Intuitionistic fuzzy XML query matching and rewriting

With the emergence of XML as a standard for data representation, particularly on the web, the need for intelligent query languages that can operate on XML documents with structural heterogeneity has recently gained a lot of popularity. Traditional Information Retrieval and Database approaches have limitations when dealing with such scenarios. Therefore, fuzzy (flexible) approaches have become the predominant. In this thesis, we propose a new approach for approximate XML query matching and rewriting which aims at achieving soft matching of XML queries with XML data sources following different schemas. Unlike traditional querying approaches, which require exact matching, the proposed approach makes use of Intuitionistic Fuzzy Trees to achieve approximate (soft) query matching. Through this new approach, not only the exact answer of a query, but also approximate answers are retrieved. Furthermore, partial results can be obtained from multiple data sources and merged together to produce a single answer to a query. The proposed approach introduced a new tree similarity measure that considers the minimum and maximum degrees of similarity/inclusion of trees that are based on arc matching. New techniques for soft node and arc matching were presented for matching queries against data sources with highly varied structures. A prototype was developed to test the proposed ideas and it proved the ability to achieve approximate matching for pattern queries with a number of XML schemas and rewrite the original query so that it obtain results from the underlying data sources. This has been achieved through several novel algorithms which were tested and proved efficiency and low CPU/Memory cost even for big number of data sources

Interval Neutrosophic Sets and Logic: Theory and Applications in Computing

A neutrosophic set is a part of neutrosophy that studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. The neutrosophic set is a powerful general formal framework that has been recently proposed. However, the neutrosophic set needs to be specified from a technical point of view. Here, we define the set-theoretic operators on an instance of a neutrosophic set, and call it an Interval Neutrosophic Set (INS). We prove various properties of INS, which are connected to operations and relations over INS. We also introduce a new logic system based on interval neutrosophic sets. We study the interval neutrosophic propositional calculus and interval neutrosophic predicate calculus. We also create a neutrosophic logic inference system based on interval neutrosophic logic. Under the framework of the interval neutrosophic set, we propose a data model based on the special case of the interval neutrosophic sets called Neutrosophic Data Model. This data model is the extension of fuzzy data model and paraconsistent data model. We generalize the set-theoretic operators and relation-theoretic operators of fuzzy relations and paraconsistent relations to neutrosophic relations. We propose the generalized SQL query constructs and tuple-relational calculus for Neutrosophic Data Model. We also design an architecture of Semantic Web Services agent based on the interval neutrosophic logic and do the simulation study

Quality of Service (QoS) in SOA Systems. A Systematic Review

In the last recent years a new technology called Web Services has emerged. The main characteristic of a web service is that it is a piece of software that the user can utilize but doesn’t own, that is, the user doesn’t install the software but uses it through the internet and standard protocols. With this new technology, a new architecture paradigm called SOA (Service Oriented Architecture) has appeared. This architecture is based on combining several web services, each one responsible to develop a concrete task, in order to obtain full‐operational software. The web services that compose a SOA System might be able to perform a task in a certain time, might be unavailable in some cases, might have security policies, etc. All this attributes, named Quality attributes, are essential in order to choose the appropriate web service for a SOA System. The objective of this Master Thesis is focused on two different but related subjects: (1) The development of a review regarding to the Quality Attributes for web services in a systematic manner and the development of a tool for monitoring SOA Systems capable to be used in several frameworks such as for Self‐Adaptive SOA Systems and for Web Service Discovery Systems

Personalized Web Content with Fuzzy System

In this paper, we will develop a new computational intelligence methodology to automatically analyze and summarize web content during a user surfing sessions. The output of this process is meaningful keywords or phrases which will be used to bring the user other contents such as images that closely relate to the web pages that he or she is currently surfing

JSON Schemas with Semantic Annotations Supporting Data Translation

Funding Information: Funding: This research was partially funded by EU ECSEL Joint Undertaking (JU) under grant agreement n° 826452 (project Arrowhead Tools).As service-oriented architectures are a solution for large distributed systems, interoperabil-ity between these systems, which are often heterogeneous, can be a challenge due to the different syntax and semantics of the exchanged messages or even different data interchange formats. This paper addresses the data interchange format and data interoperability issues between XML-based and JSON-based systems. It proposes novel annotation mechanisms to add semantic annotations and complement date values to JSON Schemas, enabling an interoperability approach for JSON-based systems that, until now, was only possible for XML-based systems. A set of algorithms supporting the translation from JSON Schema to XML Schema, JSON to XML, and XML to JSON is also pro-posed. These algorithms were implemented in an existing prototype tool, which now supports these systems’ interoperability through semantic compatibility verification and the automatic generation of translators.publishersversionpublishe

Yago - a core of semantic knowledge

We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains roughly 900,000 entities and 5,000,000 facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as relation{hasWonPrize}). The facts have been automatically extracted from the unification of Wikipedia and WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships -- and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques