A flexible architecture for privacy-aware trust management

In service-oriented systems a constellation of services cooperate, sharing potentially sensitive information and responsibilities. Cooperation is only possible if the different participants trust each other. As trust may depend on many different factors, in a flexible framework for Trust Management (TM) trust must be computed by combining different types of information. In this paper we describe the TAS3 TM framework which integrates independent TM systems into a single trust decision point. The TM framework supports intricate combinations whilst still remaining easily extensible. It also provides a unified trust evaluation interface to the (authorization framework of the) services. We demonstrate the flexibility of the approach by integrating three distinct TM paradigms: reputation-based TM, credential-based TM, and Key Performance Indicator TM. Finally, we discuss privacy concerns in TM systems and the directions to be taken for the definition of a privacy-friendly TM architecture.\u

Ontology mapping: the state of the art

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mapping has beeb the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping

Reusability ontology in business processes with similarity matching

The working technology will provide information and knowledge. Information and technology can be developed in various ways, by reusing the technologies. In this study modeled the ontology of SOPs using protégé. Ontology will be matched between ontology A and B to obtain similarity and reuse ontology to create a more optimal ontology. Matching is a matching process between both ontologies to get the same value from both ontologies. Jaro-Winkler distance is used to find commonality between ontology. The result of the Jaro-Winkler distance has a value of 0 and 1, in matching will be obtained value close to 0 or 1. On matching ontology obtained two tests using 40% SPARQL query. In the test it uses Jaro-Winkler distance with a value of 0.67. This research yields matching value between ontology A and ontology B which is the same so that reuse ontology can be done for better ontolog

An Ontology-Based Recommender System with an Application to the Star Trek Television Franchise

Collaborative filtering based recommender systems have proven to be extremely successful in settings where user preference data on items is abundant. However, collaborative filtering algorithms are hindered by their weakness against the item cold-start problem and general lack of interpretability. Ontology-based recommender systems exploit hierarchical organizations of users and items to enhance browsing, recommendation, and profile construction. While ontology-based approaches address the shortcomings of their collaborative filtering counterparts, ontological organizations of items can be difficult to obtain for items that mostly belong to the same category (e.g., television series episodes). In this paper, we present an ontology-based recommender system that integrates the knowledge represented in a large ontology of literary themes to produce fiction content recommendations. The main novelty of this work is an ontology-based method for computing similarities between items and its integration with the classical Item-KNN (K-nearest neighbors) algorithm. As a study case, we evaluated the proposed method against other approaches by performing the classical rating prediction task on a collection of Star Trek television series episodes in an item cold-start scenario. This transverse evaluation provides insights into the utility of different information resources and methods for the initial stages of recommender system development. We found our proposed method to be a convenient alternative to collaborative filtering approaches for collections of mostly similar items, particularly when other content-based approaches are not applicable or otherwise unavailable. Aside from the new methods, this paper contributes a testbed for future research and an online framework to collaboratively extend the ontology of literary themes to cover other narrative content.Comment: 25 pages, 6 figures, 5 tables, minor revision

The SP theory of intelligence: benefits and applications

This article describes existing and expected benefits of the "SP theory of intelligence", and some potential applications. The theory aims to simplify and integrate ideas across artificial intelligence, mainstream computing, and human perception and cognition, with information compression as a unifying theme. It combines conceptual simplicity with descriptive and explanatory power across several areas of computing and cognition. In the "SP machine" -- an expression of the SP theory which is currently realized in the form of a computer model -- there is potential for an overall simplification of computing systems, including software. The SP theory promises deeper insights and better solutions in several areas of application including, most notably, unsupervised learning, natural language processing, autonomous robots, computer vision, intelligent databases, software engineering, information compression, medical diagnosis and big data. There is also potential in areas such as the semantic web, bioinformatics, structuring of documents, the detection of computer viruses, data fusion, new kinds of computer, and the development of scientific theories. The theory promises seamless integration of structures and functions within and between different areas of application. The potential value, worldwide, of these benefits and applications is at least $190 billion each year. Further development would be facilitated by the creation of a high-parallel, open-source version of the SP machine, available to researchers everywhere.Comment: arXiv admin note: substantial text overlap with arXiv:1212.022

Fuzzy Family Ties: Familial Similarity Between Melodic Contours of Different Cardinalities

