Fuzzy Web Knowledge Aggregation, Representation, and Reasoning for Online Privacy and Reputation Management

A social Semantic Web empowers its users to have access to collective Web knowledge in a simple manner, and for that reason, controlling online privacy and reputation becomes increasingly important, and must be taken seriously. This chapter presents Fuzzy Cognitive Maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. With this in mind, a conceptual framework for Web knowledge aggregation, representation, and reasoning is introduced along with a use case, in which the importance of investigative searching for online privacy and reputation is highlighted. Thereby it is demonstrated how a user can establish a positive online presence.

A Restriction-Centered Theory of Reasoning and Computation to materialize a Web 3.0

Researchers suggest that personalization on the Semantic Web adds up to a Web 3.0 eventually. In this Web, personalized agents process and thus generate the biggest share of information rather than humans. In the sense of emergent semantics, which supplements traditional formal semantics of the Semantic Web, this is well conceivable. An emergent Semantic Web underlying fuzzy grassroots ontology can be accomplished through inducing knowledge from users' common parlance in mutual Web 2.0 interactions [1]. These ontologies can also be matched against existing Semantic Web ontologies, to create comprehensive top-level ontologies. On the Web, if augmented with information in the form of restrictions andassociated reliability (Z-numbers) [2], this collection of fuzzy ontologies constitutes an important basis for an implementation of Zadeh's restriction-centered theory of reasoning and computation (RRC) [3]. By considering real world's fuzziness, RRC differs from traditional approaches because it can handle restrictions described in natural language. A restriction is an answer to a question of the value of a variable such as the duration of an appointment. In addition to mathematically well-defined answers, RRC can likewise deal with unprecisiated answers as "about one hour." Inspired by mental functions, it constitutes an important basis to leverage present-day Web efforts to a natural Web 3.0. Based on natural language information, RRC may be accomplished with Z-number calculation to achieve a personalized Web reasoning and computation. Finally, through Web agents' understanding of natural language, they can react to humans more intuitively and thus generate and process information.

The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases

This chapter presents fuzzy cognitive maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. The corresponding Web KnowARR framework incorporates findings from fuzzy logic. To this end, a first emphasis is particularly on the Web KnowARR framework along with a stakeholder management use case to illustrate the framework’s usefulness as a second focal point. This management form is to help projects to acceptance and assertiveness where claims for company decisions are actively involved in the management process. Stakeholder maps visually (re-) present these claims. On one hand, they resort to non-public content and on the other they resort to content that is available to the public (mostly on the Web). The Semantic Web offers opportunities not only to present public content descriptively but also to show relationships. The proposed framework can serve as the basis for the public content of stakeholder maps.

De los registros a los objetos : Semántica y comportamiento de los documentos: el desafío de la Web 3.0

Se presenta un panorama y los interrogantes fundamentales de la etapa de la Web 3.0. Se analizan las características actuales de los sistemas bibliográficos estructurados con el modelo entidad-relación. Se definen los niveles conceptual, lógico y físico en los sistemas informáticos; consecuentemente se presentan las características de los FRBR y se obervan las relaciones entre obra y documento en el modelo conceptual FRBR. Se describen los FRBRoo como una interpretación con una lógica de objetos de los mismos requerimientos funcionales. Finalmente se plantean las tendencias a futuro, tales como pasar de las modelizaciones de entidad-relación a la de objetos, la explicitación con anotación semántica consistente, el mapeo de bases bibliográficas existentes y el desarrollo de ontologías para que los sistemas documentales se integren en la Web Semática

De los registros a los objetos : Semántica y comportamiento de los documentos: el desafío de la Web 3.0

Se presenta un panorama y los interrogantes fundamentales de la etapa de la Web 3.0. Se analizan las características actuales de los sistemas bibliográficos estructurados con el modelo entidad-relación. Se definen los niveles conceptual, lógico y físico en los sistemas informáticos; consecuentemente se presentan las características de los FRBR y se obervan las relaciones entre obra y documento en el modelo conceptual FRBR. Se describen los FRBRoo como una interpretación con una lógica de objetos de los mismos requerimientos funcionales. Finalmente se plantean las tendencias a futuro, tales como pasar de las modelizaciones de entidad-relación a la de objetos, la explicitación con anotación semántica consistente, el mapeo de bases bibliográficas existentes y el desarrollo de ontologías para que los sistemas documentales se integren en la Web Semática

De los registros a los objetos : Semántica y comportamiento de los documentos: el desafío de la Web 3.0

Se presenta un panorama y los interrogantes fundamentales de la etapa de la Web 3.0. Se analizan las características actuales de los sistemas bibliográficos estructurados con el modelo entidad-relación. Se definen los niveles conceptual, lógico y físico en los sistemas informáticos; consecuentemente se presentan las características de los FRBR y se obervan las relaciones entre obra y documento en el modelo conceptual FRBR. Se describen los FRBRoo como una interpretación con una lógica de objetos de los mismos requerimientos funcionales. Finalmente se plantean las tendencias a futuro, tales como pasar de las modelizaciones de entidad-relación a la de objetos, la explicitación con anotación semántica consistente, el mapeo de bases bibliográficas existentes y el desarrollo de ontologías para que los sistemas documentales se integren en la Web Semática

The state of semantic technology today - overview of the first SEALS evaluation campaigns

This paper describes the first five SEALS Evaluation Campaigns over the semantic technologies covered by the SEALS project (ontology engineering tools, ontology reasoning tools, ontology matching tools, semantic search tools, and semantic web service tools). It presents the evaluations and test data used in these campaigns and the tools that participated in them along with a comparative analysis of their results. It also presents some lessons learnt after the execution of the evaluation campaigns and draws some final conclusions.

