Personal eBanking Solutions Based on Semantic Web Services

We describe how Semantic Web Service technology can be used for the provision of personal e-banking online services. We describe two deployed applications: an overdraft notification service and a mortgage comparison service. The former accesses the bank accounts of a user as well as utility goods Web sites where invoicing information is stored and estimates whether the user will be in an overdraft situation in the near future, alerting him/her by e-mail or SMS. The latter accesses the mortgage information provided by the heterogeneous Web sites of different banks and allows users to compare them according to different types of criteria. The chapter not only focuses on the technological decisions followed to implement and deploy these services, but also on the added value of applying Semantic Web Services for them

SMS: A Framework for Service Discovery by Incorporating Social Media Information

© 2008-2012 IEEE. With the explosive growth of services, including Web services, cloud services, APIs and mashups, discovering the appropriate services for consumers is becoming an imperative issue. The traditional service discovery approaches mainly face two challenges: 1) the single source of description documents limits the effectiveness of discovery due to the insufficiency of semantic information; 2) more factors should be considered with the generally increasing functional and nonfunctional requirements of consumers. In this paper, we propose a novel framework, called SMS, for effectively discovering the appropriate services by incorporating social media information. Specifically, we present different methods to measure four social factors (semantic similarity, popularity, activity, decay factor) collected from Twitter. Latent Semantic Indexing (LSI) model is applied to mine semantic information of services from meta-data of Twitter Lists that contains them. In addition, we assume the target query-service matching function as a linear combination of multiple social factors and design a weight learning algorithm to learn an optimal combination of the measured social factors. Comprehensive experiments based on a real-world dataset crawled from Twitter demonstrate the effectiveness of the proposed framework SMS, through some compared approaches

Bletchley Park text: using mobile and semantic web technologies to support the post-visit use of online museum resources

A number of technologies have been developed to support the museum visitor, with the aim of making their visit more educationally rewarding and/or entertaining. Examples include PDA-based personalized tour guides and virtual reality representations of cultural objects or scenes. Rather than supporting the actual visit, we decided to employ technology to support the post-visitor, that is, encourage follow-up activities among recent visitors to a museum. This allowed us to use the technology in a way that would not detract from the existing curated experience and allow the museum to provide access to additional heritage resources that cannot be presented during the physical visit. Within our application, called Bletchley Park Text, visitors express their interests by sending text (SMS) messages containing suggested keywords using their own mobile phone. The semantic description of the archive of resources is then used to retrieve and organize a collection of content into a personalized web site for use when they get home. Organization of the collection occurs both bottom-up from the semantic description of each item in the collection, and also top-down according to a formal representation of the overall museum story. In designing the interface we aimed to support exploration across the content archive rather than just the search and retrieval of specific resources. The service was developed for the Bletchley Park museum and has since been launched for use by all visitors

Neogeography: The Challenge of Channelling Large and Ill-Behaved Data Streams

Neogeography is the combination of user generated data and experiences with mapping technologies. In this article we present a research project to extract valuable structured information with a geographic component from unstructured user generated text in wikis, forums, or SMSes. The extracted information should be integrated together to form a collective knowledge about certain domain. This structured information can be used further to help users from the same domain who want to get information using simple question answering system. The project intends to help workers communities in developing countries to share their knowledge, providing a simple and cheap way to contribute and get benefit using the available communication technology

An Algorithm for Automatic Service Composition

Telecommunication companies are struggling to provide their users with value-added services. These services are expected to be context-aware, attentive and personalized. Since it is not economically feasible to build services separately by hand for each individual user, service providers are searching for alternatives to automate service creation. The IST-SPICE project aims at developing a platform for the development and deployment of innovative value-added services. In this paper we introduce our algorithm to cope with the task of automatic composition of services. The algorithm considers that every available service is semantically annotated. Based on a user/developer service request a matching service is composed in terms of component services. The composition follows a semantic graph-based approach, on which atomic services are iteratively composed based on services' functional and non-functional properties

Mobile Phone Text Processing and Question-Answering

Mobile phone text messaging between mobile users and information services is a growing area of Information Systems. Users may require the service to provide an answer to queries, or may, in wikistyle, want to contribute to the service by texting in some information within the service’s domain of discourse. Given the volume of such messaging it is essential to do the processing through an automated service. Further, in the case of repeated use of the service, the quality of such a response has the potential to benefit from a dynamic user profile that the service can build up from previous texts of the same user. This project will investigate the potential for creating such intelligent mobile phone services and aims to produce a computational model to enable their efficient implementation. To make the project feasible, the scope of the automated service is considered to lie within a limited domain of, for example, information about entertainment within a specific town centre. The project will assume the existence of a model of objects within the domain of discourse, hence allowing the analysis of texts within the context of a user model and a domain model. Hence, the project will involve the subject areas of natural language processing, language engineering, machine learning, knowledge extraction, and ontological engineering

Balancing SoNaR: IPR versus Processing Issues in a 500-Million-Word Written Dutch Reference Corpus

In The Low Countries, a major reference corpus for written Dutch is beingbuilt. We discuss the interplay between data acquisition and data processingduring the creation of the SoNaR Corpus. Based on developments in traditionalcorpus compiling and new web harvesting approaches, SoNaR is designed tocontain 500 million words, balanced over 36 text types including bothtraditional and new media texts. Beside its balanced design, every text sampleincluded in SoNaR will have its IPR issues settled to the largest extentpossible. This data collection task presents many challenges because everydecision taken on the level of text acquisition has ramifications for the levelof processing and the general usability of the corpus. As far as thetraditional text types are concerned, each text brings its own processingrequirements and issues. For new media texts - SMS, chat - the problem is evenmore complex, issues such as anonimity, recognizability and citation right, allpresent problems that have to be tackled. The solutions actually lead to thecreation of two corpora: a gigaword SoNaR, IPR-cleared for research purposes,and the smaller - of commissioned size - more privacy compliant SoNaR,IPR-cleared for commercial purposes as well