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The web plays a crucial role in our daily life. Its openness allows users to access data around the clock. Recently, data has become more exploitable by machines due to the newly introduced mechanism of linked data, which improves the quality of published data on the web dramatically. Therefore, we have attempted to benefit from the investment, regarding data, which already exist on the web, particularly...
The consumption of Linked Data has dramatically increased with the increasing momentum towards semantic web. Linked data is essentially a very simplistic format for representation of knowledge in that all the knowledge is represented as triples which can be linked using one or more components from the triple. To date, most of the efforts has been towards either creating linked data by mining the web...
DBpedia is a huge dataset essentially extracted from the content and structure of Wikipedia. We present a new extraction producing a linked data representation of the editing history of Wikipedia pages. This supports custom querying and combining with other data providing new indicators and insights. We explain the architecture, representation and an immediate application to monitoring events.
It is found that learners prefer to use micro learning mode to conduct learning activities through open educational resources (OERs). However, adaptive micro learning is scarcely supported by current OER platforms. In this paper we focus on profiling an effective micro learning process which is central to establish the raw materials and set up rules for the final adaptive process. This work consists...
Exploiting facts that are published online using semi-structured or unstructured formats is a highly complex task, pieces of data are typically published in isolation and periodically updated in a bulk fashion without any coordination. In this paper, we propose a new software pipeline tackling this issue and semantically lifting online facts as Linked Data in a continuous manner. Our solution, LinkedPolitics,...
Most of today's commercial companies heavily rely on social media and community management tools to interact with their clients and analyze their online behaviour. Nonetheless, these tools still lack evolved data mining and visualization features to tailor the analysis in order to support useful marketing decisions. We present an original methodology that aims at formalizing the marketing need of...
The development of modern health care and clinical practice increase the need of nutritional and medical data extraction and integration across heterogeneous data sources. It can be useful for researchers and patients if there is a way to extract relevant information and organize it as easily shared and machine-processable linked data. In this paper, we describe an automatic approach that extracts...
We introduce a question-answering system that responds to a keywords-query by extracting information from linked data and generating reports in natural language (NL). Using entity disambiguation and distributed word similarity, we matched each keyword to a related entity and property in linked data. To extract keyword-related information, we used the entity and property to generate a SPARQL query...
Linked data consist of both node attributes, e.g., Preferences, posts and degrees, and links which describe the connections between nodes. They have been widely used to represent various network systems, such as social networks, biological networks and etc. Knowledge discovery on linked data is of great importance to many real applications. One of the major challenges of learning linked data is how...
Research in student retention is traditionally survey-based, where researchers use questionnaires to collect student data to analyse and to develop student predictive model. The major issues with survey-based study are the potentially low response rates, time consuming and costly. Nevertheless, a large number of datasets that could inform the questions that students are explicitly asked in surveys...
Nowadays the vast amount of text-based information stored in organizations requires different approaches and new tools in order to manage it adequately. This paper presents Hypatia, a support expert system for documentation departments and regular users that exploits not only local information, but also external resources from the Web (e.g., Linked Data). The expert system uses different modules:...
As a major role for data storage and knowledge management, file systems have been used both in enterprise contexts and personal information sphere for a long time. However, file systems organize file data using plain file hierarchies and have very little support for semantic annotation, linkage and semantic categorization. It is hard to integrate the file data with the Web of Data. In this paper,...
Today, Big Data is drawing a lot of attention and popularity and is aspiring enterprises to utilise more efficiently their data to help them understand how to better function, grow and manage as a business. Enterprises are aware that to derive real business value from Big Data and seek competitive advantages, they need to have available the right tool to extract, capture and organize a wide variety...
With the growing amount of published RDF datasets on similar domains, data conflict between similar entities (same-as) is becoming a common problem for Web of Data applications. In this paper we propose an algorithm to detect conflict of same properties values of similar entities and select the most accurate value. The proposed algorithm contains two major steps. The first step filters out low ranked...
Statistical data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we overview how statistical data can be managed on the Web. With OLAP2 Data Cube and CSV2 Data Cube we present two complementary approaches on how to extract and publish statistical data. We also discuss the linking,...
An increasing amount of data are published and consumed on the Web according to the Linked Data paradigm. In such scenario, understanding if the data consumed are up-to-date is crucial. Outdated data are usually considered inappropriate for many crucial tasks, such as make the consumer confident that answers returned to a query are still valid at the time the query is formulated. In this paper we...
There has been an ongoing trend towards open and shared source code that is published on the Internet in large software repositories to support collaborative development processes. While traditional source code analysis techniques perform well in single project contexts, new types of global source code analysis techniques are slowly introduced to address the analysis of global distributed and often...
In parallel to the effort of creating Open Linked Data for the World Wide Web there is a number of projects aimed for developing the same technologies but in the context of their usage in closed environments such as private enterprises. In the paper, we present results of research on interlinking structured data for use in Idea Management Systems - a still rare breed of knowledge management systems...
We have created a web agent for collecting Call for Papers (CFP) announcements. Our web agent obtains CFP announcements from websites or from mailbox. The most important information is extracted and published on our own special website in a user and machine readable way. One of the most important problems is event classification, categorization and clustering. In this paper we describe unsupervised...
Identification and assignment of (potential) experts to subject field is an important task in various settings and environments. In scientific domain, the identification of experts is normally based on number of factors like: number of publications, citation record, and experience etc. However, the discovered experts cannot be assigned reviewing duties immediately. One also need further information...
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