Style Guidelines for Naming and Labeling Ontologies in the Multilingual Web

In the context of the Semantic Web, natural language descriptions associated with ontologies have proven to be of major importance not only to support ontology developers and adopters, but also to assist in tasks such as ontology mapping, information extraction, or natural language generation. In the state-of-the-art we find some attempts to provide guidelines for URI local names in English, and also some disagreement on the use of URIs for describing ontology elements. When trying to extrapolate these ideas to a multilingual scenario, some of these approaches fail to provide a valid solution. On the basis of some real experiences in the translation of ontologies from English into Spanish, we provide a preliminary set of guidelines for naming and labeling ontologies in a multilingual scenario.

Using SCXML to integrate semantic sensor information into context-aware user interfaces

This paper describes a novel architecture to introduce automatic annotation and processing of semantic sensor data within context-aware applications. Based on the well-known state-charts technologies, and represented using W3C SCXML language combined with Semantic Web technologies, our architecture is able to provide enriched higher-level semantic representations of user’s context. This capability to detect and model relevant user situations allows a seamless modeling of the actual interaction situation, which can be integrated during the design of multimodal user interfaces (also based on SCXML) for them to be adequately adapted. Therefore, the final result of this contribution can be described as a flexible context-aware SCXML-based architecture, suitable for both designing a wide range of multimodal context-aware user interfaces, and implementing the automatic enrichment of sensor data, making it available to the entire Semantic Sensor Web

Linked Opinions: Describing Sentiments on the Structured Web of Data

In the paper we report on the results of our experiments on the construction of the opinion ontology. Our aim is to show the benefits of publishing in the open, on the Web, the results of the opinion mining process in a structured form. On the road to achieving this, we attempt to answer the research question to what extent opinion information can be formalized in a unified way. Furthermore, as part of the evaluation, we experiment with the usage of Semantic Web technologies and show particular use cases that support our claims.

Cross-lingual Linking on the Multilingual Web of Data (position statement)

Recently, the Semantic Web has experienced signi�cant advancements in standards and techniques, as well as in the amount of semantic information available online. Even so, mechanisms are still needed to automatically reconcile semantic information when it is expressed in di�erent natural languages, so that access to Web information across language barriers can be improved. That requires developing techniques for discovering and representing cross-lingual links on the Web of Data. In this paper we explore the different dimensions of such a problem and reflect on possible avenues of research on that topic.

Challenges for the Multilingual Web of Data

The Web has witnessed an enormous growth in the amount of semantic information published in recent years. This growth has been stimulated to a large extent by the emergence of Linked Data. Although this brings us a big step closer to the vision of a Semantic Web, it also raises new issues such as the need for dealing with information expressed in different natural languages. Indeed, although the Web of Data can contain any kind of information in any language, it still lacks explicit mechanisms to automatically reconcile such information when it is expressed in different languages. This leads to situations in which data expressed in a certain language is not easily accessible to speakers of other languages. The Web of Data shows the potential for being extended to a truly multilingual web as vocabularies and data can be published in a language-independent fashion, while associated language-dependent (linguistic) information supporting the access across languages can be stored separately. In this sense, the multilingual Web of Data can be realized in our view as a layer of services and resources on top of the existing Linked Data infrastructure adding i) linguistic information for data and vocabularies in different languages, ii) mappings between data with labels in different languages, and iii) services to dynamically access and traverse Linked Data across different languages. In this article we present this vision of a multilingual Web of Data. We discuss challenges that need to be addressed to make this vision come true and discuss the role that techniques such as ontology localization, ontology mapping, and cross-lingual ontology-based information access and presentation will play in achieving this. Further, we propose an initial architecture and describe a roadmap that can provide a basis for the implementation of this vision.

What is the current state of the Multilingual Web of Data?

The Semantic Web is growing at a fast pace, recently boosted by the creation of the Linked Data initiative and principles. Methods, standards, techniques and the state of technology are becoming more mature and therefore are easing the task of publication and consumption of semantic information on the Web.

Using Cross-Lingual Explicit Semantic Analysis for Improving Ontology Translation

Semantic Web aims to allow machines to make inferences using the explicit conceptualisations contained in ontologies. By pointing to ontologies, Semantic Web-based applications are able to inter-operate and share common information easily. Nevertheless, multilingual semantic applications are still rare, owing to the fact that most online ontologies are monolingual in English. In order to solve this issue, techniques for ontology localisation and translation are needed. However, traditional machine translation is difficult to apply to ontologies, owing to the fact that ontology labels tend to be quite short in length and linguistically different from the free text paradigm. In this paper, we propose an approach to enhance machine translation of ontologies based on exploiting the well-structured concept descriptions contained in the ontology. In particular, our approach leverages the semantics contained in the ontology by using Cross Lingual Explicit Semantic Analysis (CLESA) for context-based disambiguation in phrase-based Statistical Machine Translation (SMT). The presented work is novel in the sense that application of CLESA in SMT has not been performed earlier to the best of our knowledge.

Translational research combining orthologous genes and human diseases with the OGOLOD dataset

OGOLOD is a Linked Open Data dataset derived from different biomedical resources by an automated pipeline, using a tailored ontology as a scaffold. The key contribution of OGOLOD is that it links, in new RDF triples, genetic human diseases and orthologous genes, paving the way for a more efficient translational biomedical research exploiting the Linked Open Data cloud.