Knowledge Modeling Research Papers - Academia.edu (original) (raw)

2025, Science Education

Perceptions of mentors' practices related to primary science teaching from nine Australian universities (n=331 final year preservice teachers) were gathered through a literature-based instrument. Five factors that characterise effective mentoring practices in primary science teaching were supported by confirmatory factory analysis. These factors, namely, personal attributes, system requirements, pedagogical knowledge, modelling, and feedback had Cronbach alpha coefficients of internal consistency reliability of . 93, .76, .94, .95, and .92 respectively. Final model fit indices were χ 2 =1335, df=513, CMIDF=2.60, IFI=.922, CFI=.921, RMR=.066, RMSEA=.070 (p<.001). Specific mentoring interventions for improving primary science teaching practices may be implemented by measuring preservice teachers' perceptions of their mentoring with a valid and reliable instrument.

2025, National Conference on Artificial Intelligence

The technology for building large knowledge bases (KBs) is yet to witness a breakthrough so that a KB can be constructed by the assembly of prefabricated knowledge components. Knowledge components include both pieces of domain knowledge (for example, theories of economics or fault diagnosis) and KB tools (for example, editors and theorem provers). Most of the current KB development tools can only manipulate knowledge residing in the knowledge representation system (KRS) for which the tools were originally developed. Open Knowledge Base Connectivity (OKBC) is an application programming interface for accessing KRSs, and was developed to enable the construction of reusable KB tools. OKBC improves upon its predecessor, the Generic Frame Protocol (GFP), in several significant ways. OKBC can be used with a much larger range of systems because its knowledge model supports an assertional view of a KRS. OKBC provides an explicit treatment of entities that are not frames, and it has a much better way of controlling inference and specifying default values. OKBC can be used on practically any platform because it supports network transparency and has implementations for multiple programming languages. In this paper, we discuss technical design issues faced in the development of OKBC, highlight how OKBC improves upon GFP, and report on practical experiences in using it.

2025, Lecture Notes in Computer Science

In this paper the underlying knowledge model and architecture of I-PETER (Intelligent Personalised English Tutoring EnviRonment) are presented. This system has been designed for the on-line distance learning of English where too many students restrict the teacher's possibilities to provide individualised guidance. I-PETER is made up of four domain models that represent linguistic and didactic knowledge: the conceptual framework related to linguistic levels and knowledge stages, and the educational content and study strategies. The student model represents the knowledge that the student has learnt, the study strategies, and his/her profile. A student's command of English is evaluated by interpreting his/her performance on specific linguistic units in terms of three related criteria, rather than by a general linguistic competence ranking. Evaluation consists of a diagnostic task model which assesses student performance, taking the form of a Bayesian network, and a selection mechanism that proposes appropriate materials and study strategies.

2025, Proceedings of IEEE International …

This paper is based on the survey of various clinicalautomated systems based on the tasks of temporalabstraction and temporal-maintenance. Further, we illustrate the integration of above two tasks using temporal mediators and will show... more

2025, Various database conferences

Content management is the process of handling information within an organization or community. Therefore, content management systems have to provide generic functionality for generation, extraction, storage, and exchange of digital assets. Because of the heterogeneity and complexity of content, a sufficient semantical and user-oriented annotation
of content is crucial. Although semantical annotation by metadata and ontologies together with reasoning support has been extensively studied for a long time, commercially available content management systems provide only basic support for semantic modelling. Conceptual aspects of content users and support of user specific intensions are neglected. In this paper collection we will analyze the mismatch between the requirements of content management and semantical description and propose a data model for content which treats semantic information not only as describing metadata but incorporates the data itself, the intension behind the data, the usage of data and the origin of data on the same level.

2025, Robotics and Computer-Integrated Manufacturing

This paper proposes a knowledge representation method that supports greater reuse of manufacturing knowledge in design. The method draws on recent research into objectoriented product and manufacturing models, and problem solving agents. A research platform is proposed, and the results of a test case (based on a simplified jet engine combustion chamber) are described. The paper concludes with three basic principles of reuse, i.e. product/process separation, procedural/declarative knowledge separation, and guidelines for the optimum location of rules and constraints within product/manufacturing models.

