Abstract: This study explores a method for managing web content based on intelligent technologies, as a stage of the content life cycle in e-commerce systems. The method of content management describes the processes of creating web resources and simplifies the technology of managing web resources in conditions of uncertainty. Also, the main problems of e-commerce and functional content processing services are analyzed. The proposed method makes it possible to develop tools for managing web resources and commercial content.

Abstract: The main objective of this work was the development of the information system for support of pharmacy customers. This system provides information about required medicines and their analogues, medicine availability and prices. The main functions of the system and detailed workflow diagrams are described. The developed consolidated information resource allows to find the right medicine, sort pharmacies according to medicine location and price, give the necessary information about pharmacies and medicines, search for alternative medicines with the same chemical agent, view usage instructions for selected medications without internet connection.

Abstract: Recognition of information from web pages is an important task for tourism activity support. This article dwells upon procedures for recognition of tourism documentation fragments from web pages of open web resources. These procedures are based on the methods of decomposition and synthesis of the sets of thematic syntactic structures of web page posts. Semantic structures are separate sentences or tagged text fragments. This is feature of the developed approach to the identification of useful tourism information from web pages.

Abstract: Knowledge Base Commons (KBCommons) v1.0 provides a comprehensive web resource for storing, sharing, analyzing, exploring, and visualizing multi-organism genomics and multi-omics data. KBCommons is designed for integrating diverse multi-level omics data and facilitating biological discoveries. It provides a one-stop shop framework for creating a new organism-specific or disease-specific knowledge base (KB), adding more omics data and genome versions to existing KBs and exploring genomic data within current KBs. It has a secure data privilege management system to enable users to make their data publicly available or to share with certain groups and members. It also provides a suite of interactive web-based tools for bioinformatics analysis and data visualization. KBCommons has a user-friendly web interface, which allows users to retrieve entire genomic data, as well as any experiment data or analysis results easily. KBCommons can be publicly accessed at http://kbcommons.org/.

Abstract: Open access article. Creative Commons Attribution-NonCommercial 4.0 International LIcense (CC BY-NC 4.0) applies

Abstract: The demand for qualified teachers with sufficient pedagogical knowledge and skills is high. However, existing teacher education programs do not provide adequate experiences through which to develop pre-service teachers’ professional foundations. This study recognized Open Educational Resources (OER) as a means by which to address the issue of enhancing teacher education. The purpose of this study was to propose a framework to be used to integrate OER into lesson design activities for pre-service teachers. In this study, a focused literature review investigated the frameworks of distributed cognition and example-based learning. This review process resulted in a unified framework that provides a description of how pre-service teachers learn with OER at both the individual and cognitive system levels. Four principles and 10 guidelines are provided to guide the implementation of OER-based lesson design activities in real settings. The new framework has the potential to enhance pre-service teachers’ Web resource-based professional development.

Abstract: Mobile apps have become the main channel for accessing Web services. Both Android and iOS feature inapp Web browsers that support convenient Web service integration through a set of Web resource manipulation APIs. Previous work have revealed the attack surfaces of Web resource manipulation APIs and proposed several defense mechanisms. However, none of them provides evidence that such attacks indeed happen in the real world, measures their impacts, and evaluates the proposed defensive techniques against real attacks. This paper seeks to bridge this gap with a large-scale empirical study on Web resource manipulation behaviors in real-world Android apps. To this end, we first define the problem as cross-principal manipulation (XPM) of Web resources, and then design an automated tool named XPMChecker to detect XPM behaviors in apps. Through a study on 80,694 apps from Google Play, we find that 49.2% of manipulation cases are XPM, 4.8% of the apps have XPM behaviors, and more than 70% XPM behaviors aim at top Web sites. More alarmingly, we discover 21 apps with obvious malicious intents, such as stealing and abusing cookies, collecting user credentials and impersonating legitimate parties. For the first time, we show the presence of XPM threats in real-world apps. We also confirm the existence of such threats in iOS apps. Our experiments show that popular Web service providers are largely unaware of such threats. Our measurement results contribute to better understanding of such threats and the development of more effective and usable countermeasures.

