1,721,035 research outputs found
LPG-Based Knowledge Graphs: A Survey, a Proposal and Current Trends
Full text linkA significant part of the current research in the field of Artificial Intelligence is devoted to knowledge bases. New techniques and methodologies are emerging every day for the storage, maintenance and reasoning over knowledge bases. Recently, the most common way of representing knowledge bases is by means of graph structures. More specifically, according to the Semantic Web perspective, many knowledge sources are in the form of a graph adopting the Resource Description Framework model. At the same time, graphs have also started to gain momentum as a model for databases. Graph DBMSs, such as Neo4j, adopt the Labeled Property Graph model. Many works tried to merge these two perspectives. In this paper, we will overview different proposals aimed at combining these two aspects, especially focusing on possibility for them to add reasoning capabilities. In doing this, we will show current trends, issues and possible solutions. In this context, we will describe our proposal and its novelties with respect to the current state of the art, highlighting its current status, potential, the methodology, and our prospect
Holistic graph-based document representation and management for open science
No full textWhile most previous research focused only on the textual content of documents, advanced support for document management in digital libraries, for open science, requires handling all aspects of a document: from structure, to content, to context. These different but inter-related aspects cannot be handled separately and were traditionally ignored in digital libraries. We propose a graph-based unifying representation and handling model based on the definition of an ontology that integrates all the different perspectives and drives the document description in order to boost the effectiveness of document management. We also show how even simple algorithms can profitably use our proposed approach to return relevant and personalized outcomes in different document management tasks
Linking Graph Databases and Semantic Web for Reasoning in Library Domains
No full textThe need for digital libraries to store, catalogue, and manipulate documents is growing and the requirements are increasing daily. Much research is underway to discover effective ways to store and keep track of documents, their properties and uses. In this context, we propose the use of Labeled Property Graphs (LPGs) to store digital archives. The use of these graphs allows us high efficiency since the graphs are navigable very quickly thanks to Database Management Systems (DBMSs) (such as Neo4j) especially developed to guarantee high performance. On the other hand, this technology is not natively suited to infer new knowledge automatically. In this paper, we propose a method to use Semantic Web tools to enrich our knowledge base. This way, new operations are available, not possible with only graph databases. The proposed approach has been integrated into the GraphBRAIN (GB) system, a tool able to manage ontologies
A Graph DB-Based Solution for Semantic Technologies in the Future Internet
Full text linkWith the progressive improvements in the power, effectiveness, and reliability of AI solutions, more and more critical human problems are being handled by automated AI-based tools and systems. For more complex or particularly critical applications, the level of knowledge, not just information, must be handled by systems where explicit relationships among objects are represented and processed. For this purpose, the knowledge representation branch of AI proposes Knowledge Graphs, widely used in the Semantic Web, where different online applications may interact by understanding the meaning of the data they process and exchange. This paper describes a framework and online platform for the Internet-based knowledge graph definition, population, and exploitation based on the LPG graph model. Its main advantages are its efficiency and representational power and the wide range of functions that it provides to its users beyond traditional Semantic Web reasoning: network analysis, data mining, multistrategy reasoning, and knowledge browsing. Still, it can also be mapped onto the SW
An Ontology-driven Architecture for Intelligent Tutoring Systems with an Application to Learning Object Recommendation
No full textThe state-of-the-art in Artificial Intelligence (AI), the Internet, and the computational power reached by current technologies, allow much more advanced thinking about Intelligent Tutoring Systems than their original definition. The KEPLAIR project envisions an online platform, designed to help all players involved in educational endeavors, especially learners, to improve performance and effectiveness of their activities. Using leading edge AI solutions, KEPLAIR will act as a personalized assistant, helping its users in the entire educational experience, from goal elicitation through learning path definition, selection of materials, performance/attainment testing, analytics and report building. This paper introduces the architecture and functionalities of KEPLAIR as well as illustrating a new methodology for Learning Object (LO) suggestion based on personal profile informatio
TestGraphia, Document Analysis-Based Diagnosis of Dysgraphia
No full textDysgraphia is a disease related to handwriting and affects the size and distance of the characters and orthography. Patients with dysgraphia may have difficulties in motor skills and can hardly write down what they think. Dysgraphia symptoms are not rare but often are temporary. There are no specific causes known that can lead to dysgraphia, and then it is impossible to prevent it. For these reasons, it is crucial to find out dysgraphia; traditional methods are based on specific paper forms and rules to diagnose a suspect of dysgraphia. In this paper, we present a document analysis-based diagnosis process to support doctors to formulate a diagnosis. The medical examination can be completed in a short time. This system allows also large screening activities reducing any effort and permits a remote doctor-patient relationship: while it is being developed as a web-application, and due to its ease of use, it could be used at home, eventually revealing early symptoms