2025, 2009 21st IEEE International Conference on Tools with Artificial Intelligence

Knowledge constantly grows in scientific discourse and is revised over time by domain experts. The body of knowledge will get structured and refined as the Communities of Practice concerned with the field of knowledge develop a deeper understanding of issues. The knowledge model, as a result evolves to a new state to accommodate the new knowledge. Keeping trail of these changes in semantically rich and formally sound mechanism, has pragmatic advantages for providing the undo and redo facility and recover to a previous state of the knowledge body (i.e. ontology). In this research, we have developed and tested comprehensive methodological framework for Change Tracer. The ontology changes are captured and then stored in Change History Log (CHL) in conformance to Change History Ontology (CHO). The CHL is later used for reverting ontology to a previous consistent state and visualization of change effects on ontology. The system is compared with ChangesTab of Protégé, a comprehensive evaluation of the accuracy of rollback and roll-forward algorithm has been conducted over Documentation ontology. The system is also tested over a standard dataset of OMV and high accuracy results are observed for both roll-back and roll-forward algorithms.

2025

We report a strategy of collaborative knowledge modeling between experts and novices implemented in a Canadian organization since 2002 to support the transfer of expertise and knowledge management in this organization. Participants use an object-typed knowledge modeling editor called MOT to elaborate knowledge models in pairs. A knowledge model is similar to a concept map, except that it is based on a typology of knowledge objects and on a typology of links, and its structure is not necessarily hierarchical. This technique is used to represent concepts, principles, procedures and facts related to a specific aspect of the work done by employees in the organization. The paper presents the rationale behind this project, describes how it is implemented and identifies some research issues.

2025

Please, cite this publication as: Lundgren-Cayrol, K., Paquette, G., Marino, O., Léonard, M., & de la Teja, I. (2006). Learning Design Repositories – Structure Ontology and Processes. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence Conference. March 30th-31st, Sofia, Bulgaria: TENCompetence. Retrieved June 30th, 2006, from http://dspace.learningnetworks.org

2025

This chapter states and explains that a Learning Design is the result of a knowledge engineering process where knowledge and competencies, learning design and delivery models are constructed in an integrated framework. We present a... more

2025

This chapter discusses how to build IMS learning designs focusing on three aspects, instructional engineering, modeling tools and graphical design techniques. First, we propose that instructional designers use a systemic and systematic instructional engineering method to build Units of Learning conforming to the IMS-LD specification. MISA, a mature instructional engineering method will serve as the basis to our design approach. Second, we present a graphical modeling tool, MOT+, and a representation technique that was created to support instructional engineering. In MOT+, concepts, procedures and principles are used to describe all IMS-LD components as well as their relationships. We believe this graphical language to be closer to instructional designers, in that it represents a more pedagogical viewpoint than software engineering graphical languages like UML, while still enabling an automatic translation from graphical models into a machine-readable IMS-LD XML. Third, we will provide an example of the design processes involved in building learning designs, from the preliminary analysis to the definition of a unit of learning method, the central part of the IMS Learning Design.

2025

Domain ontologies that can solve various tasks using its concepts and determine fault reason for students’ answers may serve as a good basis for creating for a testing system with extensive explanatory abilities. But capabilities of modern ontological reasoners may not be enough for this kind of task. In this study, we developed and tested an ontology able to build execution trace for the given algorithm containing sequences and alternatives and find fault reasons for incorrect traces. The study also showed problems with the used reasoner that hinder the developed ontology from becoming fully effective.

2025, Yearbook of Medical Informatics

Summary Objectives To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. MethodsUsing examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. Results New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in ...

2025, Proc. 3th Scandinavian Conference on AI

Ahstract: Well Founded Semantics is shown adequate to capture hypothetical reasoning if we interpret the Well Founded model of a program P as a (possihly incomplete) view of the world. Thus the Well Founded model may he accepted as a partially definite view of the world, and the other extended stahle models as alternative extended consistent views of the world. The original contrihutions of this paper are: showing that Well Founded Semantics is useful for representing hypothetical reasoning prohlems; to present a framework for ...

