Semantic Web

About: Semantic Web is a research topic. Over the lifetime, 26987 publications have been published within this topic receiving 534275 citations. The topic is also known as: Sem Web & SemWeb.

Ontology evolution: a process-centric survey

Abstract: Ontology evolution aims at maintaining an ontology up to date with respect to changes in the domain that it models or novel requirements of information systems that it enables. The recent industrial adoption of Semantic Web techniques, which rely on ontologies, has led to the increased importance of the ontology evolution research. Typical approaches to ontology evolution are designed as multiple-stage processes combining techniques from a variety of fields (e.g., natural language processing and reasoning). However, the few existing surveys on this topic lack an in-depth analysis of the various stages of the ontology evolution process. This survey extends the literature by adopting a process-centric view of ontology evolution. Accordingly, we first provide an overall process model synthesized from an overview of the existing models in the literature. Then we survey the major approaches to each of the steps in this process and conclude on future challenges for techniques aiming to solve that particular stage.

Sentic Computing for social media marketing

Abstract: In a world in which millions of people express their opinions about commercial products in blogs, wikis, fora, chats and social networks, the distillation of knowledge from this huge amount of unstructured information can be a key factor for marketers who want to create an image or identity in the minds of their customers for their product, brand or organization. Opinion mining for product positioning, in fact, is getting a more and more popular research field but the extraction of useful information from social media is not a simple task. In this work we merge AI and Semantic Web techniques to extract, encode and represent this unstructured information. In particular, we use Sentic Computing, a multi-disciplinary approach to opinion mining and sentiment analysis, to semantically and affectively analyze text and encode results in a semantic aware format according to different web ontologies. Eventually we represent this information as an interconnected knowledge base which is browsable through a multi-faceted classification website.

Effective integration of declarative rules with external evaluations for semantic-web reasoning

Abstract: Towards providing a suitable tool for building the Rule Layer of the Semantic Web, hex-programs have been introduced as a special kind of logic programs featuring capabilities for higher-order reasoning, interfacing with external sources of computation, and default negation. Their semantics is based on the notion of answer sets, providing a transparent interoperability with the Ontology Layer of the Semantic Web and full declarativity. In this paper, we identify classes of hex-programs feasible for implementation yet keeping the desirable advantages of the full language. A general method for combining and evaluating sub-programs belonging to arbitrary classes is introduced, thus enlarging the variety of programs whose execution is practicable. Implementation activity on the current prototype is also reported.

Ontology Merging for Federated Ontologies for the Semantic Web

Abstract: One of the core challenges for the Semantic Web is the aspect of decentralization. Local structures can be modeled by ontologies. However, in order to support global communication and knowledge exchange, mechanisms have to be developed for integrating the local systems. We adopt the database approach of autonomous federated database systems and consider an architecture for federated ontologies for the Semantic Web as starting point of our work. We identify the need for merging specific ontologies for developing federated, but still autonomous web systems. We present the method FCA–MERGE for merging ontologies following a bottom-up approach which offers a structural description of the merging process. The method is guided by application-specific instances of the given source ontologies that are to be merged. We apply techniques from natural language processing and formal concept analysis to derive a lattice of concepts as a structural result of FCA–MERGE. The generated result is then explored and transformed into the merged ontology with human interaction.

Engineering Semantic Web Information Systems in Hera.

Abstract: The success of the World Wide Web has caused the concepts of information system to change. Web Information Systems (WIS) use from the Web its paradigm and technologies in order to retrieve information from sources on the Web, and to present the information in terms of a Web or hypermedia presentation. Hera is a methodology that supports the design and engineering of WIS. It is a model-driven methodology that distinguishes three parts in the design: integration, data retrieval, and presentation generation. The integration part manages the gathering of data from different sources on the basis of source ontologies and mappings between those source ontologies and the conceptual model of the WIS. The data retrieval part handles the user queries and produces the data that represents the query result. In the presentation generation part this query result is trasformed into a Web presentation and that presentation is constructed to suit the user (platform), e.g. HTML, WML, or SMIL. In this paper we address the Hera design methodology and specifically explain two models: the integration model that covers the different aspects of integration, and the adaptation model that specifies how the generated presentations can be adaptable (e.g. based on device capabilities, user preferences) and adaptive (e.g. based on user browsing history). This detailed description includes an explanation of how the Hera software is constructed. This software provides a set of trasformations that allow a WIS to go from integration to presentation generation. These transformations are based on RDF(S), the foundation of the Semantic Web. We show how RDF(S) has proven its value in combining all relevant aspects of WIS design, thus illustrating how Hera allows the engineering of Semantic Web Information Systems (SWIS).