60 research outputs found
Enabling Scalable Multi-channel Communication through Semantic Technologies
With the advance of the Web in the direction Social
Media the number of communication possibilities has
exponentially increased bringing new challenges and
opportunities for companies to build and shape their
reputation online as well as to engage and maintain the
relationships to their customers. In this paper we describe how
semantic technologies enable scalable, effective and efficient
on-line communication. We illustrate four different ways in
which semantics can be used for this purpose. First, we discuss
semantic analysis of communication items based on 'classical'
semantic, such as natural language processing. Second, we look
at semantics as a channel, viewing Linked Open Data
vocabularies not only as terminological assets but as
communication channels. Third, semantics provide the
methodologies and tools for content modeling by means of
ontologies. Finally, semantics through semantic matchmaking
enable semi-automatic assignment and distribution of content
to channels and vice-versa
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
Development of a Framework for Ontology Population Using Web Scraping in Mechatronics
One of the major challenges in engineering contexts is the efficient collection, management, and sharing of data. To address this problem, semantic technologies and ontologies are potent assets, although some tasks, such as ontology population, usually demand high maintenance effort. This thesis proposes a framework to automate data collection from sparse web resources and insert it into an ontology. In the first place, a product ontology is created based on the combination of several reference vocabularies, namely GoodRelations, the Basic Formal Ontology, ECLASS stan- dard, and an information model. Then, this study introduces a general procedure for developing a web scraping agent to collect data from the web. Subsequently, an algorithm based on lexical similarity measures is presented to map the collected data to the concepts of the ontology. Lastly, the collected data is inserted into the ontology. To validate the proposed solution, this thesis implements the previous steps to collect information about microcontrollers from three differ- ent websites. Finally, the thesis evaluates the use case results, draws conclusions, and suggests promising directions for future research
The OU Linked Open Data: production and consumption
The aim of this paper is to introduce the current efforts toward the release and exploitation of The Open University's (OU) Linked Open Data (LOD). We introduce the work that has been done within the LUCERO project in order to select, extract and structure subsets of information contained within the OU data sources and migrate and expose this information as part of the LOD cloud. To show the potential of such exposure we also introduce three different prototypes that exploit this new educational resource: (1) the OU expert search system, a tool focused on fnding the best experts for a certain topic within the OU staff; (2) the Buddy Study system, a tool that relies on Facebook information to identify common interest among friends and recommend potential courses within the OU that `buddies' can study together, and; (3) Linked OpenLearn, an application that enables exploring linked courses, Podcasts and tags to OpenLearn units. Its aim is to enhance the browsing experience for students, by detecting relevant educational resources on fly while reading an OpenLearn unit
Neural Networks forBuilding Semantic Models and Knowledge Graphs
1noL'abstract è presente nell'allegato / the abstract is in the attachmentopen677. INGEGNERIA INFORMATInoopenFutia, Giusepp
Improving e-commerce fraud investigations in virtual, inter-institutional teams: Towards an approach based on Semantic Web technologies
There is a dramatic shift in credit card fraud from the offline to the online world. Large online retailers have tried to establish countermeasures and transaction data analysis technologies to lower the rate of fraudulent transactions to a manageable amount. But as retailers will always have to make a trade-off between the performance of the transaction processing, the usability of the web shop, and the overall security of it, one can assume that e-commerce fraud will still happen in the future. Thus, retailers have to collaborate with relevant business partners on the incident to find a common ground and take coordinated (legal) actions against it.
Trying to combine the information from different stakeholders will face issues due to different wordings and data formats, competing incentives of the stakeholders to participate on information sharing, as well as possible sharing restrictions that prevent them from making the information available to a larger audience. Moreover, as some of the information might be confidential or business-critical to at least one of the parties involved, a centralized system (e.g. a service in the public cloud) can not be used.
This Master Thesis is therefore analysing how far a computer supported collaborative work system based on peer-to-peer communication and Semantic Web technologies can improve the efficiency and effectivity of e-commerce fraud investigations within an inter-institutional team
- …