2025, 2010 13th International Conference on Information Fusion

When ignorance due to the lack of knowledge, modeled as epistemic uncertainty using Dempster-Shafer structures on closed intervals, is present in the model parameters, a new uncertainty propagation method is necessary to propagate both aleatory and epistemic uncertainty. The new framework proposed here, combines both epistemic and aleatory uncertainty into a second-order uncertainty representation which is propagated through a dynamic system driven by white noise. First, a finite parametrization is chosen to model the aleatory uncertainty by choosing a representative approximation to the probability density function conditioned on epistemic variables. The epistemic uncertainty is then propagated through the moment evolution equations of the conditional probability density function. This way we are able to model the ignorance when the knowledge about the system is incomplete. The output of the system is a Dempster-Shafer structure on sets of cumulative distributions which can be combined using different rules of combination and eventually transformed into a singleton cumulative distribution function using Smets' pignistic transformation when decision making is needed.

2025

FrameNet Project is being developed by ICSI at Berkeley, with the goal of documenting the English language lexicon based on Frame Semantics. For Brazilian Portuguese, the FrameNet-Br Project, hosted at UFJF, follows the same theoretical and methodological perspective. This work presents a service-based infrastructure that combines Semantic Web technologies with FrameNet-like databases, by considering the hypothesis that the application of technologies such as ontologies, linked data, and web services can contribute to build and reuse lexical resources based on Frame Semantics. The contributions are related to enriched semantics, data reliability and natural language processing.

2025

Transferring expertise from highly qualified experts to nonexpert veterinarians and animal breeders is one of the Central Laboratory for Agricultural Expert Systems (CLAES) main objectives. CLAES used the knowledge based system technology to achieve this objective. Five animal knowledge based systems have been developed for diagnosis animal diseases and/or management farm. This paper presents the different methodologies used to develop these systems in Egypt. The used methodologies are: the hierarchical classification generic task, the case based reasoning and the commonKADS.

2025

The main objective of this paper is to propose a new concept of an intelligent tutoring system based on the use of an ontology for knowledge representation. An ontology provides a specific body of knowledge in a formal, structured and... more

2025, … of 1st International Conference on Obgect- …

INPE Instituto Nacional de Pesquisas Espaciais, Caixa Postal 515, 12.245-970 São José dos Campos, SP, Brazil (*) hermann@ltid.inpe.br, (**) carolina@ltid.inpe.br ... KEY WORDS: Object-oriented classification, Quickbird satellite, Ikonos... more

2025

The consensus of the documentation literature is that users rarely use help, usually preferring to muddle through. To increase use of help, tutorials for novice users could be changed from guided presentations toward using the system’s actual help system. To determine whether this approach would increase users’ use of help when they encountered problems with an application, we developed an alternative, help-based tutorial introduction to Microsoft Publisher. We compared the behaviors of users introduced to Publisher with the help-based tutorial with the behaviors of users who learned from a traditional tutorial. A balanced study of 22 novice users of Publisher suggests that using a help-based tutorial leads to significantly greater use of help systems when users encounter problems. However, the data also suggest that the increased use of help may not lead to more effective task performance.

2025, Communications of the ACM

Analysis for Knowledge MOdeling n recent years there has been increasing interest in describing complicated information processing systems in terms of the knowledge they have, rather than by the details of their implementation. This requires a means of modeling the knowledge in a system. Several different approaches to knowledge modeling have been developed by researchers working in Artificial Intelligence (AI). Most of these approaches share the view that knowledge must be modeled with respect to a goal or task. In this article, we outline our modeling approach in terms of the notion of a task-structure, which recursively links a task to alternative methods and to their subtasks. Our emphasis is on the notion of modeling domain knowledge using tasks and methods as mediating concepts. We begin by tracing the development of a number of different knowledge-modeling approaches. These approaches share many features, but their differences make it difficult to compare systems that have been modeled using different approaches. We present these approaches and describe their similarities and differences. We then give a detailed description, based on the task structure, of our knowledge-modeling approach and illustrate it with task structures for diagnosis and design. Finally, we show how the task structure can be used to compare and unify the other approaches. ® ® ® ® ® ® ® ® • ® ® ® • ® ® Knowledge-Based Systems: What are they?

