Web Language Research Articles

Decision trees in automatic ontology matching

The semantic web progress gave rise to a growing number of ontologies in various fields. In order to allow knowledge reuse, ontology matching is an interesting option. In this paper, we propose an ontology matching system that performs class, property and instance matching. This latter is usually achieved by means of Natural Language Processing NLP techniques, which are context dependent. To avoid the limits of NLP, we use a decision tree-based instance matching scheme. Decision tree is one of the most widely used learning algorithms for inductive inference and classification. Our system works on OWL-DL ontologies, that is ontologies expressed in the Description Logic version of the Ontology Web Language. This ensures the maximum of expressiveness, completeness and decidability. Our approach is tested with the benchmark and conference tracks of the OAEI'2015 campaign. It shows very promising results since it outperforms other matching systems in most of the test cases.

Fuzzy Grammaticality Models: A Tool for Web Language Analysis

In this paper, we highlight the need to propose formal models that consider grammaticality as a gradient property instead of the categorical view of grammaticality defended in theoretical linguistics. Given that deviations from the norm are inherent to the spontaneous use of language, linguistic analysis tools should account for different levels of grammaticality. Fuzzy grammaticality models may be a way to solve the problem that the so-called “noisy text” poses to parsing mechanisms used in Web language analysis–especially social networks language.

Indonesian-english cross-lingual legal ontology for information retrieval

This research encompasses the construction of a multilingual lexical database for cross-lingual information retrieval in the Indonesian legal domain. Multilingual lexical database featuring lexically and legally grounded conceptual representation can fit the cross-lingual information retrieval. Lexical database use Ontology Web Language (OWL) representation language. This representation is useful to provide application developers a high-quality resource and to promote interoperability.

Hadoop-based Crawling and Detection of New HTML5 Vulnerabilities on Public Institutions’ Web Sites

HTML5 is a recent version of HTML, a programming language for web documents. It was developed to solve the problems of previous HTML versions. However, the new elements and functions of HTML5 have expanded the range of attacks that third parties can abuse. This is especially the case for public institutions which apply HTML5 in their web sites, and means that their web sites are more vulnerable to these attacks than other private websites. Public institutions’ web sites consist of a larger number of web documents than other general web sites because the web sites provide information regarding policies, voting, and other events, and are connected with subordinate institutions. In this paper, because public institutions web sites consist of a large number of web documents, we used Hadoop, which is an open-source framework for distributed storage and processing. HTML5 vulnerabilities detection was processed for a large number of web documents by using distributed parallel processing. By applying distributed parallel processing for the crawling and detecting processes, we were able to improve the performance of the crawling and detecting processes for a large number of web documents connected to public institutions web sites.

Towards a Semantic Network of Dante’s Works and Their Contextual Knowledge

We present the achievements of the ‘Towards a Digital Dante Encyclopaedia’ project, a 3-year Italian National Research Project that aims at building a digital library endowed with services supporting scholars in creating, evolving, and consulting a digital encyclopaedia of Dante Alighieri and his works. Our main goal is to represent and visualize the knowledge of the primary sources that Dante refers to in his works. Currently, this information is scattered in many books, making it difficult to systematically overview the culture of Dante in order to obtain a well-founded perception of how this culture was gradually constructed over time. We describe a semantic representation of the involved texts and knowledge based on the Semantic Web languages. The representation is freely available as an XML document, and it can be easily acquired, e.g. by other researchers in order to extend the representation with additional texts and knowledge. We also present a web application that allows users to extract and display these texts and knowledge in the form of charts and tables. In particular, the application supports the visualization of the data related to the primary sources according to different parameters (e.g. in chronological order, by author, by work). Furthermore, it allows exploring the dynamics of the multi-faceted culture of Dante in relation to the diverse and often conflicting stages of his biography.

