Semantic Browsing Research Articles

Pengembangan Sistem Informasi Banten Menggunakan Web Semantik

The culture of Bali is strongly impacted by Hindu traditions and culture, as evidenced by the numerous yadnya ceremonies that Balinese people perform. Bali is one of the Indonesian islands with a diverse range of civilizations. Banten, also known as upakara, is a strategy for aiding in the execution of a ritual in Bali. However, a current problem is that many Balinese people only have a basic understanding of this cultural legacy and are only able to recognize it. As a result, a Banten information system was created for this project, and it was based on an ontology and prototyped utilizing the prototyping approach. The Methodology technique is employed in the construction of the ontology model. The system that was created has both semantic browsing and semantic searching capabilities. Black-Box Testing was used to test the system's accuracy and operation. The system functions well as a result of the outcomes.

A NONLINEAR MODEL FOR A SMART SEMANTIC BROWSER BOT FOR A TEXT ATTRIBUTE RECOGNITION

In spite of the advances in the state of the art in semantic artificial intelligence applications, there is still a long way to go to bring it to a level of mass adoption. Thus, in order to contribute to the advancement of this topic, this study develops a feasible model with a potential scalability for semantic applications’ mass adoption, specifically for news or statement cluster attribute identification, either positive, negative or neutral. This paper proposes a disruptive system based on Blockchain using a Semantic Browser Expert System Bot with artificial intelligence called Blockchain Semantic Browser Expert System (BSBES) to look for and analyze relevant information that significantly represents the cryptocurrencies adoption patterns. The artificial intelligence in this study consists of a deep learning neural network to process the input information to identify the news pattern in a semantic way using deep learning based on two aspects of the news: technical aspect and adoption aspect of the cryptocurrencies. BSBES performance is achieved based on deep learning tools, and scalability is supported by a blockchain system including a stability study.

User-centered design and evaluation of overview components for semantic data exploration

Purpose – The growing volumes of semantic data available in the web result in the need for handling the information overload phenomenon. The potential of this amount of data is enormous but in most cases it is very difficult for users to visualize, explore and use this data, especially for lay-users without experience with Semantic Web technologies. The paper aims to discuss these issues. Design/methodology/approach – The Visual Information-Seeking Mantra “Overview first, zoom and filter, then details-on-demand” proposed by Shneiderman describes how data should be presented in different stages to achieve an effective exploration. The overview is the first user task when dealing with a data set. The objective is that the user is capable of getting an idea about the overall structure of the data set. Different information architecture (IA) components supporting the overview tasks have been developed, so they are automatically generated from semantic data, and evaluated with end-users. Findings – The chosen IA components are well known to web users, as they are present in most web pages: navigation bars, site maps and site indexes. The authors complement them with Treemaps, a visualization technique for displaying hierarchical data. These components have been developed following an iterative User-Centered Design methodology. Evaluations with end-users have shown that they get easily used to them despite the fact that they are generated automatically from structured data, without requiring knowledge about the underlying semantic technologies, and that the different overview components complement each other as they focus on different information search needs. Originality/value – Obtaining semantic data sets overviews cannot be easily done with the current semantic web browsers. Overviews become difficult to achieve with large heterogeneous data sets, which is typical in the Semantic Web, because traditional IA techniques do not easily scale to large data sets. There is little or no support to obtain overview information quickly and easily at the beginning of the exploration of a new data set. This can be a serious limitation when exploring a data set for the first time, especially for lay-users. The proposal is to reuse and adapt existing IA components to provide this overview to users and show that they can be generated automatically from the thesaurus and ontologies that structure semantic data while providing a comparable user experience to traditional web sites.

An Educational Tool for Browsing the Semantic Web

The Semantic Web is an extension of the current Web where information is represented in a machine processable way. It is not separate from the current Web and one of the confusions that novice users might have is where the Semantic Web is. In fact, users can easily encounter RDF documents that are components of the Semantic Web while they navigate among Web pages. In addition, the number of RDF documents on the Web is ever-increasing and a lot of educational materials in RDF format become available on the Web. In this paper, we propose a simple Semantic Web browser by which non-expert users such as secondary school students who do not know technical details about the Semantic Web can browse through HTML documents and RDF documents.