2024

The worldwide increase in demand for qualified workers in science, technology, engineering, and mathematics (STEM) fields has resulted in a greater focus on preparing students to enroll in postsecondary STEM programs. The processes that lead students to become interested in and equip them for STEM careers begin years earlier. Previous research indicates that family background, financial resources, and prior family academic achievement can be used to predict whether a student will enroll in a STEM major. In this paper, we consider another class of factors that may be predictive while being more actionable. In this paper, we use predictive analytics, based on previously-validated automated detectors of student learning and engagement, to predict which students will choose a STEM major. With data from 363 college students who used ASSISTments during their regular middle school math classes, we develop a model that can successfully distinguish 66% of the time if a student will choose a STEM major or a non-STEM major when they enter college. In doing so, we offer steps towards providing educators with more actionable information on the STEM trajectories of individual students.

2024, Academia

Past work concerning the design and implementation of voice-operated personal assistants that are easy to configure and apply without directly worrying about the sophistication of leveraging Large Language Models or Neural Networks has been conducted at Makerere University via the use of intelligent parsing of user voice queries against simple plain-text Question-Answer Knowledge Bases (QAKBs). This work was part of the VOSA project, and was successfully presented at SE2024 in Copenhagen. However, one glitch in this Artificial Assistant model design is that the accuracy and relevance of the answers provided by the robot are so tightly coupled to the literal phrasing and expression of answers (and alternative answers) in the underlying manually prepared QA entries that define/compose a knowledge model against which the bot can correctly respond to questions about a particular domain. In reality though, such an approach can become too limiting; the authors of a QAKB need to know/anticipate all/most possible ways a user might pose a question to the robot in order to correctly match an entry in the KB; handling of answers that need to contain dynamic information (such as date and time, location, prices, weather and such) isn't easily catered for by the flat, literal and static JSON-formatted QAKB structures used in VOSA-like assistants much as they retain the advantage of being simpler for humans to reason about or tweak than most current alternatives using human-opaque structures such as use of matrices of probabilities in Hidden Markov [Knowledge] Models (HMKMs) or use of thousands if not millions or billions of weights and activation functions in Neural Network Models (NNMs). With the recent emergence of a feature-complete general-purpose Text Processing language, TEA, which, by its lightweight nature could allow for easy integration into existing or future intelligent systems, an idea for how VOSA-like Artificial Assistants could be further enhanced in terms of their cognitive processing power and efficiency is by leveraging smarter QAKB models that also allow for some runtime/just-in-time reprogramming/generation of answers to suit user-context and perhaps even add multi-turn QA Processing that is currently missing in VOSA but which is somewhat necessary given the state-of-the-art in assistant chatbot technologies across the industry. So, how might this better QAKB technology be realized? One idea is to add a TEA program processor inside of the VOSA client engine/architecture, and then, to allow for designers or authors of VOSA-targeting QAKBs to extend their QA-entries with specially crafted, domain relevant mini-programs or perhaps QAKB-wide QA-preprocessing Macro Programs either of which are written using the succinct, terse but powerful text processing language of TEA, the Transforming Executable Alphabet. This then would allow for VOSAC to sometimes take a user's query and the active QAKB, and then dynamically process it relative to preprocessing instructions embedded in the QAKB, and thus compile new or better answers to user queries on-the-fly and in a manner perhaps more straightforward and more transparent than leveraging pre-trained models or merely falling back to over-the-web queries to a search engine as the VOSA paper had originally proposed. This research shall also usher in a whole new approach to designing and programming Artificial Intelligence personal assistants that's different from approaches leveraging HMKMs, NNMs or just basic QAKBs and/or ontologies. Consider this a research proposal abstract.