Certificate sharing system for secure certificate distribution in mobile environment

As mobile and Internet technologies evolve, mobile services (e.g., Internet banking, social commerce) continuously expand and diversify. In order to use these mobile services, it is essential that security services, especially distribution certificates (e.g., bank certificates), relevant to mobile devices be provided. Some approaches to providing distribution certificates between a user's mobile device and a personal computer (PC) have been proposed. However, the existing approaches do not guarantee that the certificate in the mobile devices same with the issued one from the PC, causing constraints on mobile services such as mobile phone banking and mobile commerce (M-commerce).In this paper, we propose a novel approach that shares certificates securely without modification of the existing standard certificate format between a smartphone and a PC. We also implemented the certificate sharing system (CSS) in a virtual private network (VPN). The CSS provides strong end-to-end data security for the certificate with a key size of 192-bits which is able to guarantee an expiration date of three years. It also provides strong data security on physical devices with the use of device ID. The certificate that is shared between devices is available only through the CSS's authorization process. In addition, the CSS provides a flexible and extensible system for sharing certificates in enterprise environments. The CSS module of a PC was implemented by way of a standard web language, and the CSS module of a smartphone was developed with the assistance of mobile applications with a small size of 1210KB.

An ontology for Autism Spectrum Disorder (ASD) to infer ASD phenotypes from Autism Diagnostic Interview-Revised data

ObjectiveOur goal is to create an ontology that will allow data integration and reasoning with subject data to classify subjects, and based on this classification, to infer new knowledge on Autism Spectrum Disorder (ASD) and related neurodevelopmental disorders (NDD). We take a first step toward this goal by extending an existing autism ontology to allow automatic inference of ASD phenotypes and Diagnostic & Statistical Manual of Mental Disorders (DSM) criteria based on subjects’ Autism Diagnostic Interview-Revised (ADI-R) assessment data. Materials and methodsKnowledge regarding diagnostic instruments, ASD phenotypes and risk factors was added to augment an existing autism ontology via Ontology Web Language class definitions and semantic web rules. We developed a custom Protégé plugin for enumerating combinatorial OWL axioms to support the many-to-many relations of ADI-R items to diagnostic categories in the DSM. We utilized a reasoner to infer whether 2642 subjects, whose data was obtained from the Simons Foundation Autism Research Initiative, meet DSM-IV-TR (DSM-IV) and DSM-5 diagnostic criteria based on their ADI-R data. ResultsWe extended the ontology by adding 443 classes and 632 rules that represent phenotypes, along with their synonyms, environmental risk factors, and frequency of comorbidities. Applying the rules on the data set showed that the method produced accurate results: the true positive and true negative rates for inferring autistic disorder diagnosis according to DSM-IV criteria were 1 and 0.065, respectively; the true positive rate for inferring ASD based on DSM-5 criteria was 0.94. DiscussionThe ontology allows automatic inference of subjects’ disease phenotypes and diagnosis with high accuracy. ConclusionThe ontology may benefit future studies by serving as a knowledge base for ASD. In addition, by adding knowledge of related NDDs, commonalities and differences in manifestations and risk factors could be automatically inferred, contributing to the understanding of ASD pathophysiology.

Unified Data Model for Wireless Sensor Network

The constant evolution of technology in terms of inexpensive and embedded wireless interfaces and powerful chipsets has led to the massive usage and deployment of wireless sensors networks (WSNs). These networks are made of a growing number of small sensing devices and are used in multiple use cases, such as home automation (e.g., smart buildings), energy management and smart grids, crisis management and security, e-Health, entertainment, and so forth. Sensor devices, generally self-organized in clusters and domain dedicated, are provided by an increasing number of manufacturers, which leads to interoperability problems (e.g., heterogeneous interfaces and/or grounding, heterogeneous descriptions, profiles, models, and so forth). Furthermore, the data provided by these WSNs are very heterogeneous because they are coming from sensing nodes with various abilities (e.g., different sensing ranges, formats, coding schemes, and so forth). In this paper, we propose a solution for handling WSNs’ heterogeneity, as well as easing interoperability management. The solution consists of a semantic open data model for sensor and sensor data generic description. This data model, designed for handling any kind of sensors/actuators and measured data (which is still not the case of existing WSNs data models), is fully detailed and formalized in an original ontology format called MyOntoSens and written using Ontology Web Language 2 description logic language. The proposed ontology has been implemented using Protege 4.3, prevalidated with pellet reasoner, and is being standardized (A Body Area Network (BAN) dedicated instance of the proposed “MyOntoSens” ontology is being standardized as a Technical Specification (TS) within the SmartBAN Technical Committee of the ETSI (European Telecommunications Standards Institute) standardization body: ETSI SmartBAN Technical Committee website: portal.etsi.org/portal/server.pt/community/SmartBAN/368v). In addition, this original ontology has been prequalified through a runner’s exercise monitoring application, using in particular SPARQL query language, within a small wireless body area network platform comprising heartbeat, GPS sensors, and Android mobile phones.

