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Concept maps are resources for the representation and construction of knowledge. They allow the showing, through concepts and relationships, how knowledge about a subject is organized. Technological advances have boosted the development of technological approaches that help the automatic construction of a map, in order to facilitate and provide the benefits of that resource more broadly. Because of...
Organizations have an increasing need to adapt faster their Information Systems to technical, functional and legal changes. One way proposed in the literature is to make a deep process analysis in order to have a better comprehension of the business process (BP) and adapt it to its new context. In this paper, we propose a meta model for a BP contextualization solution. The solution links a BP with...
This paper presents preliminary result of research project, which is aimed to combine ontology information retrieval technology and process mining tools. The ontologies describing both data domains and data sources are used to search news in the Internet and to extract facts. Process Mining tools allows finding regularities, relations between single events or event types to construct formal models...
Over the years, the volume of information available through the world wide web has been increasing continuously, and never has so much information readily available and shared among so many people. Unfortunately, the unstructured nature and huge volume of information accessible over network have made it difficult for users to shift through and find relevant information. The information retrievals...
The main problem of rule-based information extraction technique is that the extraction rules tend to be specifically designed for specific information or document structure; hence it cannot be directly used in another without some proper modifications. Semi-structured documents like tables present another challenge to information extraction; since there are no standards on how to design it, the structure...
Given the explosive growth of scientific information and the fast advancement of research fields, researchers may not be able to find the most promising topics to combine with their current research and may be trapped in a few familiar research topics without creative ideas. Many studies of recommendation system make the effort to address the above problem, but they ignore the different styles of...
Nowadays, owing to the growth of quantity of data, the data mining techniques have been required on web exceedingly for extracting information from the data. Classification of text in data mining is very important and has been a hot issue on the topic. Especially, ontological taxonomy classification is important for more intelligent information reasoning. As it relates to data distribution of classes...
Ontology-based approaches have been explored in several domains for knowledge representation and improving accuracy. However, ontology-based approaches for assisting a decision maker by delivering a concrete plan from analyzing the insights extracted from an ontology, have not received much attention. Insights-as-a-service is a technology that aids a decision maker by providing a concrete action plan,...
Ontology Learning (OL) from a text is a process that consists of text processing, knowledge extraction, and ontology construction. For Arabic language, text processing, and knowledge extraction tasks are not mature as for Latin languages. They have not been integrated into the full Arabic OL pipeline. Currently, there is very little automated support for using knowledge from Arabic literature in semantically-enabled...
The number of web documents as well as the inherent data and information is growing at a rapid pace. The interest in extracting and utilizing this data is rising likewise. The prospects that are unlocked by Web Data Extraction to its users are as broad as the extensiveness of topics and fields on the Web. The major obstacle is to utilize the available data, contents and processes. Several, mostly...
An interesting class of irregular algorithms are tree traversal algorithms, which repeatedly traverse spatial trees to perform efficient computations. Optimizing tree traversal algorithms requires understanding specific characteristics of these algorithms which affect their behavior and govern which types of optimizations are likely to perform well. In this work, we present a set of tree traversal...
This work introduces CONCEPTUM, an advanced knowledge discovery system for speed-reading natural language texts and allowing faster and more effective learning. CONCEPTUM sports a huge plethora of features, ranging from language detection and conceptualization, up to semantic categorization, named entity recognition and automatic ontology building, effectively turning an unstructured textual source...
Today, it is possible to monitor a gene expression on a genomic scale using hierarchical clustering, DNA micro-arrays and k-means partitioning which are being the most popular methods. Several tools make use of the GO ontologies or the gene associations provided by consortium members or even individuals. While some progress has been made in addressing the gene classification, current methods are restricted...
Incidents of public security have an ascendant trend in recent years all over the world, and it is more important to understand the correlation of different kinds of public security incidents. With the popularization of the Internet, numerous web messages can provide resources to do that. However, an important challenge is that the web messages are often heterogeneous and unstructured. In this paper,...
Medical files and observation papers have always been an important source of knowledge. Unfortunately, most of the times they are still stored as physical documents either printed or handwritten, thus making it difficult to transfer this precious information from one place to another, or centralizing and extracting new knowledge from it. But with nowadays advancements in computer science this problem...
Many domains of Embedded Systems (e.g., automotive, avionics, consumer electronics, industrial automation, medical…) are rapidly evolving toward solutions that integrate hardware and software, or incorporate complete systems in a single chip. The specificities of the concepts have a complexity on data analysis and during the identification of relationship between them. The usage of an ontology for...
The gathering of real-world data is facilitated by many pervasive data sources such as sensor devices and smartphones. The abundance of the sensory data raises the need to make the data easily available and understandable for the potential users and applications. Using semantic enhancements is one approach to structure and organize the data and to make it processable and interoperable by machines...
The knowledge behind the gigantic pool of data remains largely unextracted. Techniques such as ontology design, RDF representations, hpernym extraction, etc. have been used to represent the knowledge. However, the area of logic (FOPL) and linguistics (Semantics) has not been explored in depth for this purpose. Search engines suffer in extraction of specific answers to queries because of the absence...
The information construction plays an essential role in the area of public security. However, the “Information Silo” phenomenon in Public Security Department has become a bottleneck of the development of public security. The paper proposes a novel approach to implement a public security knowledge navigation system, utilizing the information extraction to obtain the ontology for the topic maps of public...
Ontology matching requests to find correspondences between entities of two semantically related ontologies. several approaches have been proposed for ontology matching. The most of those approaches are based on similarity measurements. consequently, they can detect only the equivalence relations between entities and do not take into account the asymmetric relations such as the subsumption. In addition,...
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