LPG-based Ontologies as Schemas for Graph DBs
No full textGraph DBs are an emerging NoSQL technology that is boosting the opportunity of data handling based on interconnection and processing of single instances, rather than batch processing as usual in traditional relational DBs. Differently from relational DBs, the most prominent graph DB, Neo4j, is schema-less and based on the LPG graph model. We propose the definition and uses of ontologies as schemas, which would also enable high-level (logical) automated reasoning on the data. The graph model adopted by standard approaches to ontologies in Computer Science is incompatible with the LPG model. So, we propose a technology, called GraphBRAIN, specifically designed to exploit the full representational power of LPGs, still having a mapping to standard ontological approaches. GraphBRAIN also allows to apply different schemas on one underlying graph, representing different but inter-related views on the same data, and to combine schemas. This paper describes the formalism and outlines its possible applications. Development and implementation of the technology is ongoing, and a prototype is available and running
Holistic Graph-Based Document Representation and Management for Open Science
No full text(Extended Abstract) While most previous research focused only on the textual content of documents, advanced support for document management in Digital Libraries, for Open Science, requires handling all aspects of a document: from structure, to content, to context. These different but inter-related aspects cannot be handled separately, and were traditionally ignored in Digital Libraries. We propose a graph-based unifying representation and handling model based on the definition of an ontology that integrates all the different perspectives and drives the document description in order to boost the effectiveness of document management. We also show how even simple algorithms can profitably use our proposed approach to return relevant and personalized outcomes in different document management tasks
A Holistic Ontology for Digital Libraries The IFLA-compliant Core
No full textThe record-based approach to library information organization is obsolete and cannot support advanced opportunities provided by AI. Graph-based representations driven by ontologies are needed, but representation models proposed in this field are not compliant with those adopted by DBs. GraphBRAIN is a framework and technology that applies the ontological approach to the LPG model adopted by graph DBs, taking the best of both worlds: representational power and flexibility of ontologies and efficiency in data handling of DBs. It can be mapped onto the standard Semantic Web representations. The International Federation of Library Associations and Institutions (IFLA) proposed different conceptual models of library data that move from record-based to relational representations, but do not reach the ontological level. Conversely, attempts to tackle the ontological level are often not fully compliant with the IFLA models. This paper reports on developing an ontology based on GraphBRAIN technology that aligns the various models proposed by IFLA, fully representing their elements. It shows how it can be expanded to include elements that are not traditionally represented in library models, but that can unleash new potentiality for library practitioners, researchers and end-users
Simultaneous separation of malondialdehyde, ascorbic acid, and adenine nucleotide derivatives from biological samples by ion-pairing high-performance liquid chromatography
No full textA method for a simultaneous separation of malondialdehyde (MDA), ascorbic acid and adenine nucleotide derivatives in biological samples by ion-pairing high-performance liquid chromatography is presented. The separation is obtained by an LC-18-T 15 cm x 4.6 mm 3 μm particle size column using tetrabutylammonium as the pairing ion. The starting buffer consists of 10 mM tetrabutylammonium hydroxide, 10 mM KH2PO4 plus 1% methanol, pH 7.00. A step gradient is formed using a second buffer consisting of 2.8 mM tetrabutylammonium hydroxide, 100 mM KH2PO4 plus 30% methanol, pH 5.5. Under these chromatographic conditions a highly resolved separation of MDA, ATP, ADP, AMP, adenosine, ascorbic acid, GTP, GDP, IMP, inosine, Hypoxanthine, Xanthine, uric acid, NAD, and NADP can be performed in about 36 min. In addition, the separation of NADH and NADPH can also be obtained; this renders the present method suitable for the detection of these reduced coenzymes in alkaline extracts from tissue samples. Data referring to PCA extracts from ischemic and reperfused isolated rat hearts and from human erythrocytes peroxidized in vitro by a challenge with 1 mM NaN3 and various concentrations of H2O2 are reported. The relevance of this chromatographic method lies in the possibility to determine directly MDA concentrations avoiding the unspecific thiobarbituric acid colorimetric test, any other manipulation of the sample out of the PCA extraction, and any possible coelution of other acid soluble compounds. The simultaneous determination of MDA, ascorbic acid, and of ATP and its degradation products gives the opportunity to correlate, by a single chromatographic run, peroxidative damages with the energy state of the cell which is of great importance in studies of ischemic and reperfused tissues
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