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This paper proposes a novel semiautomatic system domain data analysis method. The method is based on the iterative acquisition and analysis of a large body of bibliometric data, generation of domain taxonomies, and creation of domain models. The method was applied on a smart grid case study through collection and analysis of more than 6000 documents. We have found that our method produces domain models...
A large number of long non-coding RNAs (lncRNAs) have been identified over the past decades. Accumulating evidence proves that lncRNAs play key roles in various biological processes. However, the majority of the lncRNAs have not been functionally characterized. The annotation of lncRNA functions has become an area of focus in the fields of biology and bioinformatics. In this paper, we develop a global...
The collaborations of the diseases might be the key to understand the mechanism of the diseases since it is difficult to detect the role of complex genes and micro RNA in diseases. With the rapid development of technology, several metabolites of many kinds of diseases could be obtained by the advanced machines. Some diseases are related to several metabolites, and some metabolites have strong relationship...
Discovering similar diseases is very helpful for revealing the pathogenesis of diseases and making direction in drug use. And related diseases are often triggered by disease-related genes. Therefore, function interaction networks structured by disease-related genes are suitable for measurement of disease similarity, and some methods have utilized the advantage of function interaction of disease-related...
We propose a novel, semantic-reasoning-based approach to look for potentially adverse drug-drug interactions (DDIs) by using a knowledge-base of biomedical public ontologies and datasets in a semantic graph representation. This approach makes it possible to find previously unknown relations between different biological entities like drugs, proteins and biological processes, and perform inferences...
An ontology is a framework for describing domain-specific knowledge in a structured format. It is comprised of a set of terms as nodes and a set of relationships between terms as directed edges to form a directed acyclic graph. Gene Ontology (GO) and Human Phenotype Ontology (HPO) are widely referred biological and biomedical ontology databases. They also provide extensive annotations of human genes...
The aim of this paper is to introduce a semantic methodology using ontology in order to improve results of data mining in judicial decisions database. An intelligent and automatic method to search for sentences in lawsuits related to the one in trial is presented. A judicial ontology is built with and without rules from experts. The method can provide judiciary celerity, seeking to solve the yearning...
A thorough literature research is usually the first step when dealing with a novel topic in science. Regarding the medical domain, a popular starting point for this task is the web based search engine PubMed, which has an index of over 27 million medical publications from the MEDLINE database and other sources. Given certain search terms of interest, e.g. neurodegeneration or the drug FTY 720, results...
Barter system is an alternative commerce approach where customers meet at a marketplace in order to exchange their goods or services without currency. E-barter systems, also gain attention with the rise of e-commerce. Barterers search databases for goods and services they need. In this paper, the integration of ontology and agent systems is proposed as a solution for searching in diverse barter databases...
Advancements in both computer science and biotechnology opened way for an unprecedented amount and variety of gene expression raw data to appear in the open access. It is sometimes worth to rearrange and unite data from several similar gene expression studies into new case-control groups to test new hypothesis using available data. Unfortunately, most popular gene expression databases, such as GEO...
Data interoperability is a prerequisite to achieve cross-community and cross-application sharing of information and knowledge. Heterogeneous data from multiple sources including semantic and non-semantic data sources (e.g. SNS data, web data, relational data, RDF, XML, CSV, etc.) have an important effect for IoT service provisioning. The data are not in a same type or format always that requires to...
The emergence of a new paradigm such as ubiquitous or IoT implies that the members of future software systems can vary dynamically, rather than being predetermined according to the purpose of the system. Unlike in the case of the conventional systems, in order to give adaptability to systems that change dynamically, the system rules should be designed and applied considering the dynamic changes of...
Building the right team is vital for the success of any project in an organisation but many organisations today are faced with the problem of selecting the right mix of individuals to form a team. This process is often performed manually based on personal sentiments, while some automated approaches use normal database queries to assign individuals to tasks based on limited knowledge dimensions such...
Using formal concept analysis, we propose a method for engineering ontology from MongoDB to effectively represent unstructured data. Our method consists of three main phases: (1) generating formal context from a MongoDB, (2) applying formal concept analysis to derive a concept lattice from that formal context, and (3) converting the obtained concept lattice to the first prototype of an ontology. We...
Cross-bordering trade is considered as a significant driver in economic developments to promotions of regional stability and cooperations. With the current system, crossing borders must take much costs because there are many weak points in the processes, e.g., redundant clearance processes, and multiple documents requirements in different formats and different data elements. Thus, cross-bordering...
The development and enhancement of the effectiveness of scientific research in the learning process requires the use of new tools for working with knowledge using the methods of knowledge engineering: methods of Data Mining, Text Mining, semantic information processing technologies. The use of sets of video materials on a large scale for automatic annotation is a new task and requires the development...
Semantic similarity and relatedness are applied more and more extensively in many fields, such as in Artificial Intelligence, Semantic Web and Knowledge Management. In this paper, we propose a comprehensive metric of similarity, a method of relatedness measure and a comprehensive degree measure that combines semantic similarity and relatedness between two concepts. Then we compare the proposed metrics...
This article involves the analysis of known ontologies for solving production system management problems. The article considers the tasks solved by the ontological approach. It describes the developed ontology integration at the semantic level of data from databases of different industry information systems to support the management decisions, to use knowledge bases to support the decisions in logistics...
The word ontology refers to the hierarchical structure of entities and their relationships. The entities are nodes and each node is dominated by their parent node in the hierarchical structure. The nodes are related by semantic and lexical relations such as synonymy, homonymy, meronymy, antonymy, etc. Hierarchical structure is created for different types of semantic domains. The top domains are entities,...
In many real life situations end results and basic starting data are known. To deduce conclusive evidence or to build holistic picture one needs to find out hidden information and missing text. This research paper delivers a novel algorithm (Probabilistic Intent-Action Ontology and Tone Matching Algorithm) to map multiple events on time line by determining their interdependency to predict the most...
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