A Textual Case-Based Mobile Phone Diagnosis Support System

Java Cases and Ontology Libraries Integration for Building Reasoning Infrastructures (jCOLIBRI) is a framework which makes the development of Textual Case-Based Reasoning (CBR) applications easier by providing the preprocessing of text methods, textual similarity methods and appropriate representation for textual cases which are the major techniques needed in any CBR systems. In this paper, a Mobile Phone Diagnosis Support System is presented as an extension to jCOLIBRI which accepts a problem and reasons with cases to provide a solution related to a new given problem. Experimental evaluation using some set of problems shows that the developed system predicts the solution that is relatively closer to the user given mobile phone problem. The solution also provide the user valuable advise on how to go about solving the new problem

Clood CBR: towards microservices oriented case-based reasoning.

CBR applications have been deployed in a wide range of sectors, from pharmaceuticals; to defence and aerospace to IoT and transportation, to poetry and music generation; for example. However, a majority of these have been built using monolithic architectures which impose size and complexity constraints. As such these applications have a barrier to adopting new technologies and remain prohibitively expensive in both time and cost because changes in frameworks or languages affect the application directly. To address this challenge, we introduce a distributed and highly scalable generic CBR system, Clood, which is based on a microservices architecture. This splits the application into a set of smaller, interconnected services that scale to meet varying demands. Experimental results show that our Clood implementation retrieves cases at a fairly consistent rate as the casebase grows by several orders of magnitude and was over 3,700 times faster than a comparable monolithic CBR system when retrieving from half a million cases. Microservices are cloud-native architectures and with the rapid increase in cloud-computing adoption, it is timely for the CBR community to have access to such a framework

A Case-based Reasoning Approach to Validate Grammatical Gender and Number Agreement in Spanish language

Across Latin America 420 indigenous languages are spoken. Spanish is considered a second language in indigenous communities and is progressively introduced in education. However, most of the tools to support teaching processes of a second language have been developed for the most common languages such as English, French, German, Italian, etc. As a result, only a small amount of learning objects and authoring tools have been developed for indigenous people considering the specific needs of their population. This paper introduces Multilingual–Tiny as a web authoring tool to support the virtual experience of indigenous students and teachers when they are creating learning objects in indigenous languages or in Spanish language, in particular, when they have to deal with the grammatical structures of Spanish. Multilingual–Tiny has a module based on the Case-based Reasoning technique to provide recommendations in real time when teachers and students write texts in Spanish. An experiment was performed in order to compare some local similarity functions to retrieve cases from the case library taking into account the grammatical structures. As a result we found the similarity function with the best performance

Integrating case based reasoning and geographic information systems in a planing support system: Çeşme Peninsula study

Thesis (Doctoral)--Izmir Institute of Technology, City and Regional Planning, Izmir, 2009Includes bibliographical references (leaves: 110-121)Text in English; Abstract: Turkish and Englishxii, 140 leavesUrban and regional planning is experiencing fundamental changes on the use of of computer-based models in planning practice and education. However, with this increased use, .Geographic Information Systems. (GIS) or .Computer Aided Design.(CAD) alone cannot serve all of the needs of planning. Computational approaches should be modified to deal better with the imperatives of contemporary planning by using artificial intelligence techniques in city planning process.The main aim of this study is to develop an integrated .Planning Support System. (PSS) tool for supporting the planning process. In this research, .Case Based Reasoning. (CBR) .an artificial intelligence technique- and .Geographic Information Systems. (GIS) .geographic analysis, data management and visualization techniqueare used as a major PSS tools to build a .Case Based System. (CBS) for knowledge representation on an operational study. Other targets of the research are to discuss the benefits of CBR method in city planning domain and to demonstrate the feasibility and usefulness of this technique in a PSS. .Çeşme Peninsula. case study which applied under the desired methodology is presented as an experimental and operational stage of the thesis.This dissertation tried to find out whether an integrated model which employing CBR&GIS could support human decision making in a city planning task. While the CBS model met many of predefined goals of the thesis, both advantages and limitations have been realized from findings when applied to the complex domain such as city planning