Dynamic Linking and Personalization on the Web using Linked Open Data

This paper presents a novel Semantic Web browser, called SemWeB. SemWeB supports Web browsing using Linked Open Data and personalization. This is the first time a Semantic Web browser combines the advances in Adaptive Hypermedia (i.e. personalization) and Linked Open Data. In particular, users are provided with a personalized and semantically rich Web browsing experience. For example, SemWeB supplies goal-based adaptive information retrieval from the LOD, adaptive link recommendation using a novel semantic relatedness measure and adaptive content creation. A user based study was used to assess the value of LOD-based hyperlinks and personally relevant content compared with a standard Web browser (Firefox). Results showed that users were able to browse and view more relevant information, as well as, value significance of LOD-based hyperlinks and personalized content in comparison to a standard Web browser.

From Overview to Facets and Pivoting for Interactive Exploration of Semantic Web Data

The proliferation of Linked Open Data on the Web has increased the amount of data available for analysis and reuse. However, casual users find it difficult to explore and use Semantic Web Data due to the prevalence of specialised browsers that require complex queries to be formed and intimate knowledge on the structure of datasets. The authors address this problem in the Rhizomer tool by applying the data analysis mantra of overview, zoom and filter. These interaction patterns are implemented using information architecture components users are already familiar with but that are automatically generated from data and ontologies. This approach makes it possible to obtain an overview of the dataset being explored using techniques, such as navigation menus, treemaps or sitemaps, which are usually not available in text-based semantic web browsers. From there, users can interactively explore the data using facets. Moreover, facets also feature a pivoting operation, motivated during tests with lay users, that removes the main constraint of most faceted browsers, i.e. the inability to combine filters for differently faceted views to build complex queries.

Ontological model of legal norms for creating and using legislation

This paper presents a formal model of legal norms modeled in OWL. It is intended for semiautomatic drafting and semantic retrieval and browsing of legislation. Most existing solutions model legal norms by formal logic, rules or ontologies. Nevertheless, they were not in-tended as a basis for drafting, retrieval and browsing of legislation. The proposed model formally defines legal norms using their elements and elements of legal relations they regulate. The duality between the con-tent and the form of legislation is exploited by connecting it to the XML model of legislation based on the CEN MetaLex specification. Those models are verified by applying them to the norms contained in an existing piece of legislation and by developing a prototype application for semantic browsing of legislation that is based on the models.

Publishing Knowledge and Transformation of Conventional Web into Semantic Web using Metadata

In Semantic Web research, most of the work has focused around the OWL ontology, natural language processing, word sense disambiguation and semantic matching. Few efforts have been made to provide a publishing methodology for metadata-rich Web content for end users. This work encompasses all possible aspects of publishing pure digital content, such as HTML documents, images, video, and other media documents free from metadata. Afterwards the content could be integrated with metadata to provide optimal capability and scalability for document organization, search and navigation in the aim of explicit knowledge publishing. The effort is made on our specific framework to publish documents which are enriched with metadata for better machine reasoning. The first and the second version of the prototype is a Mozilla Firefox extension called Semantic Web (SWeb) browser. SWeb is intended for managing and publishing knowledge and information, as “publishing knowledge” was missing in the system where we got the opportunity to contribute.

