Expert knowledge management based on ontology in a digital library

The architecture of the future Digital Libraries should be able to allow any users to access available knowledge resources from anywhere and at any time and efficient manner. Moreover to the individual user, there is a great deal of useless information in addition to the substantial amount of useful information. The goal is to investigate how to best combine Artificial Intelligent and Semantic Web technologies for semantic searching across largely distributed and heterogeneous digital libraries. The Artificial Intelligent and Semantic Web have provided both new possibilities and challenges to automatic information processing in search engine process. The major research tasks involved are to apply appropriate infrastructure for specific digital library system construction, to enrich metadata records with ontologies and enable semantic searching upon such intelligent system infrastructure. We study improving the efficiency of search methods to search a distributed data space like a Digital Library. This paper outlines the development of a CaseBased Reasoning prototype system based in an ontology for retrieval information of the Digital Library University of Seville. The results demonstrate that the used of expert system and the ontology into the retrieval process, the effectiveness of the information retrieval is enhanced

Intelligent Knowledge Retrieval from Industrial Repositories

Actually, a large amount of information is stored in the industrial repositories. Accessing this information is complicated, and the techniques currently used in metadata and the material chosen by the user do not scale efficiently in large collections. The semantic Web provides a frame of reference that allows sharing and reusing knowledge efficiently. In our work, we present a focus for discovering information in digital repositories based on the application of expert system technologies, and we show a conceptual architecture for a semantic search engine. We used case-based reasoning methodology to create a prototype that supports efficient retrieval knowledge from digital repositories. OntoEnter is a collaborative effort that proposes a new form of interaction between users and digital enterprise repositories, where the latter are adapted to users and their surroundings

A context-aware model to improve usability of information presented on mobile devices

Online information access on mobile devices is increasing as a result of the growth in the use of Internet-enabled handheld (or pocket-size) devices. The combined influence of recent enabling technologies such as Web 2.0, mobile app stores and improved wireless networks have driven the increase in online applications that allow users to access various types of information on mobile devices regardless of time and location. Examples of such applications (usually shortened to app) include: social media, such as FacebookTM App and TwitterTM App, banking applications such as (Standard Bank South Africa)TM Mobile Banking App and First National Bank (FNB) BankingTM App, and news application such as news 24TM App and BBCTM News App. Online businesses involved in buying, selling and business transaction processing activities via the Internet have exploited the opportunity to extend electronic commerce (e-commerce) initiatives into mobile commerce (m-commerce). Online businesses that interact with end user customers implement business to consumer (B2C) m-commerce applications that enable customers to access and browse product catalogue information on mobile devices, anytime, anywhere. Customers accessing electronic product catalogue information on a mobile device face a number of challenges such as a long list of products presented on a small screen and a longer information download time. These challenges mainly originate from the limiting and dynamic nature of the mobile apps operating environment, for example, dynamic location, bandwidth fluctuations and, diverse and limited device features, collectively referred to as context. The goal of this research was to design and implement a context-aware model that can be incorporated into an m-commerce application in order to improve the presentation of product catalogue information on m-commerce storefronts. The motivation for selecting product catalogue is prompted by literature which indicates that improved presentation of information in m-commerce (and e-commerce) applications has a positive impact on usability of the websites. Usable m-commerce (and e-commerce) websites improve efficiency in consumer behaviour that impacts sales, profits and business growth. The context-aware model aimed at collecting context information within the user environment and utilising it to determine optimal retrieval and presentation of product catalogue in m-commerce. An integrated logical context sensor and Mathematical algorithms were implemented in the context-aware model. The integrated logical context sensor was responsible for the collection of different types of predetermined context information such as device specification or capabilities, connection bandwidth, location and time of the day as well as the user profile. The algorithms transformed the collected context information into usable formats and enabled optimal retrieval and presentation of product catalogue data on a specific mobile device. Open-source implementation tools were utilised to implement components of the model including: HTML5, PhP, JavaScript and MySQL database. The context-aware model was incorporated into an existing m-commerce application. Two user evaluation studies were conducted during the course of the research. The first evaluation was to evaluate the accuracy of information collected by the context sensor component of the model. This survey was conducted with a sample of 30 users from different countries across the world. In-between the context sensor and main evaluation surveys, a pilot study was conducted with a sample of 19 users with great experience in mobile application development and use from SAP Next Business and Technology, Africa. Finally an overall user evaluation study was conducted with a sample of 30 users from a remote area called Kgautswane in Limpopo Province, South Africa. The results obtained indicate that the context-aware model was able to determine accurate context information in real-time and effectively determine how much product information should be retrieved and how the information should be presented on a mobile device interface. Two main contributions emerged from the research, first the research contributed to the field of mobile Human Computer Interaction. During the research, techniques of evaluating and improving usability of mobile applications were demonstrated. Secondly, the research made a significant contribution to the upcoming field of context-aware computing. The research brought clarity with regard to context-aware computing which is lacking in existing, current research despite the field’s proven impact of improving usability of applications. Researchers can utilise contributions made in this research to develop further techniques and usable context-aware solutions