Case acquisition from text: ontology-based information extraction with SCOOBIE for myCBR

myCBR is a freely available tool for rapid prototyping of similarity-based retrieval applications such as case-based product recommender systems. It provides easy-to-use model generation, data import, similarity modelling, explanation, and testing functionality together with comfortable graphical user interfaces. SCOOBIE is an ontology-based information extraction system, which uses symbolic background knowledge for extracting information from text. Extraction results depend on existing knowledge fragments. In this paper we show how to use SCOOBIE for generating cases from texts. More concrete we use ontologies of the Web of Data, published as so called Linked Data interlinked with myCBR’s case model. We present a way of formalising a case model as Linked Data ready ontology and connect it with other ontologies of the Web of Data in order to get richer cases

Razonamiento basado en casos (RBC) para toma de decisiones en proyectos de implementación de sistemas ERP utilizando jColibri

Propone un Modelo de Razonamiento Basado en Casos (RBC) que permita contar con información oportuna, ágil y confiable para la gestión del conocimiento y la toma de decisiones en proyectos de Implementación de Sistemas ERP. Para realizar el presente trabajo se utilizará la herramienta jColibri la cual es un armazón o Framework orientado a objetos que facilita la construcción de sistemas de razonamiento basado en casos (RBC). La implementación del modelo incrementa la calidad de la información y reduce los tiempos utilizados en solucionar los problemas de toma de decisiones de estos proyectos.Trabajo de suficiencia profesiona

Collective Intelligence to solve creative problems in conceptual design phase

In industry, there is an interest in the collective resolution of creative problems found on the phase of conceptual design. In this work we introduce an information-based software framework for collaboration in the problem resolution process. This framework proposes the implementation of techniques from the collective intelligence research field in combination with the systematic methods provided by TRIZ theory. Both approaches are centered in the human aspect of the innovation process, and are complementary. While collective intelligence focuses on the intelligence or behavior that emerges in collaborative work, the TRIZ theory is centered in the individual's capacity to solve problems. The framework's objective is to improve the individual creativity provided by TRIZ method and tools, with the value created by the collective contributions. This work aims to expand the horizon in the field of computer aided innovation (CAI), to the next evolutionary step called Open CAI 2.0

Extracting knowledge from web communities and linked data for case-based reasoning systems

Web communities and the Web 2.0 provide a huge amount of experiences and there has been a growing availability of Linked Open Data. Making experiences and data available as knowledge to be used in case-based reasoning CBR systems is a current research effort. The process of extracting such knowledge from the diverse data types used in web communities, to transform data obtained from Linked Data sources, and then formalising it for CBR, is not an easy task. In this paper, we present a prototype, the Knowledge Extraction Workbench KEWo, which supports the knowledge engineer in this task. We integrated the KEWo into the open-source case-based reasoning tool myCBR Workbench. We provide details on the abilities of the KEWo to extract vocabularies from Linked Data sources and generate taxonomies from Linked Data as well as from web community data in the form of semi-structured texts

Tuuurbine: A Generic CBR Engine over RDFS

International audienceThis paper presents Tuuurbine, a case-based reasoning (CBR) system for the Semantic Web. Tuuurbine is built as a generic CBR system able to reason on knowledge stored in RDF format; it uses Semantic Web technologies like RDF/RDFS, RDF stores, SPARQL, and optionally Semantic Wikis. Tuuurbine implements a generic case-based inference mechanism in which adaptation consists in retrieving similar cases and in replacing some features of these cases in order to obtain one or more solutions for a given query. The search for similar cases is based on a generalization/specialization method performed by means of generalization costs and adaptation rules. The whole knowledge (cases, domain knowledge, costs, adaptation rules) is stored in an RDF store