Abstract: Information retrieval is the process of satisfying user information needs that are expressed as textual queries. Search engines represent a Web-specific example of the information retrieval paradigm. The problem of Web search has many additional challenges, such as the collection of Web resources, the organization of these resources, and the use of hyperlinks to aid the search. Whereas traditional information retrieval only uses the content of documents to retrieve results of queries, the Web requires stronger mechanisms for quality control because of its open nature. Furthermore, Web documents contain significant meta-information and zoned text, such as title, author, or anchor text, which can be leveraged to improve retrieval accuracy.

Abstract: With the evolution of mobile devices and app eco system, all major content providers develop services in native apps and web-apps Web-apps have an inherent advantage of platform independent and uniform experience across devices, but the page load time, battery usage, and bandwidth consumption have to be improved To solve some of these issues, there has been an introduction of Progressive Web Apps (PWA) by content providers PWA apps use an effective caching policy on web resources based on its property But the webpages are overwhelmingly non-PWA compliant There is a need for non-PWA web pages to be effective in bandwidth utilization so that we can avoid the exchange of needless resources This paper proposes a new method to inject a service worker into a webpage at Proxy Servers This service worker is packaged along with non-PWA webpage as a response to web browser requests The web engine then runs the service worker to identify stale web resources which in turn will be helpful to avoid transfer of redundant web resources The proposed approach was evaluated using top 25 Non-PWA sites from Alexa 100 websites for one month It saved an average of 25% data traffic and also provided an offline experience of these websites This proposal can be further extended to create a generalized framework for seamlessly converting Non-PWA apps to PWA apps

Abstract: Summary Clustering is one of the most common techniques used in data analysis to discover hidden structures by grouping together data points that are similar in some measure into clusters. Although there are many programs available for performing clustering, a single web resource that provides both state-of-the-art clustering methods and interactive visualizations is lacking. ClusterEnG (acronym for Clustering Engine for Genomics) provides an interface for clustering big data and interactive visualizations including 3D views, cluster selection and zoom features. ClusterEnG also aims at educating the user about the similarities and differences between various clustering algorithms and provides clustering tutorials that demonstrate potential pitfalls of each algorithm. The web resource will be particularly useful to scientists who are not conversant with computing but want to understand the structure of their data in an intuitive manner. Availability ClusterEnG is part of a bigger project called KnowEnG (Knowledge Engine for Genomics) and is available at http://education.knoweng.org/clustereng. Contact songi@illinois.edu.

Abstract: Navigating through the web of uncertain data has become increasingly difficult. Unfortunately, the old techniques used in the classical web can not handle the navigation of uncertain web data or resources. Uncertain data published on the web can be heterogeneous, conflicting, inconsistent or in incompatible formats. This uncertainty is inherently related to many factors such as information extraction and data integration. In order to give the web user the best experience and provide him with the most relevant answer we have to consider the uncertainty of web data and model it. In this paper, we propose a probabilistic approach to model and interpret uncertain web resources. We present operators to compute the uncertainty for the response. Finally, we propose algorithms in order to validate resources and to achieve the uncertain navigation.

