Using Ontology Research in Semantic Web Applications

In the light of improving the World Wide Web, researchers are working towards the Semantic Web. Ontologies and ontology-based applications are its basic ingredients. Several ontological environments, categorizations and methodologies can be found in the literature. This paper shows how we have investigated the state of the art in these areas in an ontology building process that is the basis for an application developed at the later stage in an events organisation domain

A Generic Communications Module for Cooperative 3D Visualization and Modelling over the Internet: the Collaborative API

Cooperative three-dimensional visualization and modeling applications allow a distributed group of users to work together with a model they share. To implement this kind of applications the underlying communications system must provide reliable and ordered multicast of users interactions. Due to the high complexity that characterizes the models, network bandwidth requirements have limited their use to intranets or in a few cases to very high-speed Internet connections. In this paper we present a communications module that solves this problem. The library exposed, which is called Collaborative API, supports the creation of very efficient cooperative 3D visualization and modeling applications by optimizing the use of the network resources. The Collaborative API, implements a new communications architecture: the dynamic client/server. The communications module presented in this paper is illustrated by two examples of applications that use it to provide cooperative 3D visualization over the Internet

Integration with Ontologies

One of today’s hottest IT topics is integration, as bringing together information from different sources and structures is not completely solved. The approach outlined here wants to illustrate how ontologies [Gr93] could help to support the integration process

Evolution and overview of Linked USDL

For more than 10 years, research on service descriptions has mainly studied software-based services and provided languages such as WSDL, OWL-S, WSMO for SOAP, and hREST for REST. Nonetheless, recent developments from service management (e.g., ITIL and COBIT) and cloud computing (e.g. Software-as-a-Service) have brought new re- quirements to service descriptions languages: the need to also model business services and account for the multi-faceted nature of services. Business-orientation, co-creation, pricing, legal aspects, and security issues are all elements which must also be part of service descriptions. While ontologies such as e service and e value provided a first modeling attempt to capture a business perspective, concerns on how to contract services and the agreements entailed by a contract also need to be taken into account. This has for the most part been disregarded by the e family of ontologies. In this paper, we review the evolution and provide an overview of Linked USDL, a comprehensive language which provides a (multi-faceted) description to enable the commercialization of (business and technical) services over the web

Automated information extraction from web APIs documentation

A fundamental characteristic of Web APIs is the fact that, de facto, providers hardly follow any standard practices while implementing, publishing, and documenting their APIs. As a consequence, the discovery and use of these services by third parties is significantly hampered. In order to achieve further automation while exploiting Web APIs we present an approach for automatically extracting relevant technical information from the Web pages documenting them. In particular we have devised two algorithms that automatically extract technical details such as operation names, operation descriptions or URI templates from the documentation of Web APIs adopting either RPC or RESTful interfaces. The algorithms devised, which exploit advanced DOM processing as well as state of the art Information Extraction and Natural Language Processing techniques, have been evaluated against a detailed dataset exhibiting a high precision and recall–around 90% for both REST and RPC APIs outperforming state of the art information extraction algorithms

Feature LDA: a supervised topic model for automatic detection of Web API documentations from the Web

Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models

Linked USDL: a vocabulary for web-scale service trading

Real-world services ranging from cloud solutions to consulting currently dominate economic activity. Yet, despite the increasing number of service marketplaces online, service trading on the Web remains highly restricted. Services are at best traded within closed silos that offer mainly manual search and comparison capabilities through a Web storefront. Thus, it is seldom possible to automate the customisation, bundling, and trading of services, which would foster a more efficient and effective service sector. In this paper we present Linked USDL, a comprehensive vocabulary for capturing and sharing rich service descriptions, which aims to support the trading of services over the Web in an open, scalable, and highly automated manner. The vocabulary adopts and exploits Linked Data as a means to efficiently support communication over the Web, to promote and simplify its adoption by reusing vocabularies and datasets, and to enable the opportunistic engagement of multiple cross-domain providers

Real-world data of fulvestrant as first-line treatment of postmenopausal women with estrogen receptor-positive metastatic breast cancer

Goals of endocrine therapy for advanced breast cancer (ABC) include prolonging survival rates, maintaining the quality of life, and delaying the initiation of chemotherapy. We evaluated the effectiveness of fulvestrant as first-line in patients with estrogen receptor (ER)-positive ABC with relapse during or after adjuvant anti-estrogenic therapy in real-world settings. Retrospective, observational study involving 171 postmenopausal women with ER-positive ABC who received fulvestrant as first-line between January 2011 and May 2018 in Spanish hospitals. With a median follow-up of 31.4 months, the progression-free survival (PFS) with fulvestrant was 14.6 months. No differences were seen in the visceral metastatic (14.3 months) versus non-visceral (14.6 months) metastatic subgroup for PFS. Overall response rate and clinical benefit rate were 35.2% and 82.8%. Overall survival was 43.1 months. The duration of the clinical benefit was 19.2 months. Patients with ECOG performance status 0 at the start of treatment showed a significant greater clinical benefit rate and overall survival than with ECOG 1-2. Results in real-world settings are in concordance with randomized clinical trials. Fulvestrant continues to demonstrate clinical benefits in real-world settings and appears be well tolerated as first-line for the treatment of postmenopausal women with ER-positive ABC

Prikaz znanja u internetu stvari: semantičko modeliranje i njegove primjene

Semantic modelling provides a potential basis for interoperating among different systems and applications in the Internet of Things (IoT). However, current work has mostly focused on IoT resource management while not on the access and utilisation of information generated by the “Things”. We present the design of a comprehensive and lightweight semantic description model for knowledge representation in the IoT domain. The design follows the widely recognised best practices in knowledge engineering and ontology modelling. Users are allowed to extend the model by linking to external ontologies, knowledge bases or existing linked data. Scalable access to IoT services and resources is achieved through a distributed, semantic storage design. The usefulness of the model is also illustrated through an IoT service discovery method.Semantičko modeliranje pruža potencijalnu osnovu za me.udjelovanje različitih sustava i aplikacija unutar interneta stvari (IoT). Međutim, postojeći radovi uglavnom su fokusirani na upravljanje IoT resursima, ali ne i pristupu i korištenju informacija koje generira “stvar”. Predstavljamo projektiranje sveobuhvatnog i laganog semantičkog opisnog modela za prikaz znanja u IoT domeni. Projektiranje slijedi široko-priznate najbolje običaje u inženjerstvu znanja i ontološkom modeliranju. Korisnicima se dopušta proširenje modela povezivanjem na eksterne ontologije, baze znanja ili postoje će povezane podatke. Skalabilni pristup IoT uslugama i resursima postiže se kroz distribuirano, semantičko projektiranje pohrane. Upotrebljivost modela tako.er je ilustrirana kroz metodu pronalaska IoT usluga