A Framework for Geographic Object-Based Image Analysis (GEOBIA) based on geographic ontology

Abstract. GEOBIA (Geographic Object-Based Image Analysis) is not only a hot topic of current remote sensing and geographical research. It is believed to be a paradigm in remote sensing and GIScience. The lack of a systematic approach designed to conceptualize and formalize the class definitions makes GEOBIA a highly subjective and difficult method to reproduce. This paper aims to put forward a framework for GEOBIA based on geographic ontology theory, which could implement "Geographic entities - Image objects - Geographic objects" true reappearance. It consists of three steps, first, geographical entities are described by geographic ontology, second, semantic network model is built based on OWL(ontology web language), at last, geographical objects are classified with decision rule or other classifiers. A case study of farmland ontology was conducted for describing the framework. The strength of this framework is that it provides interpretation strategies and global framework for GEOBIA with the property of objective, overall, universal, universality, etc., which avoids inconsistencies caused by different experts’ experience and provides an objective model for mage analysis.

Report on the Seventh Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR'14)

There is an increasing amount of structure on the Web as a result of modern Web languages, user tagging and annotation, emerging robust NLP tools, and an ever growing volume of linked data. These meaningful, semantic, annotations hold the promise to significantly enhance information access, by enhancing the depth of analysis of today's systems. The goal of the ESAIR'14 workshop remained to advance the general research agenda on this core problem, with an explicit focus on one of the most challenging aspects to address in the coming years. The main remaining challenge is on the user's side---the potential of rich document annotations can only be realized if matched by more articulate queries exploiting these powerful retrieval cues---and a more dynamic approach is emerging by exploiting new forms of query autosuggest. How can the query suggestion paradigm be used to encourage searcher to articulate longer queries, with concepts and relations linking their statement of request to existing semantic models? How do entity results and social network data in "graph search" change the classic division between searchers and information and lead to extreme personalization---are you the query? How to leverage transaction logs and recommendation, and how adaptive should we make the system? What are the privacy ramifications and the UX aspects---how to not creep out users. There was a strong feeling that we made substantial progress. Specifically, the discussion contributed to our understanding of the way forward. First, for notable (head, shoulder, but not tail) entities in semantic search we have reached the level of quality at minimal costs allowing for deployment in major web search engines---the dream has become a reality. Second, entity detection is moving fast into domain specific, personal, and business domains, and has become a vital component for a range of applications. Third, semantic web has exchanged logic for machine learning approaches, and machine learning is the natural unification of semantic web and information retrieval approaches.

Scalpel and Metaphor: The Ceremony of Organ Harvest in Gothic Science Fiction

In organ transfer, tissue moves through a web of language. Metaphors reclassify the tissue to enable its redeployment, framing the process for practitioners and public. The process of marking off tissue as transferrable in legal and cultural terms parallels many of the processes that typically accompany commodification in late capitalism. This language of economic transformation echoes the language of Gothic ceremony, of purification and demarcation. As in literary Gothic' s representations of ceremony, this economic work is anxious and the boundaries it creates unstable. This article identifies dominant metaphors shaping that ceremony of tissue reclassifi cation, and examines how three twenty-first century novels deploy these metaphors to represent the' harvest' (procurement) process (the metaphor of' harvest'; is itself highly problematic, as I will discuss). Kazuo Ishiguro's Never Let Me Go (2005), Neal Shusterman Unwind (2007), and Ninni Holmqvist's Swedish novel Enhet (The Unit) (2006, translated into English in 2010) each depict vulnerable protagonists within societies where extreme tissue procurement protocols have state sanction. The texts invite us to reflect on the kinds of symbolic substitutions that help legitimate tissue transfer and the way that procurement protocols may become influenced by social imperatives. In each text, the Gothic trope of dismemberment becomes charged with new urgency.