2024, IGI Global eBooks

This chapter describes a model and an underlying theoretical framework for hybrid planning. Modern planning domain-description formalisms are based on purely sentential languages. Sentential representations produce problem encodings that often require the system to carry out an unnecessary amount of trivial deductions, preventing it from concentrating all the computational effort on the actual search for a plan and leading to a loss in performances. This chapter illustrates how techniques from the area of knowledge representation and reasoning can be adopted to develop more efficient domain-description languages. In particular, experimental evidence suggests that the adoption of analogical descriptions can lead to significant improvements in planning performance. Although often more efficient, however, analogical representations are generally less expressive than sentential ones. The hybrid approach proposed here provides a framework in which sentential and analogical descriptions can be integrated and used interchangeably, thereby overcoming the limitations and exploiting the advantages of both paradigms.

2024, National Conference on Artificial Intelligence

The effectiveness of tools that provide support for software development is highly dependent on the match between the tools and their task. Knowledge-acquisition (KA) tools constitute a class of development tools targeted at knowledge-based systems. Generally, KA tools that are custom-tailored for particular application domains are more effective than are general KA tools that cover a large class of domains. The high cost of custom-tailoring KA tools manually has encouraged researchers to develop recta-tools for KA tools. Current research issues in meta-tooZs for knowledge acquisition are the specification styles, or me,a-views, for target KA tools used, and the relationships between the specification entered in the metatool and other specifications for the target program under development. We examine different types of meta-views and meta-tools. Our current project is to provide meta-too!s that produce KA tools from multiple specification sources--for instance, from a task analysis of the target application. = :. _

2024, HAL (Le Centre pour la Communication Scientifique Directe)

This paper presents spatio-temporal multi-modality ontology for indexing and retrieving satellite images in the high level to improve the quality of the system retrieval and to perform semantic in the retrieval process. Our approach is based on three modules: (1) regions and features extraction, (2) ontological indexing and (3) semantic image retrieval. The first module allows extracting regions from the satellite image using the fuzzy c-means (FCM) segmentation algorithm. The second module allows indexing the satellite image by a spatio-temporal ontology which represents sensors, spatial objects, visual features (spectral signature, texture, shape, etc.), spatial relation between objects, temporal variation and semantic relation between terms. The last module allows retrieving satellite images by comparing the ontological model of the requested satellite image with the ontological model base. We adopted several algorithms for measuring the lexical and the structural similarity degree between ontological models. Our approach attempts to fully describe the semantic content of the satellite image and to perform the quality of the retrieval system.

2024

Introduction Several parts of the World Heritage City of Timbuktu have been destroyed during the Malian civil war [whc.unesco.org, 13/06/2013]. In Italy's Emilia Romagna and Lombardy regions, a series of earthquakes and their aftershocks caused serious damage to the cultural heritage in May 2012 [UNESCO, 2012]. These two examples illustrate that both human and natural actions can in a short time destroy objects to which a historical, scientifi c or aesthetic value has been attributed for a long time. Therefore, accurate documentation of cultural heritage is of inestimable value [Santana, 2003]. Such efforts at the protection and conservation of cultural heritage are generally accepted as important for future generations [e.g. UNESCO, 1972; Jokelitho, 2008]. However, there is no shared understanding of what is meant by 'cultural heritage' [Jokelitho, 2008; González-Pérez & Parcero-Oubiña, 2012], since several defi nitions exist in literature and in national and international legislation. For example, Jokelitho [2008] observed an emerging diversity of 'things' conceptualized as cultural heritage. In addition, González-Pérez and Parcero-Oubiña [2012] described a set of principles that reoccur in the defi nitions. For a clear understanding, this paper combines the defi nitions of the UNESCO 1 World Heritage Convention [1972] and the ICOMOS 2 [www. icomos.org, 8/03/2013]. In these defi nitions, monuments, groups of buildings, cultural landscapes and archaeological sites are considered as cultural heritage if they are assigned a historical, artistic or scientifi c value. For all of these classes of cultural heritage, a precise documentation results not only in a more well-founded assessment of its conservation state, but also in a better understanding of its historical background [Santana, 2003]. Consequently, sharing heritage documentation can create an important knowledge transfer between policy makers, researchers (e.g. archaeologists) and the general public (e.g. tourists) [Shaw et al., 2009; McKeague et al., 2012]. However, the future reuse of heritage documentation, such as archaeological data and its derived interpretations, is often prevented because the data sets (i) contain sensitive information, (ii) are conceived as copyrighted or (iii) are simply forgotten [McKeague et al., 2012]. The fi rst two reasons are linked to the general 'Open Data' 3 discussion. The last issue (iii) can be tackled by applying a common data model, which facilitates the sharing of information [Shaw et al., 2009; McKeague et al., 2012]. Besides enhancing the data interoperability and exchange by encouraging the use of data models, the domain of cultural heritage can also reap the fruits from the increasing popularity of Geographical Information Systems (GIS). These systems may hold many advantages for the integration and analysis of cultural heritage information. This paper focusses on the current use of GIS and data models in cultural heritage. The remainder of this paper is organized as follows. Section 2 de