Abstract: . Large amounts of spatial data are hold in relational databases. Spatial data in the relational databases must be converted to RDF for semantic web applications. Spatial data is an important key factor for creating spatial RDF data. Linked Data is the most preferred way by users to publish and share data in the relational databases on the Web. In order to define the semantics of the data, links are provided to vocabularies (ontologies or other external web resources) that are common conceptualizations for a domain. Linking data of resource vocabulary with globally published concepts of domain resources combines different data sources and datasets, makes data more understandable, discoverable and usable, improves data interoperability and integration, provides automatic reasoning and prevents data duplication. The need to convert relational data to RDF is coming in sight due to semantic expressiveness of Semantic Web Technologies. One of the important key factors of Semantic Web is ontologies. Ontology means “explicit specification of a conceptualization”. The semantics of spatial data relies on ontologies. Linking of spatial data from relational databases to the web data sources is not an easy task for sharing machine-readable interlinked data on the Web. Tim Berners-Lee, the inventor of the World Wide Web and the advocate of Semantic Web and Linked Data, layed down the Linked Data design principles. Based on these rules, firstly, spatial data in the relational databases must be converted to RDF with the use of supporting tools. Secondly, spatial RDF data must be linked to upper level-domain ontologies and related web data sources. Thirdly, external data sources (ontologies and web data sources) must be determined and spatial RDF data must be linked related data sources. Finally, spatial linked data must be published on the web. The main contribution of this study is to determine requirements for finding RDF links and put forward the deficiencies for creating or publishing linked spatial data. To achieve this objective, this study researches existing approaches, conversion tools and web data sources for relational data conversion to the spatial RDF. In this paper, we have investigated current state of spatial RDF data, standards, open source platforms (particularly D2RQ, Geometry2RDF, TripleGeo, GeoTriples, Ontop, etc.) and the Web Data Sources. Moreover, the process of spatial data conversion to the RDF and how to link it to the web data sources is described. The implementation of linking spatial RDF data to the web data sources is demonstrated with an example use case. Road data has been linked to the one of the related popular web data sources, DBPedia. SILK, a tool for discovering relationships between data items within different Linked Data sources, is used as a link discovery framework. Also, we evaluated other link discovery tools e.g. LIMES, Silk and results are compared to carry out matching/linking task. As a result, linked road data is shared and represented as an information resource on the web and enriched with definitions of related different resources. By this way, road datasets are also linked by the related classes, individuals, spatial relations and properties they cover such as, construction date, road length, coordinates, etc.

Abstract: This paper considers the potential of web-analytic tools for a detailed study of the main fields of work of libraries in the web environment, study of user behavior, and analysis of the relevance of library information products and services offered on the sites. It presents the parameters for assessing the audience of library web resources (attendance, traffic sources, geography of users, etc.) using plug-ins, log-analyzers, counters, ratings, and services (Google Analytics, Yandex.Metrics, and Hotlog). The sites of several world libraries are analyzed by marketing tools (Hubspot Website Grader, Nibbler, CheckTrust, Google page-speed insights, and Hemingway).

Abstract: Web resources change over time and many ultimately disappear. While this has become an inconvenient reality in day-to-day use of the web, it is problematic when these resources are referenced in scholarship where it is expected that referenced materials can reliably be revisited. We introduce Robust Links, an approach aimed at maintaining the integrity of the scholarly record in a dynamic web environment. The approach consists of archiving web resources when referencing them and decorating links to convey information that supports accessing referenced resources both on the live web and in web archives.

Abstract: The continuous growth in the size and use of the Internet is increasing the difficulties in searching for information. Reductions on the Internet traffic load and user access cost is therefore particular important. Clustering is an important part of web mining that involves finding natural groupings of web resources or web users. Researchers have pointed out some important differences between clustering in conventional applications and clustering in web mining. Web clustering as an important web usage mining (WUM) task groups web users based on their browsing patterns to ensure the provision of a useful knowledge of personalized web services. Based on the web structure, each Uniform Resource Locator (URL) in the web log data is parsed into tokens which are uniquely identified for URLs classification. The collective sequence of URLs a user navigated over a period of 30 minutes is considered as a session and the session is a representation of the users' navigation pattern. This paper proposes a variation of the K-means clustering algorithm based on properties of rough sets. The proposed algorithm represents the clustering of the web users based on their browsing activities or patterns on the web. Specifically, a user may visit a website often and spends much time on each visit. users with similar browsing activities are clustered or grouped in to clusters. The paper also describes the design of an experiment including data collection and the clustering process.

