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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...
The characteristics of big data not only challenge the processing methods of large volume of data, but also the way we make use of such semantic-rich resources, among which how users plan to manipulate the intermediate or final results requires to be well considered. This is especially challenging in building analytics systems as big data is richer in semantics and the heterogeneous data modalities...
In molecular biology, phenotypes are often described using complex semantics and diverse biomedical expressions, thereby facilitating the development of named entity recognition (NER). Here, we propose a novel approach of recognizing plant phenotypes by cascading word embedding to sentence embedding with a class label enhancement. We utilized a word embedding method to find high-frequency phenotypes...
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...
Automatic essay evaluation (AEE) systems are designed to assist a teacher in the task of classroom assessment in order to alleviate the demands of manual subject evaluation. However, although numerous AEE systems are available, most of these systems do not use elaborate domain knowledge for evaluation, which limits their ability to give informative feedback to students and also their ability to constructively...
The unstructured data, which volume grows exponentially, often hide important and even vital information for society and companies. It takes a lot of work to extract information such as the nature of consumption in a category of individuals, trends, etc. When it comes to statistical data, it is often very useful to synthesize this kind of information in the form of graphical representations. In this...
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...
This paper takes the basic endowment insurance related to social stability and economic development as an example to study the emotional analysis. Extracting major public opinion events and public attitudes related to the basic endowment insurance from the microblog, the paper extracts the subjective review information as the object of the study and perfects the emotional dictionary of the social...
In recent years, ontologies as a semantic knowledge representation become widely used in many information systems. Manual creation of ontologies by domain experts and ontology developers is also a costly task, time consuming and needs extra efforts. Learning Non-Taxonomic Relationships is a subfield of ontology learning which targets automatic extraction of non-taxonomic relationships from input,...
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...
In this paper, we present a new method for detecting professional skills (as noun phrases) from resumes written in natural language. The proposed method uses an ontology of skills, the Wikipedia encyclopedia, and a set of standard multi word part-of-speech patterns in order to detect the professional skills. First, the method checks to see if there are, in the text of the resumes, skills that are...
We present a system of services for the automatic processing of collections of scientific documents that are part of digital libraries. These services are based on ontologies for scientific documents representation, as well as on methods for semantic analysis of mathematical documents. The developed tools automatically check validity of documents for compliance with manuscript guidelines, convert...
Nowadays there are a great number of applications based on expert systems implementing the expertise of a human academic evaluator. Many of them refer to the self-evaluation of students' academic performance. The actual research targets the evaluation of academic courses from blended learning point of view. In this work, we present the design and implementation of an Intelligent Agent based Expert...
In this paper, we present an approach to adapt the e-assessment workflow by considering learner's profiles. We have started by creating a learner profile ontology based on extraction data from e-assessment activities, file log and personal information. Then, we have defined three adaptation actions: Add Activity, Edit Activity and Delete Activity, applied on the workflow assessment and using information...
Crowdsourcing data is an essential part of information collection in healthcare. Patient data serves as the foundation for creating healthcare policy, creating new pharmaceuticals, and determining treatment. In this paper, we propose a novel conceptual method of standardizing and classifying the crowdsourcing of healthcare data using modular ontologies, authoritative medical ontologies (AMOs) and...
The Internet of Things concept is increasingly being used in projects from different areas. Often, projects encompass applications from different domains that need to share information for a common purpose. These types of systems can become complex because they involve different domains and it can be difficult to share information without misinterpreting certain information. Ontologies can be a way...
Retrieving information based on the users’ preferences and profiles represent a challenging issue to overcome. Moreover, in the public transport field, this task becomes increasingly complex due to the heterogeneous data fetched from various sources. Though, ontologies have emerged in retrieving information field to reduce this complexity. This paper describes a visual framework aiming...
Identify the serious games that best meet the needs and expectations of teachers and pedagogical objectives of their courses remains a necessity about the integration of serious games in the learning process. Indeed, several serious games have developed in recent years, and it is often difficult for a teacher, not a computer scientist in particular, to find and choose a game that meets its specific...
Adaptive and Intelligent Educational Systems are interesting resources for supporting teaching-learning activities. Such environments make use of intelligent techniques to adapt educational content to the real needs of students. With the increasing amount of educational content becoming available, there is a good reason to believe that smart data analysis and machine learning techniques will become...
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