Learning to harvest information for the semantic web

This work was carried out within the AKT project (www.aktors.org), sponsored by the UK Engineering and Physical Sciences Research Council (grant GR/N15764/01), and the Dot.Kom project (www.dot-kom.org), sponsored by the EU IST asp part of Framework V (grant IST-2001-34038).In this paper we describe a methodology for harvesting in- formation from large distributed repositories (e.g. large Web sites) with minimum user intervention. The methodology is based on a combination of information extraction, information integration and machine learning techniques. Learning is seeded by extracting information from structured sources (e.g. databases and digital libraries) or a user-defined lexicon. Retrieved information is then used to partially annotate documents. An- notated documents are used to bootstrap learning for simple Information Extraction (IE) methodologies, which in turn will produce more annotation to annotate more documents that will be used to train more complex IE engines and so on. In this paper we describe the methodology and its implementation in the Armadillo system, compare it with the current state of the art, and describe the details of an implemented application. Finally we draw some conclusions and highlight some challenges and future work.peer-reviewe

Knowledge Rich Natural Language Queries over Structured Biological Databases

Increasingly, keyword, natural language and NoSQL queries are being used for information retrieval from traditional as well as non-traditional databases such as web, document, image, GIS, legal, and health databases. While their popularity are undeniable for obvious reasons, their engineering is far from simple. In most part, semantics and intent preserving mapping of a well understood natural language query expressed over a structured database schema to a structured query language is still a difficult task, and research to tame the complexity is intense. In this paper, we propose a multi-level knowledge-based middleware to facilitate such mappings that separate the conceptual level from the physical level. We augment these multi-level abstractions with a concept reasoner and a query strategy engine to dynamically link arbitrary natural language querying to well defined structured queries. We demonstrate the feasibility of our approach by presenting a Datalog based prototype system, called BioSmart, that can compute responses to arbitrary natural language queries over arbitrary databases once a syntactic classification of the natural language query is made

Using pattern languages to mediate theory–praxis conversations in design for networked learning

Educational design for networked learning is becoming more complex but also more inclusive, with teachers and learners playing more active roles in the design of tasks and of the learning environment. This paper connects emerging research on the use of design patterns and pattern languages with a conception of educational design as a conversation between theory and praxis. We illustrate the argument by drawing on recent empirical research and literature reviews from the field of networked learning

On distributed data processing in data grid architecture for a virtual repository

The article describes the problem of integration of distributed, heterogeneous and fragmented collections of data with application of the virtual repository and the data grid concept. The technology involves: wrappers enveloping external resources, a virtual network (based on the peer-topeer technology) responsible for integration of data into one global schema and a distributed index for speeding-up data retrieval. Authors present a method for obtaining data from heterogeneously structured external databases and then a procedure of integration the data to one, commonly available, global schema. The core of the described solution is based on the Stack-Based Query Language (SBQL) and virtual updatable SBQL views. The system transport and indexing layer is based on the P2P architecture

Pattern Recognition Software and Techniques for Biological Image Analysis

The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays

Development of an online collaborative working environment for design and manufacturing

This research is to develop a novel collaborative working environment (CWE) for manufacturing and design using advanced Web/Internet technologies such as Web Service, Grid Service and other related software tools/packages. To achieve the above, the following research modules are developed by the author: A service oriented framework for computer aid design, which acts as an online collaboration system, has been developed with the utilisation of the latest technology, Web Service. The concept of Service-Oriented Architecture has been implemented in the framework. Users from anywhere in the world can join the design process from their PCs, no matter what operation system they are using. The service-oriented system has the capability of going through firewalls and can afford multi-users due to the characteristics of Web service. Also the loose-coupling structure makes the system very easy to be updated. Another module for the CWE is to solve the software sharing problem when the platform is used among several geographically dispersed users or organisations. A software package bank system has been developed, which utilised the ideology of service oriented approach and successfully solved traditional problems in this field. Based on the outcomes mentioned above, the research finally developed a more powerful infrastructure using Grid service, which is a further development of Grid computing and Web service. The Grid service is considered to be the most important future solvent for Internet