Abstract: Introduction. High subscription fees to scholarly research journals provoke researchers to use illegal channels of access to scientific information. Analysis of statistical data on downloads of scholarly research papers by Ukrainian Internet users from illegal web resource can help to define gaps in information provision at the institutional or the state level for each scientific field. Problem Statement. To conduct an analysis of behavior and geography of downloads of scholarly research publications from illegal web resource Sci-Hub by Ukrainian Internet users within the period from September 1, 2015 to February 29, 2016. Purpose. To assess the information needs of Ukrainian researchers who download scientific papers from Sci-Hub. Materials and Methods. The used file is available at public domain and contains complete data of downloads of scholarly research articles from Sci-Hub for the period from September 1, 2015 to February 29, 2016. Inquiries of users with Ukrainian IP-addresses have been selected. Using DOI of downloaded articles enables finding the publishers and journal brands with the help of CrossRef API, whereas using the All Science Journal Classification (ASJC) codes makes it possible to identify the subject. Results. The study has shown that the most documents downloaded related to natural sciences (primarily, chemistry, physics, and astronomy), with Elsevier publications being the most frequently inquired by Ukrainian users of Sci-Hub and Internet users from Kyiv downloading the papers most actively. Conclusion. The obtained data are important for understanding the information needs of Ukrainian researchers and can be used to formulate an optimal subscription policy for providing access to information resources at Ukrainian R&D institutions.

Abstract: Every day, practitioners, researchers, and students consult the Web to meet their information needs about GIS concepts and tools. How do we improve GIS in terms of conceptual organisation, findability, interoperability and relevance for user needs? So far, efforts have been mainly top-down, overlooking the actual usage of software and tools. In this article, we critically explore the potential of Web science to gain knowledge about tool usage and public interest in GIScience concepts. First, we analyse behavioural data from Google Trends, showing clear patterns in searches for GIS software. Second, we analyse the visits to GIScience-related websites, highlighting the continued dominance of ESRI, but also the rapid emergence of Web-based new tools and services. We then study the views of Wikipedia articles to enable the quantification of methods and tools’ popularity. Fourth, we deploy web crawling and network analysis on the ArcGIS documentation to observe the relevance and conceptual associations among tools. Finally, in order to facilitate the study of GIS usage across the Web, we propose a linked-data inventory to identify Web resources related to GI concepts, methods, and tools. This inventory will also enable researchers, practitioners, and students to find what methods are available across software packages, and where to get information about them.

Abstract: Nowadays, with the emergence of new web technologies, no one could deny the necessity of including such external data sources in the analysis process in order to provide the necessary knowledge for companies to improve their services and increase their profits. However, processing data in an open environment such as the web has become too difficult due to the diversity of distributed data sources and incapability of machines to 'understand' the real semantic of web resources. The Semantic Web (SW) provides the semantic annotations to describe and link scattered information over the web and facilitate inference mechanisms using ontologies. Web Ontology Language (OWL) is the W3C recommendation. A Data warehouse (DW) is used in decision making processes to store multidimensional (MD) information from heterogeneous data sources using ETL (Extract, Transform and Load) techniques. In this paper, we introduce firstly a simplification method of OWL inputs and then we define the related MD schema. Transformation rules are applied for defining multidimensional concepts over the OWL graph.

Abstract: The major evolution of the semantic web has become exchanging data between applications in all domains of activities. Based on this vision, different applications in recent days, e.g. in the fields of community web portals, social networking, e-learning, multimedia retrieval, etc. have been designed. Due to growing number of web services, clustering of web resources becomes a valuable tool for semantic web mining. Clustering of internet objects like Internet web pages’ intimate new methods for grouping correlated content for better understanding and satisfies massive user query results in web pages’ search. Hence, web pages clustering algorithms should be able to handle massive irregular content and discover knowledge regardless of the web page complexity. These algorithms vary depending on the characteristics and data types. So, choosing the most appropriate algorithm is not an easy process as it should be accurate in terms of time and space complexity. Therefore, this paper rigorously surveys the most important algorithms of different types used for web page clustering. In addition, a comparative analysis of all such algorithms are provided in terms of several parameters. Finally, a brief discussion is provided on why web page clustering isimportant in emerging era of Semantic Web of Thing (SWoT) applications.

