Search results for "Knowledge extraction"
showing 10 items of 58 documents
A Knowledge Management System using Bayesian Network
2009
In today's world, decision support and knowledge management processes are strategic and interdependent activities in many organizations. The companies' interest on a correct knowledge management is grown, more than interest on the mere knowledge itself. This paper proposes a Knowledge Management System based on Bayesian networks. The system has been tested collecting and using data coming from projects and processes typical of ICT companies, and provides a Document Management System and a Decision Support system to share documents and to plan how to best use firms' knowledge.
A Knowledge Management System based on Ontologies
2009
Recently the companies’ interest on a correct knowledge management is grown, more than interest on the mere knowledge itself. In the last few years, several projects have been carried out, with the aim of the development of innovative systems capable of collecting and sharing information. This paper proposes a Knowledge Management System, whose main feature is an ontological knowledge representation. The ontological representation of data allows of specializing the reasoning capabilities and of providing ad hoc behaviors. The system has been tested collecting and using data coming from projects and processes typical of ICT companies, and provides a Document Management System and an Expert S…
An Ontology Design Methodology for Knowledge-Based Systems with Application to Bioinformatics
2012
Ontologies are formal knowledge representation models. Knowledge organization is a fundamental requirement in order to develop Knowledge-Based systems. In this paper we present Data-Problem-Solver (DPS) approach, a new ontological paradigm that allows the knowledge designer to model and represent a Knowledge Base (KB) for expert systems. Our approach clearly distinguishes among the knowledge about a problem to resolve (answering the what to do question), the solver method to resolve it (answering the how to do question) and the type of input data required (answering the what I need question). The main purpose of the proposed paradigm is to facilitate the generalization of the application do…
A Structural Approach to Infer Recurrent Relations in Data
2014
Extracting knowledge from a great amount of collected data has been a key problem in Artificial Intelligence during the last decades. In this context, the word "knowledge" refers to the non trivial new relations not easily deducible from the observation of the data. Several approaches have been used to accomplish this task, ranging from statistical to structural methods, often heavily dependent on the particular problem of interest. In this work we propose a system for knowledge extraction that exploits the power of an ontology approach. Ontology is used to describe, organise and discover new knowledge. To show the effectiveness of our system in extracting and generalising the knowledge emb…
XML-based Knowledge Discovery for Linguistic Atlas of Sicily (ALS) Project
2009
The identification of new useful patterns in data is a core process for intelligent systems. Information overflow is directly related to this problem. In this work we propose a knowledge discovery methodology to retrieve useful and novel information from raw data stored in a DBMS. We used ALSDB, a database that has been built suitably to access structured information obtained from the questionnaires produced in the Linguistic Atlas of Sicily (ALS) project. The ALS project is a decennal joint effort led by researchers at the Dipartimento di Scienze Filologiche e Linguistiche of the University of Palermo that has the purpose to track and study the geo-linguistic and lexicographic processes ab…
The ALSWEB Framework: A Web-based Framework for the Linguistic Atlas of Sicily Project
2011
In this work the ALSWEB framework is presented. The ALSWEB is a virtual linguistic laboratory for linguistic research developed as a web application. The purpose of the framework is to model the entire process regarding the different steps of data acquisition, data transformation, information acquisition from different data and research hypotheses verification in the ALS (Linguistic Atlas of Sicily) project. The nature of the ALS research involves different type of data. The socio-linguistic researcher that is the main actor of the proposed framework has to acquire information in many formats: multimedia data, audio data, question-answer (textual) from particular questionnaires. In this wor…
Knowledge Extraction from Healthcare Data Using User-Adaptable Keywords-Based Query Language
2020
Nowadays, the volume of the information gathered by any organization increases more and more rapidly. It is essential to be able to use this information efficiently for it to benefit the operation of the organization. There is no point of gathering the information if it is not converted into knowledge. The knowledge extraction process becomes the backbone of any successful organization. Moreover, the extraction of the knowledge must be quick and efficient, so that the newly-obtained knowledge can be put in use at once. The problem addressed in this paper is how to allow the domain expert to extract the knowledge from their information systems themselves without involving the third party in …
Gl-learning
2016
In this paper, we present a new open-source software library, Gl-learning, for grammatical inference. The rise of new application scenarios in recent years has required optimized methods to address knowledge extraction from huge amounts of data and to model highly complex systems. Our library implements the main state-of-the-art algorithms in the grammatical inference field (RPNI, EDSM, L*), redesigned through the OpenMP library for a parallel execution that drastically decreases execution times. To our best knowledge, it is also the first comprehensive library including a noise tolerance learning algorithm, such as Blue*, that significantly broadens the range of the potential application s…
Mobile agents and knowledge discovery in ubiquitous computing
2004
Publisher Summary This chapter discusses a knowledge discovery strategy to be performed by mobile agents in an augmented reality (AR) scenario. AR entities are implemented by mobile agents who perform all the behaviors of cooperating entities. Among other tasks, mobile agents implement a resource discovery strategy, which is aimed at filling lacking entities with missing methods and knowledge rules. A three layer entity description model and a cooperation mechanism are discussed, which allow knowledge and methods to be shared between entities in augmented reality. Three layers host three different projection descriptions of an AR entity respectively are: (1) a semantic projection for knowle…
An Ontology-Based Approach for the Reconstruction and Analysis of Digital Incidents Timelines
2015
International audience; Due to the democratisation of new technologies, computer forensics investigators have to deal with volumes of data which are becoming increasingly large and heterogeneous. Indeed, in a single machine, hundred of events occur per minute, produced and logged by the operating system and various software. Therefore, the identification of evidence, and more generally, the reconstruction of past events is a tedious and time-consuming task for the investigators. Our work aims at reconstructing and analysing automatically the events related to a digital incident, while respecting legal requirements. To tackle those three main problems (volume, heterogeneity and legal require…