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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...
Linked Data is an emerging trend on the web with top companies promoting their own means of marking up data semantically, publishing and connecting data on Web. Despite the increasing prevalence of Linked Data, there are a limited number of applications that implement and take advantage of its capabilities, particularly in the domain of education. In this project we are using Semantic technologies...
We address the problem of record linkage and semantic integration in the context of large collections of user-generated content. These datasets are often large since it contains the contributions of millions of Internet users. We present an approach based on approximate string matching between the metadata associated with such data. The discovered linkages are stored in an ontology for answering queries...
A hierarchical learning algorithm is developed for supporting large-scale plant species identification. A visual tree is first constructed for organizing large numbers of plant species hierarchically in a coarse-to-fine fashion. For the fine-grained plant species at the sibling leaf nodes under the same parent node, they share significant common visual properties but still contain subtle visual differences,...
Bioenergy is a renewable energy generated from biomass, while biofuel is a hydrocarbon fuel that is produced from biomass. Recently, bioenergy and biofuel projects are encouraged and supported by many governments and organizations in various ways such as providing incentives, technical supports, information, and decision support tools. Economic model is one of the decision support tools, which helps...
Nearest neighbor search is a key technique used in hierarchical clustering. The time complexity of standard agglomerative hierarchical clustering is O(n3), while the time complexity of more advanced hierarchical clustering algorithms (such as nearest neighbor chain) is O(n2). This paper presents a new nearest neighbor search method called nearest neighbor boundary(NNB), which first divides a large...
This paper investigates the street-based network topology of urban spaces as represented in Geographic Information Systems (GIS) databases. We apply graph theoretical spectral methods to analysis of ways in maps. Our findings show that such methods can find natural parcellations of spaces, thus capturing the significance and semantics of a location from analysis of topological structure of the underlying...
In spite of the long tradition of Rhetorical Structure Theory (RST) in computational linguistics, there is no robust method capable of detecting rhetorical relations in the text of discourse. To pave the way for development of such techniques, we carried out experiments aimed at understanding the effectiveness of using corpus-based lexical cues in the identification of RST relations for three different...
Cyberattackers often attack the weakest point of system, which is increasingly the people who use and interact with a computer-based system. A great deal of research has been dedicated to protection of computer-based assets, but by exploiting human vulnerabilities, an attacker can circumvent many computer-based defenses. Phishing emails are a common form of social engineering attack, but the most...
Fashion is a key defining factor of popular culture, and it changes over time. Each season tons of new products emerge to the market. People who follow fashion wish to discover new and trendy products and quickly catch the most fashionable styles. Traditionally, product trends can be found in fashion magazines and product catalogs, but now the proliferation of the Internet and social networks may...
Successfully modeling state and analytics-based semantic relationships of documents enhances thoroughness of representation, contextualization of importance and relevancy, posterity of provenance, and a delineation of priority for a document. These attributes are the core elements that form the machine-based knowledge representation for documents. However, modeling document relationships that can...
As the literature of international business has been developed by contributions of researches from different areas, it has become a more complex system and researches from different areas have constructed a complex network for the research domain of international business. Data mining has become an important technology in researching networks of business area, and this research applies the technology...
Process exploration tools help to identify business processes that are not executed according to their documentation or lack such documentation at all. These process steps are executed by human beings, therefore process traces can often be found in unstructured documents. In order to reconstruct a process execution, these documents have to be retrieved. Natural language properties such as hyponyms,...
Most Arabic systems developed for newspaper information extraction relate to events that occurred in the past. This paper presents a proposal for developing a web-based system that will be able to regularly collect news reports from Arabic newspaper websites, and then be able to extract information relating to future events, e.g. event type, date and location. Also, the system will be able to deposit...
In today's cloud service market, different providers have very different low-level mechanisms to accommodate various types of policies from their users. Enforcement of policies over multiple cloud provider domains is an intrinsically complex problem for both sides. In reality, cloud providers have to either manually update enforcement mechanisms or negotiate adjusted policies with their users for...
With the increasing number of mobile devices, there have been many researches on searching and managing a large volume of mobile data. Most of the mobile platforms today provide users with keyword-based full text search (FTS) in order to search for mobile data. Recently, voice search interfaces have been deployed. These search methods, however, query only the keywords given as an input to local databases...
The Linked Data (LD) Cloud consists of LD sources covering a wide variety of topics. These data sources use formal vocabularies to represent their data and in many cases, they use heterogeneous vocabularies to represent data about the same topics. This data heterogeneity must be overcome to effectively integrate and consume data from the LD Cloud. Mappings overcome this data heterogeneity by transforming...
Today the Web represents a rich source of labour market data for both public and private operators, as a growing number of job offers are advertised through Web portals and services. In this paper we apply and compare several techniques, namely explicit-rules, machine learning, and LDA-based algorithms to classify a real dataset of Web job offers collected from 12 heterogeneous sources against a standard...
Semantic metadata has many uses in online virtual environments, but the technology for acquiring and managing metadata is not yet fully developed. This paper presents a partial solution that combines and extends traditional top-down and bottom-up approaches to semantic annotation. The paper proposes a metadata architecture composed of three layers, each of which has a metadata store and an interface...
An improved method of scene change detection (SCD) is required for content-based video analysis, indexing, searching and editing. Many researchers have suggested various SCD techniques in recent years. However, it is difficult to detect a scene change in the video context with a variety of camera movements and shot transitions. Moreover, data volume becomes an issue in the influx of ultra-high definition...
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