufacturing (CIM) system, an enormous amount of complex data needs to be logically integrated and managed. Presents and discusses the complex nature of CIM data and the difficulties associated with managing them. Given these difficulties, effective data management of such advanced manufacturing systems poses a challenging task for system designers and managers. Given the growing rate of diffusion of relational databases, it is important to explore the capabilities of this technology in serving the data management needs of manufacturing systems. Proposes a relational database schema, as opposed to a hierarchical or a network model. Uses appropriate examples from a Cellular Manufacturing setting to illustrate the proposed schema. Discusses issues related to distributing and logically integrating databases, and outlines managerial implications associated with rapidly changing information management technologies.

The purpose of this paper is to discuss a Multi-perspective approach to knowledge production in terms of a set of cybernetic concepts relevant to the approach; to describe a software system that computationally embodies the approach; and to articulate a research project that pragmatically employs the approach.

A definition is provided. The paper uses a survey methodology, exploring relevant cybernetic and contemporary technological concepts. An operational software mechanism (The Insight Engine) is discussed that enables the bridging of transdisciplinary concepts by a user in the service of accretive research –Recombinant Informatics.

Many cybernetic concepts are relevant to contemporary research into cognition and Neosentience research. More study needs to be undertaken related to historical BCL projects in terms of articulating relevance to contemporary research.

Future research seeks to extend the computational functionality of “The insight engine”, as well as uncover relevant BCL/cybernetic materials.

The software is unique in the field and already there is interest in its use by differing research communities including the Duke Institute for Brain Sciences, and at Stanford, research under Ian Hodder.

The Insight Engine has potential to be used as a multi-perspective tool for many different fields enabling different forms of distributed, transdisciplinary team-based research.

This text is valuable to researchers interested in new forms of interface, augmentation of thought and learning via computational approaches; and the development of bridges between novel research areas, including contemporary, historical BCL, and other cybernetic inquiry.

After almost three centuries of employing western educational approaches, many African societies are still characterized by low western literacy rates, civil conflicts, and underdevelopment. It is obvious that these western educational paradigms, which are not indigenous to Africans, have done relatively little good for Africans. Thus, the purpose of this paper is to argue that the salvation for Africans hinges upon employing indigenous African educational paradigms which can be subsumed under the rubric of ubuntugogy, which the authors define as the art and science of teaching and learning undergirded by humanity toward others.

Therefore, ubuntugogy transcends pedagogy (the art and science of teaching), andragogy (the art and science of helping adults learn), ergonagy (the art and science of helping people learn to work), and heutagogy (the study of self-determined learning). That many great African minds, realizing the debilitating effects of the western educational systems that have been forced upon Africans, have called for different approaches.

One of the biggest challenges for studying and teaching about Africa in Africa at the higher education level, however, is the paucity of published material. Automated generation of metadata is one way of mining massive data sets to compensate for this shortcoming.

Thus, the authors address the following major research question in this paper: What is automated generation of metadata and how can the technique be employed from an African-centered perspective? After addressing this question, conclusions and recommendations are offered.

This paper aims to improve the semantic-disambiguation capability of an information-retrieval system by taking advantages of a well-crafted classification tree. The unstructured nature and sheer volume of information accessible over networks have made it drastically difficult for users to seek relevant information. Many information-retrieval methods have been developed to address this problem, and keyword-based approach is amongst the most common approach. Such an approach is often inadequate to cope with the conceptualization associated with user needs and contents. This brings about the problem of semantic ambiguation that refers to the disagreement in meaning of terms between involving parties of a communication due to polysemy, leading to increased complexity and lesser accuracy in information integration, migration, retrieval and other related activities.

A novel ontology-based search approach, named GeTFIRST (short for Graph-embedded Tree Fostering Information Retrieval SysTem), is proposed to disambiguate keywords semantically. The contribution is twofold. First, a search strategy is proposed to prune irrelevant concepts for accuracy improvement using our Graph-embedded Tree (GeT)-based ontology. Second, a path-based ranking algorithm is proposed to incorporate and reward the content specificity.

An empirical evaluation was performed on United States Patent And Trademark Office (USPTO) patent datasets to compare our approach with full-text patent search approaches. The results showed that GeTFIRST handled the ambiguous keywords with higher keyword-disambiguation accuracy than traditional search approaches.

The search approach of this paper copes with the semantic ambiguation by using our proposed GeT-based ontology and a path-based ranking algorithm.