A novel semantic web browser for user centric information retrieval: PERSON

As semantic web technologies mature and consequently more semantic web data is published on the web, there is a growing need for tools to access and use this data in user friendly ways. The most generic tool to access semantic web data is the common web browser. Developing plug-ins for advanced web browsers is one way of adding semantic information to web documents automatically or semi-automatically. To enable this enhancement, we present a novel semantic web browser called PERSON which is short for PERsonal Semantic extensiON. PERSON is an extension for Mozilla Firefox Web Browser and it adds semantics to users’ browsing experience by annotating web resources, associating them in categorical, entity-based manner and presenting more meaningful, structured documents to users. As a notable difference, semantic layer provided by PERSON works not only on web pages navigated by users but also on RSS data of user choice. Additionally, acquired content from web resources associated with linked data domains bring users together with structured information easily. In this paper, we evaluate PERSON as a new approach for semantic web browsing and present the analysis, design and implementation of PERSON and compare its features with related tools.

Towards linked open gene mutations data

BackgroundWith the advent of high-throughput technologies, a great wealth of variation data is being produced. Such information may constitute the basis for correlation analyses between genotypes and phenotypes and, in the future, for personalized medicine. Several databases on gene variation exist, but this kind of information is still scarce in the Semantic Web framework.In this paper, we discuss issues related to the integration of mutation data in the Linked Open Data infrastructure, part of the Semantic Web framework. We present the development of a mapping from the IARC TP53 Mutation database to RDF and the implementation of servers publishing this data.MethodsA version of the IARC TP53 Mutation database implemented in a relational database was used as first test set. Automatic mappings to RDF were first created by using D2RQ and later manually refined by introducing concepts and properties from domain vocabularies and ontologies, as well as links to Linked Open Data implementations of various systems of biomedical interest.Since D2RQ query performances are lower than those that can be achieved by using an RDF archive, generated data was also loaded into a dedicated system based on tools from the Jena software suite.ResultsWe have implemented a D2RQ Server for TP53 mutation data, providing data on a subset of the IARC database, including gene variations, somatic mutations, and bibliographic references. The server allows to browse the RDF graph by using links both between classes and to external systems. An alternative interface offers improved performances for SPARQL queries. The resulting data can be explored by using any Semantic Web browser or application.ConclusionsThis has been the first case of a mutation database exposed as Linked Data. A revised version of our prototype, including further concepts and IARC TP53 Mutation database data sets, is under development.The publication of variation information as Linked Data opens new perspectives: the exploitation of SPARQL searches on mutation data and other biological databases may support data retrieval which is presently not possible. Moreover, reasoning on integrated variation data may support discoveries towards personalized medicine.

Collaborative browsing system based on semantic mashup with open APIs

Due to a large amount of information available on world wide web, it has been difficult for users to effectively find relevant information. Many web browsing methods and systems have been investigated to apply adaptive approaches which can extract personal interests of the users. In this paper, we propose a semantic mashup-based collaborative browsing (co-browsing) platform for supporting knowledge sharing with other partners. Especially, the semantic mashup scheme can integrate heterogeneous information collected by various Open APIs, and help users to determine which partners should be selected. For evaluating the proposed method, we have implemented a co-browsing platform which can exchange bookmarks, and measured whether the semantic mashup scheme make a positive influence on improving the performance of the co-browsing process.

Beyond Findability – Search-Enhanced Information Architecture for Content-Intensive Rich Internet Applications

This paper details a way to extend classic information architecture for web-based applications. The goal is to enhance traditional user experiences, mainly based on navigation or search, to new ones (also relevant for stakeholders’ requirements). Examples are sense making, at a glance understanding, playful exploration, serendipitous browsing, and brand communication. These new experiences are often unmet by current information architecture solutions, which may be stiff and difficult to scale, especially in the case of large or very large websites. A heavy reliance upon search engines seems not to offer a viable solution: it supports, in fact, a limited range of user experiences. We propose to transform (parts of) websites into Rich Internet Applications (RIAs), based, beside other features, upon interaction-rich interfaces and semantic browsing across content. We introduce SEE-IA (SEarch-Enhanced Information Architecture), a coherent set of information architecture design strategies, which innovatively blend and extend IA and search paradigms. The key ingredients of SEE-IA are a seamless combination of structured hypertext-based information architectures, faceted search paradigms, and RIA-enabled visualization techniques. The paper elucidates and codifies these design strategies and their underlying principles, identifying also how they support a set of requirements which are often neglected by most current design approaches. A real case study of a complex RIA designed for a major institutional client in Italy is used to vividly showcase the design strategies and to provide ready-to-use examples that can be transferred to other IA contexts and domains