2024

Intelligent Tutoring Systems are based on the knowledge-module that is holding the system's knowledge in a well-structured format. Considering the current state of the art knowledge-module representations, we lack a model that can represent evolving information. Representing evolving information is needed for those tutoring systems that are working with dynamically changing domains, e.g.: software science. In this paper a new combined model is presented that is based on the Ontology model and the fundamentals of Knowledge Space Theory. Our new model introduces the term of abstract time to be able to formulate an evolving knowledge graph. Our model also introduces the term of evoking-hooks that makes it possible to realize connections between external domain elements and our model's nodes.

2024

The aim of this paper is to improve one of the limitations of the fuzzy models of business failure. In this sense an application to a group of small and medium –sized enterprises (SMEs) from the construction sector is introduced in a given time horizon to test the diagnosis model capacity to predict diseases. This simulation involves the adaptation of the methodological hypothesis, and the definition of the main variables that interact in the estimation. This research presents the estimation of the matrix of economic–financial knowledge and verifies its capacity of diagnosis. Also, a goodness measure, through approximate solutions, is introduced to test the model ́s functionality with companies outside initial sample to demonstrate its ability to predict. Therefore, through this simulation some of the fuzzy model ́s restrictions are overcome, the theoretical postulates are adapted; the difficulties associated with the estimation are solved and new criteria and guidelines that enrich...

2024

A study was conducted to determine the effectiveness of using advance organizers in instruction at the graduate level. Participants were 218 graduate students in research methodology courses. Fifty-four students were enrolled in sections in which advance and post organizers were used; 164 were enrolled in sections in which this type of instruction did not take place. Conceptual knowledge, involving students' command of research concepts, methodologies, and applications, was measured individually in both sets of classes through midterm and final examinations. Findings show that students in the advance organizer sections of the course obtained higher levels of overall achievement than did their counterparts. The effect size pertaining to this difference was 0.54, which is considered moderate. The implications of these findings are discussed, as are recommendations for incorporating advance and post organizers in research methodology courses. (Contains 1 figure and 44 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document.

2024

Methods to help efficiently digest and use information have become an important research area in resolving information overload. While automatic text summarization research demonstrates significant efforts in this regard, the processes are complex and results have poorer quality than those created manually by experts. The generated summary tends to be rigid as the systems are designed for specific domains and applications. Our Automatic Table of Content Developer system, based on the Probability of Co-occurrence Analysis (POCA) technique, creates outputs that are content dependent, and yet the system can adapt to all document domains. We thus propose the resultant table-of-contents (TOC) display as an alternative to help users digest a large document collection using less time and effort.

2024, HAL (Le Centre pour la Communication Scientifique Directe)

In this article we analyse the notion of knowledge role. First of all, we present how the relationship between problem solving methods and domain models is tackled in different approaches. We concentrate on how they cope with this issue in the knowledge engineering process. Secondly, we introduce several properties which can be used to analyse, characterise and define the notion of role. We evaluate and compare the works exposed previously following these dimensions. This analysis suggests some developments to better exploit the relationship between reasoning and domain knowledge. We present them in a last section.

