Abstract: The Open Annotation Core Data Model specifies an interoperable framework for creating associations between related resources, called annotations, using a methodology that conforms to the Architecture of the World Wide Web. Open Annotations can easily be shared between platforms, with sufficient richness of expression to satisfy complex requirements while remaining simple enough to also allow for the most common use cases, such as attaching a piece of text to a single web resource. This paper presents the W3C Open Annotation Community Group specification and the rationale behind the scoping and technical decisions that were made. It also motivates interoperable Annotations via use cases, and provides a brief analysis of the advantages over previous specifications.

Abstract: Similar to data mining, three major web mining operations include clustering, association rule mining, and sequential analysis. Typical clustering operations in web mining involve finding natural groupings of web resources or web users. Researchers have found and pointed at some important and fundamental differences between clustering in conventional applications and clustering in web mining. Moreover, due to variety of reasons inherent in web browsing and web logging, the likelihood of bad and incomplete data is higher. This is where Rough Set Theory can play a crucial role and researchers have been utilizing this in clustering the incomplete data and thus aiding in decision making. This paper aims at understanding the Rough Set Theory and its applications in web mining.

Abstract: One key feature of the Semantic Web lies in the ability to link related Web resources. However, while relations within particular datasets are often well-defined, links between disparate datasets and corpora of Web resources are rare. The increasingly widespread use of cross-domain reference datasets, such as Freebase and DBpedia for annotating and enriching datasets as well as documents, opens up opportunities to exploit their inherent semantic relationships to align disparate Web resources. In this paper, we present a combined approach to uncover relationships between disparate entities which exploits (a) graph analysis of reference datasets together with (b) entity co-occurrence on the Web with the help of search engines. In (a), we introduce a novel approach adopted and applied from social network theory to measure the connectivity between given entities in reference datasets. The connectivity measures are used to identify connected Web resources. Finally, we present a thorough evaluation of our approach using a publicly available dataset and introduce a comparison with established measures in the field.

Abstract: One key feature of the Semantic Web lies in the ability to link related Web resources. However, while relations within particular datasets are often well-defined, links between disparate datasets and corpora of Web resources are rare. The increasingly widespread use of cross-domain reference datasets, such as Freebase and DBpedia for annotating and enriching datasets as well as documents, opens up opportunities to exploit their inherent semantic relationships to align disparate Web resources. In this paper, we present a combined approach to uncover relationships between disparate entities which exploits (a) graph analysis of reference datasets together with (b) entity co-occurrence on the Web with the help of search engines. In (a), we introduce a novel approach adopted and applied from social network theory to measure the connectivity between given entities in reference datasets. The connectivity measures are used to identify connected Web resources. Finally, we present a thorough evaluation of our approach using a publicly available dataset and introduce a comparison with established measures in the field.

Abstract: The Web has developed to the biggest source of information and entertainment in the world. By its size, its adaptability and flexibility, it challenged our current paradigms on information sharing in several areas. By offering everybody the opportunity to release own contents in a fast and cheap way, the Web already led to a revolution of the traditional publishing world and just now, it commences to change the perspective on advertisements. With the possibility to adapt the contents displayed on a page dynamically based on the viewer's context, campaigns launched to target rough customer groups will become an element of the past. However, this new ecosystem, that relates advertisements with the user, heavily relies on the quality of the underlying user profile. This profile has to be able to model any combination of user characteristics, the relations between its composing elements and the uncertainty that stems from the automated processing of real-world data. The work at hand describes the beginnings of a PhD project that aims to tackle those issues using a combination of data analysis, ontology engineering and processing of big data resources provided by an industrial partner. The final goal is to automatically construct and populate a profile ontology for each user identified by the system. This allows to associate these users to high-value audience segments in order to drive digital marketing.