Beyond Findability: Search-Enhanced Information Architecture for Content-Intensive Rich Internet Applications

This paper details a way to extend classic information architecture for web-based applications. The goal is to enhance traditional user experiences, mainly based on navigation or search, to new ones (also relevant for stakeholders’ requirements). Examples are sense making, at a glance understanding, playful exploration, serendipitous browsing, and brand communication. These new experiences are often unmet by current information architecture solutions, which may be stiff and difficult to scale, especially in the case of large or very large websites. A heavy reliance upon search engines seems not to offer a viable solution: it supports, in fact, a limited range of user experiences. We propose to transform (parts of) websites into Rich Internet Applications (RIAs), based, beside other features, upon interaction-rich interfaces and semantic browsing across content

A user-centred evaluation framework for the Sealife semantic web browsers.

BackgroundSemantically-enriched browsing has enhanced the browsing experience by providing contextualised dynamically generated Web content, and quicker access to searched-for information. However, adoption of Semantic Web technologies is limited and user perception from the non-IT domain sceptical. Furthermore, little attention has been given to evaluating semantic browsers with real users to demonstrate the enhancements and obtain valuable feedback. The Sealife project investigates semantic browsing and its application to the life science domain. Sealife's main objective is to develop the notion of context-based information integration by extending three existing Semantic Web browsers (SWBs) to link the existing Web to the eScience infrastructure.MethodsThis paper describes a user-centred evaluation framework that was developed to evaluate the Sealife SWBs that elicited feedback on users' perceptions on ease of use and information findability. Three sources of data: i) web server logs; ii) user questionnaires; and iii) semi-structured interviews were analysed and comparisons made between each browser and a control system.ResultsIt was found that the evaluation framework used successfully elicited users' perceptions of the three distinct SWBs. The results indicate that the browser with the most mature and polished interface was rated higher for usability, and semantic links were used by the users of all three browsers.ConclusionConfirmation or contradiction of our original hypotheses with relation to SWBs is detailed along with observations of implementation issues.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2105-10-S10-S14) contains supplementary material, which is available to authorized users.

UML for the conceptual web

PurposeThe purpose of this paper is to propose the use of unified modelling language (UML) based ontologies to develop a faceted model to facilitate semantic browsing and searching in digital libraries.Design/methodology/approachThe approach is to understand the way information gets logically organised in the human mind in terms of mutually defined concepts. Ontologies will be used to model the semantic structure of individual information sources using the faceted classification schema of Dr S.R. Ranganathan, though with improvisation to accommodate new concepts relating to digital resources.FindingsUML can be the best option for knowledge representation if the target system is a digital library where the required type of reasoning about ontologies is more in terms of answering specific and specialised questions. Here, ontologies can be used to facilitate a distributed information retrieval system.Originality/valueThe proposed model will not only facilitate semantic searching using UML concept maps but will also enable domain experts, even those with little coding expertise, to build ontologies for their resources while submitting their documents to the digital library.

Building rich, semantic descriptions of learning activities to facilitate reuse in digital libraries

This paper describes efforts to extend educational descriptions of learning objects to enable semantic search for suitable resources held within digital libraries and cyberinfrastructure, and describes some further advantages that accrue from the use of formal description languages (ontologies) to describe both pedagogy and domain content. These advantages include: semantic browsing and visualization of learning object contents, advanced search capabilities linking to several different online collections, easy extension of learning objects with external content added by learners and educators, and utilization of the many rich models of education and educational domains now available as ontologies. As well as conceptual justifications and descriptions of our work, we provide examples throughout to concretize the ideas presented, using learning objects developed for college-level education in geography and the geosciences. We conclude with some thoughts on the further possibilities that arise from the application of detailed semantics, and associated reasoning, in the pursuit of genuinely reusable educational content that integrates more closely with community research activities such as exemplified by e-science.