2024, HAL (Le Centre pour la Communication Scientifique Directe)

Resolving the semantic heterogeneity in the semantic web requires finding correspondences between ontologies describing resources. In particular, with the explosive growth of data sets in the Linked Open Data, linking multiple vocabularies and ontologies simultaneously, known as holistic matching problem, becomes necessary. Currently, most state-of-the-art matching approaches are limited to pairwise matching. In this paper, we propose a holistic ontology matching approach that is modeled through a linear program extending the maximumweighted graph matching problem with linear constraints (cardinality, structural, and coherence constraints). Our approach guarantees the optimal solution with mostly coherent alignments. To evaluate our proposal, we discuss the results of experiments performed on the Conference track of the OAEI 2015, under both holistic and pairwise matching settings.

2024, Expert Systems With Applications

In conceptual design of engineering devices, a designer decomposes a required function into sub-functions, so-called functional decomposition, using a kind of functional knowledge representing achievement relations among functions. However, such knowledge about functionality of engineering devices is usually left implicit because each designer possesses it. Even if such knowledge is found in documents, it is often scattered around technical domains and lacks consistency. Aiming at capturing such functional knowledge explicitly and sharing it in design teams, we discuss its systematic description based on functional ontologies which provide common concepts for its consistent and generic description. We propose a new concept named 'way of achievement' as a key concept for capturing such functional knowledge. Categorization of typical representations of the knowledge and its organization as is-a hierarchies are also discussed. The generic concepts representing functionality of a device in the functional knowledge are provided by the functional concept ontology, which makes the functional knowledge consistent and applicable to other domains. We also discuss development of a design supporting system using the systematized knowledge, called a functional way server. It helps human designers redesign an existing engineering device by providing a wide range of alternative ways of achievement of the required function in a manner suitable for the viewpoint of each designer and then facilitates innovative design.

2024

We present a stochastic greybox model of a BioDenitro WWTP that can be used for short time horizon Model Predictive Control. The model is based on a simplified ASM1 model and takes model uncertainty into account. It estimates unmeasured state variables in the system, e.g. the inlet concentration or the sensor measurements in case of temporary sensor faults. This improves control performance without adding additional or redundant sensors. We fitted the parameters of the model to actual plant data and demonstrate the state estimation capabilities with this data set. The model now runs online at a WWTP in Denmark.

2024

The resource accessibility problem in a cooperative learning environment can be stated as how both teachers and students can gain access to resources (information and hardware devices) not only from remote locations, but also from the classroom. In this paper we present a task model (TMo) that describes the services for a Resource Management System (RMS) to solve such problem. The model illustrates how to: 1) manage course information, and 2) operate hardware devices. As a modelling methodology we have resorted to CommonKADS.

2024, Revista da Escola de Enfermagem da USP

Artigo de reflexão que enfoca as origens e as principais caracterís-ticas dos modelos clínico e epide-miológico, seus nexos com os mo-delos assistenciais vigentes no sis-]tema de saúde brasileiro, e a cons-trução do conhecimento da enfer-magem nesse contexto. Nessa perspectiva, as autoras propõem um repensar acerca do saber/fazer da enfermagem, apontando possibilidades de expansão do seu campo de atuação, bem como dos limites e desafios a serem venci-dos pelos profissionais da área.

2024

This paper introduces and evaluates a new class of knowledge model, the recursive Bayesian multinet (RBMN), which encodes the joint probability distribution of a given database. RBMNs extend Bayesian networks (BNs) as well as partitional clustering systems. Briefly, a RBMN is a decision tree with component BNs at the leaves. A RBMN is learnt using a greedy, heuristic approach akin to that used by many supervised decision tree learners, but where BNs are learnt at leaves using constructive induction. A key idea is to treat expected data as real data. This allows us to complete the database and to take advantage of a closed form for the marginal likelihood of the expected complete data that factorizes into separate marginal likelihoods for each family (a node and its parents). Our approach is evaluated on synthetic and real-world databases.