Pain and Physical Functioning in Neuropathic Pain: A Systematic Review of Psychometric Properties of Various Outcome Measures.

A range of outcome measures across various domains are used to evaluate change following an intervention in clinical trials on chronic neuropathic pain (NeP). However, to capture a real change in the variable of interest, the psychometric properties of a particular measure should demonstrate appropriate methodological quality. Various outcome measures in the domains of pain and physical functioning have been used in the literature for NeP, for which individual properties (eg, reliability/validity) have been reported. To date, there is no definitive synthesis of evidence on the psychometric properties of those outcome measures; thus, the aim of this systematic review was to evaluate the methodological quality [COnsensus-based Standards for the selection of health status Measurement INstruments (COSMIN) guidelines] of studies that evaluated psychometric properties of pain and physical functioning outcome measures used for NeP. Specific MeSH/keywords related to 3 areas (pain and/or physical functioning, psychometric properties, and NeP) were used to retrieve relevant studies (English language) in key electronic databases (MEDLINE (Ovid), CINAHL (EBSCO), Scopus, AMED, and Web of Science) from database inception-July 2012. Articles retrieval/screening and quality analysis (COSMIN) were carried out by 2 independent reviewers. Twenty-four pain and thirty-seven physical functioning outcome measures were identified, varying in methodological quality from poor-excellent. Although a variety of pain and physical functioning outcome measures have been reported in the literature, few have demonstrate methodologically strong psychometric properties. Thus, future research is required to further investigate the psychometric properties of existing pain and physical functioning outcome measures used for clinical and research purposes.

자동차 기능안전성을 위한 온톨로지 기반의 위험원 분석 및 위험 평가

The ISO 26262 standard requires a preliminary hazard analysis and risk assesment early in the development for automotive system. This is a first step for the development of an automotive system to determine the necessary safety measures to be implemented for a certain function. In this paper, we propose an ontology-based hazard analysis and risk assessment method for automotive functional safety. We use ontology to model the hazard and SWRL(Semantic Web Language) to describe risk analysis. The applicability of the proposed method is evaluated by the case study of an ESCL(electronic steering column lock) system. The result show that ontology deduction is useful for improving consistency and accuracy of hazard analysis and risk assessment. ▸

An integrated dataset of energy efficiency measures published as linked open data

Despite an extensive energy efficiency potential, measures are sometimes not adopted due to barriers, such as lack of information. An integrated database of available energy efficiency measures, which has not existed previously, is one step towards overcoming such barriers. To address this, we present a dataset (i.e., data-base) integrating energy efficiency data from Sweden (from the Swedish Energy Agency) and the USA (from the Department of Energy’s Industrial Assessment Centers), and publishing the data on the Web, using standardized Web languages and following the principles and best practices of so-called linked data. Additionally, several demonstration interfaces to access the data are provided, in order to show the potential of the result. These are entirely novel results, since this is the first dataset we are aware of that publishes this type of data using linked data principles and standards, thus integrating data from entirely different sources making them jointly searchable and reusable. Our results show that such data integration is possible, and that the integrated dataset has several benefits for different categories of users, e.g., supporting industry and energy efficiency auditors in overcoming the information barrier for investment in energy efficiency measures, and supporting application developers to more easily integrate such data into support tools for energy efficiency assessment.

Knowledge Representation Using Type-2 Fuzzy Rough Ontologies in Ontology Web Language

Nowadays semantic web languages play a vital role in representing ontologies. In order to deal with uncertainty in the semantic web languages, we need a concrete procedure to represent such information. We may tackle this problem by extending the current semantic web languages with uncertainty. In this article, we extend the current standard language OWL2 (version 2 of the Web Ontology Language), to deal with uncertainty features and also propose an appropriate methodology to represent type-2 fuzzy rough ontologies by the aid of OWL2 annotation properties. We also provide a plug-in, used to edit type-2 fuzzy rough ontologies using OWL2 annotation properties and parsers that translate the type-2 fuzzy rough ontologies into the languages supported by current description logic (DL) reasoners. Moreover, we conduct a large user group study to prove the effectiveness of the proposed work.