Building a user-centered semantic hierarchy in image databases

Recent development in the field of digital media technology has resulted in the generation of a huge number of images. Consequently, content-based image retrieval has emerged as an important area in multimedia computing. Research in human perception of image content suggests that the semantic cues play an important role in image retrieval. In this paper, we present a new paradigm to establish the semantics in image databases based on multi-user relevance feedback. Relevance feedback mechanism is one way to incorporate the users' perception during image retrieval. By treating each feedback as a weak classifier and combining them together, we are able to capture the categories in the users' mind and build a user-centered semantic hierarchy in the database to support semantic browsing and searching. We present an image retrieval system based on a city-landscape image database comprising of 3,009 images. We also compare our approach with other typical methods to organize an image database. Superior results have been achieved by the proposed framework.

DartGrid: a semantic infrastructure for building database Grid applications

AbstractIn the presence of a Database Grid where a huge number of highly diverse, widely distributed, autonomously managed databases can be involved in a sharing cycle, database tools and middleware should be well suited for schema mediation and query processing in a semantically meaningful way. In this paper, an implemented system called DartGrid is presented. DartGrid is intended to provide a semantic infrastructure for building database grid applications. We explore the essential and fundamental roles played by Resource Description Framework (RDF) semantics for database grids and implement a set of semantically enabled tools and grid services such as semantic browser, semantic mapping tools, ontology service, semantic query service and semantic registration service. We propose an RDF‐View‐based approach for relational schema mediation and describe the view‐based semantic query rewriting algorithm implemented in DartGrid. DartGrid has been used to build a real database grid application for Traditional Chinese Medicine in China. Copyright © 2006 John Wiley & Sons, Ltd.

MizarMode—an integrated proof assistance tool for the Mizar way of formalizing mathematics

The Emacs authoring environment for Mizar (MizarMode) is today the authoring tool of choice for many (probably the majority of) Mizar authors. This article describes the MizarMode and focuses on the proof assistance functions and tools available in it. We start with the explanation of the design principles behind the Mizar system, and show how these design principles—mainly the concentration on simple and intuitive human-oriented proofs—have helped Mizar in developing and maintaining a very large body of formalized mathematics. Mizar is a non-programmable and non-tactical verifier: the proofs are developed in the traditional “write—compile—correct” software programming loop. While this method is in the beginning more laborious than the methods employed in tactical and programmable proof assistants, it makes the “proof code” in the long-run more readable, maintainable and reusable. This seems to be a crucial factor for a long-term and large-scale formalization effort. MizarMode has been designed with the aim to facilitate this kind of proof development by a number of “code-generating”, “code-browsing” and “code-searching” methods, and tools programmed or integrated within it. These methods and tools now include, e.g., the automated generation of proof skeletons, semantic browsing of the articles and abstracts, structured viewing, proof advice using trained machine learning tools like the Mizar Proof Advisor, deductive tools like MoMM, etc. We give an overview of these proof-assistance tools and their integration in the MizarMode, and also discuss some emerging and future extensions such as integration of external theorem proving assistance.

An ontology and context based client model for dart information grid

The WWW is growing at an astounding rate and various autonomous organisations have disseminated heterogeneous information resources in an 'out of order' state, across the web. It is expected to have the ability of integrating and sharing largescale information resources in dynamic virtual organisations. Integrating semantics with context theory, we propose an 'ontology based context role' model (OCR Model) for constructing intelligent clients to information grids. We implement the OCR Model as a semantic browser, which is a novel client for DartGrid and aims at providing end users with an intelligent graphical interface for accessing information effectively in the Grid environment. The semantic browser has been applied in the field of Traditional Chinese Medicine (TCM) to resolve some practical problems.