2024, Lecture Notes in Computer Science

To select an adequate coding is one of the main problems in applications based on Evolutionary Algorithms. Many codings have been proposed to represent the search space for obtaining decision rules. A suitable representation of the individuals of the genetic population can reduce the search space, so that the learning process is accelerated by decreasing the number of necessary generations to complete the task. In this sense, natural coding achieves such reduction and improves the results obtained by other codings. This paper justifies the use of natural coding by comparing it with hybrid coding that joins well-known binary and real representations. We have tested both codings on a heterogeneous subset of databases from the UCI Machine Learning Repository. The experiments' results show that natural coding improves the quality of the obtained knowledge-model using only one third of the generations that hybrid coding needs as well as a smaller population.

2024, CAADRIA proceedings

In this paper we present a knowledge representation infrastructure that is being tested in collaboration with several institutions. This infrastructure is designed to map the structure of institutions dealing in Architecture and related disciplines, their interrelationships, and knowledge constructed by institutionalized processes in a given historical context.

2024

Three dimensional geometric models have been used in a variety of application areas, such as surgical simulation, planning, visualization, and teaching. In nearly all such domains, these models encode detailed spatial geometric information, but usually contain little additional information, such as knowledge about the structures these models contain or properties of those structures.

2024, Expert Systems with Applications

In this paper, we present SAMAP, whose goal is to build a software tool to help different people visit different cities. This tool integrates modules that dynamically capture user models, determine lists of activities that can provide more utility to a user given the past experience of the system with similar users, and generates plans that can be executed by the user. This system is intended to work in portable devices (mobile phones, PDAs, etc,) with internet connection. In this paper, we describe the architecture, the knowledge model that is shared among components using an ontology, and the three components of the tool: user module, case-based module and planning module.

2024, Proceedings of the 15th international conference on World Wide Web

2024

In this paper we want to show how the Eclipse platform can offer very interesting support and be an adequate infrastructure in the realization of a software environment for the design and development of security policies. The efficient and effective design of security policies for modern information systems is a crucial open problem, important and at the same time quite difficult. The lifecycle of a company-wide security system is complex. Its correct management requires conceptual depth, with the ability to describe the security configuration at different abstraction levels, from a representation that is near to the way security requirements arise from business applications, to the concrete configuration of the security components that characterizes the implementation of the system. Also, information systems present a large variety of securityenabled tools and devices, each one tailored to a specific task and operating on a specific representation of a system subset, and a correct security management environment has to be able to cover as many of them as possible. Ideally, an integrated security management environment should provide interoperability among all the security tools and assist the user in such a complex job. In such a scenario, Eclipse is able, with its open source technology and its flexible architecture, to support the realization of such systems, facilitating the integration among the separate models required to describe the security configuration of a heterogeneous system. For instance, formal ontologies can be easily integrated and they can be used for the definition of the involved models, with clear benefits in terms of automatization of model definition and control.

2024, Proc. 3th Scandinavian Conference on AI

2024

We developed a patent retrieval system with the cor- responding very large number of patents from NTCIR- 6 Patent Retrieval Task. And we developed a method of refining and emphasizing query. Our retrieval system consisting of four PCs could make indices of all claims in specifications for ten years. Then we confirmed that the query emphasis was better mean average precision than merely query expansion. And we had tried to re- duce the number of results with the belief assessment.

2024, International Journal of Human-Computer Studies

http://dia.fi.upm.es Summary. This article describes a knowledge-based application in the domain of road traffic management that we have developed following a knowledge modeling approach and the notion of problem-solving method. The article presents first a domain-independent model for real-time decision support as a structured collection of problem solving methods. Then, it is described how this general model is used to develop an operational version for the domain of traffic management. For this purpose, a particular knowledge modeling tool, called KSM (Knowledge Structure Manager), was applied. Finally, the article shows an application developed for a traffic network of the city of Madrid and it is compared with a second application developed for a different traffic area of the city of Barcelona.