Granulation-based resource classification in Cloud Manufacturing

Cloud Manufacturing, a new manufacturing mode, has the characteristics of service-oriented, knowledge-based, high efficiency and low consumption. Resource virtualization is critical for Cloud Manufacturing, which describes physical resources as cloud services. In this article, a resource virtualization method is proposed for sharing manufacturing resources. By analyzing features of Cloud Manufacturing resources, a multilevel resource virtualization framework is constructed. A multi-granularity resource classification algorithm is presented for cloud services encapsulation, based on which physical resources are flexibly composed to respond business opportunities. Ontology, the fundamental of the proposed method, is implemented by Web Ontology Language and Semantic Web Rule Language, along with a case study validating the proposed method.

Semantic framework for mapping object-oriented model to semantic web languages.

The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.

Examining the risk reduction strategies of actors in online criminal markets

Research examining offender risk reduction strategies within illicit markets focus primarily on those operating in the real world for drugs and stolen goods. Few have considered the strategies that may be used by individuals in virtual illicit markets that are hidden from public view. This study addresses this gap through a grounded theory analysis of posts from 10 Russian and three English language web forums selling stolen data to engage in identity theft and fraud. The findings indicate that buyers employ multiple strategies to reduce their risk of loss from unreliable vendors, along with resources provided by forum administrators to manage relationships between participants. The implications of this study for law enforcement and offender decision-making research are also discussed.

Transforming XML documents to OWL ontologies: A survey

The aims of XML data conversion to ontologies are the indexing, integration and enrichment of existing ontologies with knowledge acquired from these sources. The contribution of this paper consists in providing a classification of the approaches used for the conversion of XML documents into OWL ontologies. This classification underlines the usage profile of each conversion method, providing a clear description of the advantages and drawbacks belonging to each method. Hence, this paper focuses on two main processes, which are ontology enrichment and ontology population using XML data. Ontology enrichment is related to the schema of the ontology (TBox), and ontology population is related to an individual (Abox). In addition, the ontologies described in these methods are based on formal languages of the Semantic Web such as OWL (Ontology Web Language) or RDF (Resource Description Framework). These languages are formal because the semantics are formally defined and take advantage of the Description Logics. In contrast, XML data sources are without formal semantics. The XML language is used to store, export and share data between processes able to process the specific data structure. However, even if the semantics is not explicitly expressed, data structure contains the universe of discourse by using a qualified vocabulary regarding a consensual agreement. In order to formalize this semantics, the OWL language provides rich logical constraints. Therefore, these logical constraints are evolved in the transformation of XML documents into OWL documents, allowing the enrichment and the population of the target ontology. To design such a transformation, the current research field establishes connections between OWL constructs (classes, predicates, simple or complex data types, etc.) and XML constructs (elements, attributes, element lists, etc.). Two different approaches for the transformation process are exposed. The instance approaches are based on XML documents without any schema associated. The validation approaches are based on the XML schema and document validated by the associated schema. The second approaches benefit from the schema definition to provide automated transformations with logic constraints. Both approaches are discussed in the text.

A framework to canonicalize manufacturing service capability models

The capability to share precisely defined information models, which reveal a supplier’s manufacturing service capability (MSC) with anyone who needs it, is key to the creation of more agile supply chains. Today, unfortunately, this capability does not exist. Why? Because most suppliers use proprietary information models to represent and share their MSC information! This limits both the semantic precision in the models, which is needed for interoperability, and the level of agility in the supply chains. The availability of a semantically precise and rich reference MSC ontology could address both of these limitations. Based on our prior research, the development of such an ontology will require a semantic mediation process between the proprietary MSC models and the reference MSC ontology. At the heart of every known, semantic-mediation process is a mapping between a proprietary MSC model and the reference MSC ontology. Such a mapping must deal with the structural and semantic conflicts between the two. In this paper, we propose a new approach, which we call canonicalization to address the structural conflicts. The semantic conflicts are addressed using logical mapping. The canonicalization pre-processes the structural representations of the proprietary models and then aligns them using ontology design patterns which are also used in the reference ontology. This simplifies both the mapping problems themselves and the resulting mapping statements considerably. In the paper, we also demonstrate our approach and its benefits in the context of a description-logic-based semantic mediation using the Ontology Web Language (OWL).