Abstract: This paper reviews the use of computer ontologies for Internet data linking and knowledge representation. We discuss a trend in organizing ontology libraries and servers for the joint development of ontologies and their application. Ontology libraries are regarded as public Web resources. We pay special attention to the design of ontology libraries, their debugging, and directions for their development.

Abstract: Introduction. High subscription fees to scholarly research journals provoke researchers to use illegal channels of access to scientific information. Analysis of statistical data on downloads of scholarly research papers by Ukrainian Internet users from illegal web resource can help to define gaps in information provision at the institutional or the state level for each scientific field. Problem Statement. To conduct an analysis of behavior and geography of downloads of scholarly research publications from illegal web resource Sci-Hub by Ukrainian Internet users within the period from September 1, 2015 to February 29, 2016. Purpose. To assess the information needs of Ukrainian researchers who download scientific papers from Sci-Hub. Materials and Methods. The used file is available at public domain and contains complete data of downloads of scholarly research articles from Sci-Hub for the period from September 1, 2015 to February 29, 2016. Inquiries of users with Ukrainian IP-addresses have been selected. Using DOI of downloaded articles enables finding the publishers and journal brands with the help of CrossRef API, whereas using the All Science Journal Classification (ASJC) codes makes it possible to identify the subject. Results. The study has shown that the most documents downloaded related to natural sciences (primarily, chemistry, physics, and astronomy), with Elsevier publications being the most frequently inquired by Ukrainian users of Sci-Hub and Internet users from Kyiv downloading the papers most actively. Conclusion. The obtained data are important for understanding the information needs of Ukrainian researchers and can be used to formulate an optimal subscription policy for providing access to information resources at Ukrainian R&D institutions.

Abstract: In social bookmarking websites, social tags contain rich information about individual preference in web resources. Nevertheless, the unsupervised way of tag creation makes the expressions of user's interests are troubled by tag semantic gap. Additionally, in social network sites, the user's interests are influenced by his/her friends' preferences. To handle the problem of personalised interest expression and to recommend the relevant web resource for the users, we propose a tag-based recommender system framework for social bookmarking websites, in which user, tag and resource profiles are expressed reciprocally in a unified form and the 'following interest' is defined based on social network analysis for computing the influence of social relationship on individual interests. We compare our method with several collaborative filtering-based recommendation methods using datasets collected from two social bookmarking websites. The results show that it improves the performance of resource recommendation and outperforms the baseline methods.

Abstract: Context. A large number of web resources of different organizations requires checking of relevance and correctness of the content, in particular, concerning characteristics of the organization, staff, etc. For this, it is necessary to develop a system of the automated content analysis. This task causes the need to develop a method and software for structuring and recognizing of web resources content. Existing parsing systems do not provide solving of the specified task, since they do not contain elements of machine learning. The object of the research is the process of automated analysis of the web resources content. Objective. The goal of the work is the creation of the system for web resources content structuring and recognizing. Method. The system of structuring and recognizing of text content of web resources with elements of machine learning is considered. Models of the system functioning are proposed. The architecture for realizing of software system for structuring and recognizing of text content of web resources is developed. Example of implementation of the model of developed system for structuring, recognizing and revealing of outdated and incorrect information about personnel on the web resource of educational institution is given. Results. The developed software may be used by support services in order to update and correct the information content. Conclusions. The system of structuring and recognizing of content of web resources with the machine learning elements has been considered. The proposed system compared with the known ones, ensures automated content structuring, recognizing of outdated, non-relevant or wrong information. Represented example of the structuring and recognizing of outdated and incorrect information on the website of educational institution confirms the effectiveness of the proposed system.