Abstract: Scholars are using the Web every day to search, read, collaborate, and ultimately do their research. While some of the basic activities that the scholars do, such as reading and writing papers, are already well supported in the digital world, some essential scholarly primitives, such as annotation, augmentation, contextualiza- tion, and externalization, do not yet have clear support in terms of software tools. What scholars ultimately do during their research activity is to iteratively and collaboratively create new knowledge. With the advent of the Digital Humanities, we now have the opportunity—and technology—to capture at least a part of this knowledge and make it available as machine-processable data so to be better explorable and discoverable. In this paper, we present and discuss Pundit: a novel semantic annotation tool that enables scholars to collect, annotate, and contextualize Web resources. Deep-linking is used in conjunction with an RDF- based data model to allow granular selection of content (e.g. text excerpts, image fragments). Pundit aims at enabling scholars to produce meaningful machine- readable data that captures the semantics of their annotations. By providing a customizable annotation environment, where domain specific vocabularies can be loaded, and easy ways of integrating with existing Web archives or libraries, Pundit enables users to publish their annotations and collaboratively build a semantic graph. Such a graph can be consumed via HTTP APIs and standard SPARQL, thus allowing existing Linked Data applications to easily work with the data and Web clients in general to build specific visualizations.

Abstract: Introduction. People search for information on different search engines billions of times day all over the developed world. Not all Web resources are, however, equally authoritative and not all sea ...

Abstract: With the increasing development of distributed computer systems (DCSs) in networked industrial and manufacturing applications on the World Wide Web (WWW) platform, including service-oriented architecture and Web of Things QoS-aware systems, it has become important to predict the Web performance. In this paper, we present Web performance prediction in time and in space by making a forecast of a Web resource downloading using the Turning Bands (TB) geostatistical simulation method. Real-life data for the research were obtained in an active experiment conducted by our multi-agent measurement system MWING performing monitoring of a group of Web servers worldwide from agents localized in different geographical localizations in Poland. The results show good quality of Web performance prediction made by means of the TB method, especially in the case when European Web servers were monitored by an MWING agent localized in Gliwice, Poland.

Abstract: Efficient learning from Web resources can depend on accurately assessing the quality of each resource. We present a methodology for developing computational models of quality that can assist users in assessing Web resources. The methodology consists of four steps: 1) a meta-analysis of previous studies to decompose quality into high-level dimensions and low-level indicators, 2) an expert study to identify the key low-level indicators of quality in the target domain, 3) human annotation to provide a collection of example resources where the presence or absence of quality indicators has been tagged, and 4) training of a machine learning model to predict quality indicators based on content and link features of Web resources. We find that quality is a multifaceted construct, with different aspects that may be important to different users at different times. We show that machine learning models can predict this multifaceted nature of quality, both in the context of aiding curators as they evaluate resources submitted to digital libraries, and in the context of aiding teachers as they develop online educational resources. Finally, we demonstrate how computational models of quality can be provided as a service, and embedded into applications such as Web search.

Abstract: The amount of web-based resources (databases, tools etc.) in biomedicine has increased, but the integrated usage of those resources is complex due to differences in access protocols and data formats. However, distributed data processing is becoming inevitable in several domains, in particular in biomedicine, where researchers face rapidly increasing data sizes. This big data is difficult to process locally because of the large processing, memory and storage capacity required. This manuscript describes a framework, called MAPI, which provides a uniform representation of resources available over the Internet, in particular for Web Services. The framework enhances their interoperability and collaborative use by enabling a uniform and remote access. The framework functionality is organized in modules that can be combined and configured in different ways to fulfil concrete development requirements. The framework has been tested in the biomedical application domain where it has been a base for developing several clients that are able to integrate different web resources. The MAPI binaries and documentation are freely available at http://www.bitlab-es.com/mapi under the Creative Commons Attribution-No Derivative Works 2.5 Spain License. The MAPI source code is available by request (GPL v3 license).

Abstract: Interactive three-dimensional content is the primary element of virtual reality (VR) and augmented reality (AR) systems. The increasing complexity and the use of VR/AR systems in various application domains requires efficient methods of creating, searching and combining interactive 3D content, which could be used by people with different specialities, who are not required to be IT-experts. The Semantic Web approach enables description of web resources with common semantic concepts. However, the use of semantic concepts may also facilitate creation of 3D content. The main contribution of this paper is a method of semantic modelling of interactive 3D content. The method leverages semantic constraints between different components of 3D content as well as representations of 3D content at different levels of abstraction. It can be used with a multitude of domain-specific ontologies and knowledge bases to simplify creating and searching of reusable semantic 3D content components and assembling complex 3D scenes from independent distributed elements.

