Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

A distributed approach to retrieving JPEG pictures in portable hypermedia documents

In this paper, we single out one of the problem aspects of multimedia: how can one efficiently store high-quality picture information in a manner that does not make its retrieval characteristics incompatible with the needs of a (distributed) multimedia application. These needs include: timely access to data, predictable access to common (i.e., network) resources and ease in user specification of information. Our approach to solving this problem is to define adaptive data objects that adjust the amount and type of information given to an application as a function of resource availability. The key to our approach is that we transparently adapt the information presented to the application based on a set of pre-specified conditions that were defined by the application at author time. We discuss this work in the context of a parallel JPEG image decoder that provides adaptive images (with respect to data content and image representation) based on a transparent client/server negotiation scheme. Our work is based on the Amsterdam Multimedia Framework (AMF), a partitioning of control operations for supporting distributed multimedia. The parallel JPEG algorithm, AMF and the negotiated control algorithm are explained

A Distributed, Component-based Solution for Scientific Information Management

This paper describes the design and performance of a distributed, multi-tier architecture for scientific information management and data exploration. A novel aspect of this framework is its integration of Java IDL, the CORBA distributed object computing middleware with JavaBeans, the Java Component model to provide a flexible, interactive framework for distributed, high-performance scientific data visualization. CORBA server objects running in a distributed, collaborative environment provide data acquisition and perform data-intensive computations. Clients as Java Bean components use these server objects for data retrieval and provide an interactive environment for visualization. The server objects use JDBC, the Java application programming interface to databases, to retrieve data from the distributed data stores. We discuss the system framework and its components and describe an example application and its performance

A Java-based Mobile Agent Framework for Distributed Network Applications

Recently, a new paradigm has emerged forstructuring and developing distributed network applications inopen distributed and heterogeneous environments. Manyapplication areas, such as electronic commerce, mobilecomputing, network management and information retrieval canbenefit from the application of the Mobile Agent technology. Theexploitation of Mobile Agents offers several peculiar advantages,such as reduction of network latency, asynchronous execution,robust and fault tolerant behavior. Java technology provides aplatform-independent, portable software environment whichmakes it an excellent tool for mobile agent development. MobileAgents are mainly intended to be used for applicationsdistributed over large scale (slow) networks because they allowsaving communication costs by moving computation to the hoston which the target data resides. However, it has not becomepopular due to some problems such as security. In this paper, wepresent a distributed network architecture based on the MobileAgent approach. A network of communicating servers each ofwhich support multiple clients is our goal. We also propose asecurity approach for mobile agents, which protect critical dataof mobile agents from malicious attacks, by using cryptographictechniques. We implement a bank service application to be testedon our mobile agent framework. The results suggest that fornetworks with high latency, Mobile Agents may provideimprovements over more conventional client-server systems

Challenges in distributed information search in a semantic digital library

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the current digital libraries. Access to these collections poses a serious challenge, however, because present search techniques based on manually annotated metadata and linear replay of material selected by the user do not scale effectively or efficiently to large collections. The artificial intelligent and semantic Web provides a common framework that allows knowledge to be shared and reused. In this paper we propose a comprehensive approach for discovering information objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We suggest a conceptual architecture for a semantic and intelligent search engine. OntoFAMA is a collaborative effort that proposes a new form of interaction between people and Digital Library, where the latter is adapted to individuals and their surroundings. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from digital library of Seville University

A grid-based infrastructure for distributed retrieval

In large-scale distributed retrieval, challenges of latency, heterogeneity, and dynamicity emphasise the importance of infrastructural support in reducing the development costs of state-of-the-art solutions. We present a service-based infrastructure for distributed retrieval which blends middleware facilities and a design framework to ‘lift’ the resource sharing approach and the computational services of a European Grid platform into the domain of e-Science applications. In this paper, we give an overview of the DILIGENT Search Framework and illustrate its exploitation in the field of Earth Science

Interoperability between Multimedia Collections for Content and Metadata-Based Searching

Artiste is a European project developing a cross-collection search system for art galleries and museums. It combines image content retrieval with text based retrieval and uses RDF mappings in order to integrate diverse databases. The test sites of the Louvre, Victoria and Albert Museum, Uffizi Gallery and National Gallery London provide their own database schema for existing metadata, avoiding the need for migration to a common schema. The system will accept a query based on one museum’s fields and convert them, through an RDF mapping into a form suitable for querying the other collections. The nature of some of the image processing algorithms means that the system can be slow for some computations, so the system is session-based to allow the user to return to the results later. The system has been built within a J2EE/EJB framework, using the Jboss Enterprise Application Server

Design Architecture-Based on Web Server and Application Cluster in Cloud Environment

Cloud has been a computational and storage solution for many data centric organizations. The problem today those organizations are facing from the cloud is in data searching in an efficient manner. A framework is required to distribute the work of searching and fetching from thousands of computers. The data in HDFS is scattered and needs lots of time to retrieve. The major idea is to design a web server in the map phase using the jetty web server which will give a fast and efficient way of searching data in MapReduce paradigm. For real time processing on Hadoop, a searchable mechanism is implemented in HDFS by creating a multilevel index in web server with multi-level index keys. The web server uses to handle traffic throughput. By web clustering technology we can improve the application performance. To keep the work down, the load balancer should automatically be able to distribute load to the newly added nodes in the server