Abstract: The increasing availability of multi-omic platforms poses new challenges to data analysis. Joint visualization of multi-omics data is instrumental to understand interconnections across molecular layers and to fully leverage the biology discovery power offered by the multi-omics approach. We present here PaintOmics 3, a web-based resource for the integrated visualization of multiple omic data types onto KEGG pathway diagrams. PaintOmics 3 combines server-end capabilities for data analysis with the potential of modern web resources for data visualization, providing researchers with a powerful framework for interactive exploration of their multi-omics information. Unlike other visualization tools, PaintOmics 3 covers a complete pathway analysis workflow, including automatic feature name/identifier conversion, multi-layered feature matching, pathway enrichment, network analysis, interactive heatmaps, trend charts, etc. It accepts a wide variety of omic types, including transcriptomics, proteomics and metabolomics, as well as region-based approaches such as ATAC-seq or ChIP-seq data. The tool is freely available at http://bioinfo.cipf.es/paintomics/.

Abstract: JavaScript Object Notation, JSON (RFC 8259) is a text-based data format which is popular for Web based data exchange. Concise Binary Object Representation, CBOR (RFC7049) is a binary data format which has been optimized for data exchange for the Internet of Things (IoT). For many IoT scenarios, CBOR formats will be preferred since it can help decrease transmission payload sizes as well as implementation code sizes compared to other data formats. Web Linking (RFC 8288) provides a way to represent links between Web resources as well as the relations expressed by them and attributes of such a link. In constrained networks, a collection of Web links can be exchanged in the CoRE link format (RFC 6690). Outside of constrained environments, it may be useful to represent these collections of Web links in JSON, and similarly, inside constrained environments, in CBOR. This specification defines a common format for this.

Abstract: The article considers the bibliographic database “Librarianship and Bibliography”, developed by the specialists of the Russian State Library in the context of other libraries and institutions that distribute resources related to library science. The author reveals the specifics of structure and composition of databases with similar resources, created by some central regional libraries of Russia and federal libraries of other departments. The authar touches upon the issue of foreign companies’ information support of studies in library science. This database was created using many years, experience in formation of information resources on culture and art, which have no analogues in Russia. The article presents the search capabilities of this bibliographic online resource and the practice of user interaction with it in 2016—2017. The author notes that the main body of records includes articles from monographs, scientific collections, conference proceedings and other publications. The article outlines the features of working with the database. The resource interface and the structure of its search fields are described. There are given some examples of its search fragments and navigation capabilities. Using statistical data, the author analyses the resorce access dynamics, user requests and the geography of user access to the database. The access leaders among the eight regions of the Russian Federation are Ural, Northwestern and Siberian Federal Districts. There is a stable interest observed in Siberian, Volga and Central Districts. The rating of the most popular search terms is made. The results of the study confirm the demand for the online resource among users. This is especially important in the conditions of low circulation of Russian scientific publications that significantly decreases their accessibility and reduces the ability to disseminate scientific knowledge among specialists.

Abstract: The invention relates to a hybrid APP local Web resource hot update mechanism, belonging to the technical field of mobile application and divided into two large update processes: a server Web resourceupdate packaging process and an APP update process, wherein the server Web resource update packaging process comprises saving the new version of the webpage resource to a specified folder of the server when there is a server-side webpage update. By accessing the server-defined update web application interface, the hot update of the web resource is implemented, the latest web resources of the server are ensured to be accurately transmitted to the client with a small amount of data, thereby quickly iterating functions, implementing new services and quickly fixing old-version bugs.

Abstract: The paper presents the techniques for supervised information extraction and change notification of the Web resources. The method uses the combination of supervised wrapping or Web scraping techniques integrated to a browser as an extension. A prototype was developed to provide the proof of concept validation and moreover to identify the pros and cons of proposed solution. The paper focuses on the core methods being used for structured data extraction from Web resources and on notification of the users in the most appropriate manner. The approach has a potential to share marked Web elements among users taking advantages of the collaborative annotation. The paper concludes with the research challenges stumbled on during the process on method design.