Abstract: Instantiating a resource of an IT-service includes: analyzing a service model including nodes representing resources and being indicative of a resource type, each node comprising a generic API providing at least one abstract method for instantiating the resource represented by the respective node. For each node, determining the resource type indicated by the node; evaluating a service provider catalog indicative of a resource manager operable to provide a resource of a given resource type and determining an address of the resource manager; selecting a resource manager; sending a request to the address of the selected resource manager for a description of a resource-manager-specific API of the resource manager; receiving the requested description from the selected resource manager; overriding the abstract method by a resource-manager specific method of the resource-manager-specific API for instantiating the resource; and executing the overridden abstract method for instantiating the resource represented by the node.

Abstract: There is provided a method for delivering web resources to user devices, the method comprising: receiving a plurality of resource requests for a web resource, each resource request being received from a respective user device; and, for each resource request for the web resource, sending an authorisation request to an access server, the authorisation request including authorisation data comprising user identification information. Further, there is provided method for authorising delivery of web resources, the method comprising: receiving an authorisation request from a content delivery network, the request including authorisation data comprising user identification information; authorising the authorisation request based on the authorisation data; and, returning a response to the content delivery network based on the authorisation, wherein if the authorisation is negative the response includes an address of an alternative web resource different from the requested web resource. A content delivery network, access server, system and computer readable medium are also provided.

Abstract: The complexity of 3D content makes its creation accessible to professional IT developers equipped with specific software tools and hardware devices, but it is generally inaccessible to non-expert users. The Semantic Web approach enables description of web resources with commonly used concepts. However, the use of semantic concepts may also facilitate creation of interactive 3D content. In this paper, a new approach to conceptual semantic representation of 3D content is proposed. The presented solution permits modelling of 3D content at an arbitrarily high level of semantic abstraction with the use of domain-specific ontologies. Thanks to the compliance with well-established solutions for semantics and 3D content representation, the proposed approach can facilitate widespread creation, dissemination and reuse of 3D content by non IT-professionals in a variety of application domains.

Abstract: The invention discloses a method for web downloading, which comprises the steps that a request for downloading web resources in a page is initiated during page loading; the request for downloading the web resources is intercepted; a downloading request queue is formed according to downloading priorities corresponding to classes of the web resources in the request for downloading the web resources; and the web resources of different classes are downloaded in the downloading request queue according to the downloading priorities. According to the method, the web resources requested by a web are classified and subjected to priority processing on the downloading based on the classes of the network resources; the resources influencing a web effect can be downloaded preferentially during web browsing; and the web downloading efficiency is improved under the condition that a user experience is not influenced.

Abstract: The initiation of a reload event by a user of a client-side application who requests a web resource from a server is an implicit indication that the user is dissatisfied with at least some aspect of the loading of the web resource by the client-side application. Information regarding the operational condition of the application at the time of a reload event may be instructive in identifying any issues or deficiencies exist regarding the web resource, the client-side application or the server. Code for displaying the web page may include one or more detection scripts which instruct the client-side application and/or the server-side application to detect a reload event, to capture the information upon the initiation of the reload event and to transfer the captured information back to the server, where the information may be compared against thresholds or tolerances to determine whether any such issues or deficiencies exist.

Abstract: Techniques for sharing application states are disclosed. According to one aspect of the disclosure, the techniques include receiving a web resource identifier indicating a web address of a web server hosting a web application and including one or more parameters indicating a state of the web application. The techniques also include obtaining an instruction set for generating an application resource identifier, the instruction set being obtained based on a first portion of the web resource identifier. The techniques further include determining one or more parameter values based on the web resource identifier and the instruction set, and generating an application resource identifier based on the instruction set and the one or more parameter values, the application resource identifier being indicative of the state accessed via a native application.