All melodies have shape: a pattern of ascents, descents, and plateaus that occur as music moves through time. This shape—or contour—is one of a melody’s defining characteristics. Music theorists such as Michael Friedmann (1985), Robert Morris (1987), Elizabeth Marvin (1987), and Ian Quinn (1997) have developed models for analyzing contour, but only a few compare contours with different numbers of notes (cardinalities), and fewer still compare entire families of contours. Since these models do not account for familial relations between different-sized contours, they apply only to a limited musical repertoire, and therefore it seems unlikely that they reflect how listeners perceive melodic shape. This dissertation introduces a new method for evaluating familial similarities between related contours, even if the contours have different cardinalities. My Familial Contour Membership model extends theories of contour transformation by using fuzzy set theory and probability. I measure a contour’s degree of familial membership by examining the contour’s transformational pathway and calculating the probability that each move in the pathway is shared by other family members. Through the potential of differing alignments along these pathways, I allow for the possibility that pathways may be omitted or inserted within a contour that exhibits familial resemblance, despite its different cardinality. Integrating variable cardinality into contour similarity relations more adequately accounts for familial relationships between contours, opening up new possibilities for analytical application to a wide variety of repertoires. I examine familial relationships between variants of medieval plainchant, and demonstrate how the sensitivity to familial variation illuminated by fuzzy theoretical models can contribute to our understanding of musical ontology. I explain how melodic shape contributes to motivic development and narrative creation in Brahms’s “Regenlied” Op. 59, No. 3, and the related Violin Sonata No. 1, Op. 78. Finally, I explore how melodic shape is perceived within the repetitive context of melodic phasing in Steve Reich’s The Desert Music. Throughout each study, I show that a more flexible attitude toward cardinality can open contour theory to more nuanced judgments of similarity and familial membership, and can provide new and valuable insights into one of music’s most fundamental elements

XML Matchers: approaches and challenges

Schema Matching, i.e. the process of discovering semantic correspondences between concepts adopted in different data source schemas, has been a key topic in Database and Artificial Intelligence research areas for many years. In the past, it was largely investigated especially for classical database models (e.g., E/R schemas, relational databases, etc.). However, in the latest years, the widespread adoption of XML in the most disparate application fields pushed a growing number of researchers to design XML-specific Schema Matching approaches, called XML Matchers, aiming at finding semantic matchings between concepts defined in DTDs and XSDs. XML Matchers do not just take well-known techniques originally designed for other data models and apply them on DTDs/XSDs, but they exploit specific XML features (e.g., the hierarchical structure of a DTD/XSD) to improve the performance of the Schema Matching process. The design of XML Matchers is currently a well-established research area. The main goal of this paper is to provide a detailed description and classification of XML Matchers. We first describe to what extent the specificities of DTDs/XSDs impact on the Schema Matching task. Then we introduce a template, called XML Matcher Template, that describes the main components of an XML Matcher, their role and behavior. We illustrate how each of these components has been implemented in some popular XML Matchers. We consider our XML Matcher Template as the baseline for objectively comparing approaches that, at first glance, might appear as unrelated. The introduction of this template can be useful in the design of future XML Matchers. Finally, we analyze commercial tools implementing XML Matchers and introduce two challenging issues strictly related to this topic, namely XML source clustering and uncertainty management in XML Matchers.Comment: 34 pages, 8 tables, 7 figure

The potential of semantic paradigm in warehousing of big data

Big data have analytical potential that was hard to realize with available technologies. After new storage paradigms intended for big data such as NoSQL databases emerged, traditional systems got pushed out of the focus. The current research is focused on their reconciliation on different levels or paradigm replacement. Similarly, the emergence of NoSQL databases has started to push traditional (relational) data warehouses out of the research and even practical focus. Data warehousing is known for the strict modelling process, capturing the essence of the business processes. For that reason, a mere integration to bridge the NoSQL gap is not enough. It is necessary to deal with this issue on a higher abstraction level during the modelling phase. NoSQL databases generally lack clear, unambiguous schema, making the comprehension of their contents difficult and their integration and analysis harder. This motivated involving semantic web technologies to enrich NoSQL database contents by additional meaning and context. This paper reviews the application of semantics in data integration and data warehousing and analyses its potential in integrating NoSQL data and traditional data warehouses with some focus on document stores. Also, it gives a proposal of the future pursuit directions for the big data warehouse modelling phases