Abstract: A computer-implemented method includes receiving from a user a reference to a web resource for sharing with others, and providing a portion of content generated based on the received reference to the web resource for display to the user. The method also includes receiving a user selection of a portion of the generated content based at least on the displayed portion of the generated content. The method also includes generating the snapshot based on the received user selection of the portion of the generated content, and providing, without further user intervention, a rendering including the reference to the web resource and the generated snapshot for sharing with the others. Systems and machine-readable media are also provided.

Abstract: The invention provides a method of accelerating webpage loading. The method comprises the following steps: when determining that loaded web resources to be loaded contain adverting web resources, modifying a web resource loading sequence in a web resource scheduling strategy generated by a client browser according to a strategy that non-adverting web resources in the web resources of the same type are prior to the adverting web resources; and loading the web resources according to the modified web resource scheduling strategy. By utilizing the method, the web resources of the same type can be loaded and subjected to priority partition again, so that the loading priority of the non-adverting web resources is higher than the loading priority of the adverting web resources, thus the loading time of the web resources, which is more important to the user, is shortened.

Abstract: The invention discloses a network resource semantic retrieval method and a network resource semantic retrieval system based on a resource description framework. A resource description method provided by using the resource description framework is used for carrying out data modeling on a heterogeneous resource on a Web; uniform description based on RDF (Radio Direction Finding) is carried out according to models so as to support information retrieval based on semantics in a querying process, so that physically-loosened resources in a previous system are effectively and logically collected together by the uniform description based on the RDF, web resources are effectively utilized and the target of sharing the resources on different platforms is realized. A resource semantic related base is introduced to store resources with the relevancy on the aspect of the semantics and the dynamic change of the Web resources is successfully processed, so that the recall ratio and the precision ratio are guaranteed. A dynamic sieving algorithm based on a bayesian decision theory is adopted to ensure that a usually-queried object is placed into a high-speed buffering storage and the time of returning back to a queried result is effectively shortened.

Abstract: Web services are application based programming interfaces (API) or web APIs that are accessed through Hypertext Transfer Protocol (HTTP) to execute on a remote system hosting the requested services. A RESTFUL web service is a budding technology, and a light weight approach that do not restrict the client- server communication. The open authorization (OAuth) 2.0 protocol enables the users to grant third-party application access to their web resources without sharing their login credential data. The Authorization Server includes authorization information with the Access Token and signs the Access Token. An access token can be reused until it expires. An authentication filter is used for business services. This paper presents a secure communication at the message level with minimum overhead and provides a fine grained authenticity using the Jersey framework. Keywords: Open authorization (oauth), Restful web services, HTTP protocols and uniform resource identifier(URI).

Abstract: With the constant evolution of the Internet, a repetitive and ordinary task such as searching online resources has become more complex due to the amount of web services and formats available (e.g., video, audio, text or images). In order to obtain resources within a specific domain, a user manually performs several tasks, such as navigating through different web services, filtering according to various criteria and selecting the relevant results. However, the insufficient contextual information of the underlying application hampers the user's experience. In this paper, we propose a tool to improve a user's experience by automating the task of retrieving interesting resources in a multi user setting. We apply this approach to a chat scenario where users are exposed to resources that are of common interests by exploiting the users' personal context information.

Abstract: Most traditional recommender systems focus on the objective of improving the accuracy of recommendations in a single domain. However, preferences of users may extend over multiple domains, especially in the Web where users often have browsing preferences that span across different sites, while being unaware of relevant resources on other sites. This work tackles the problem of recommending resources from various domains by exploiting the semantic content of these resources in combination with patterns of user browsing behavior. We overcome the lack of overlaps between domains by deriving connections based on the explored semantic content of Web resources. We present an approach that applies Support Vector Machines for learning the relevance of resources and predicting which ones are the most relevant to recommend to a user, given that the user is currently viewing a certain page. In real-world datasets of semantically-enriched logs of user browsing behavior at multiple Web sites, we study the impact of structure in generating accurate recommendations and conduct experiments that demonstrate the effectiveness of our approach.