Semantic Framework for an Efficient Information Retrieval in the E-Government Repositories

2015 ◽  
pp. 192-213
Author(s):  
Antonio Martín ◽  
Carlos León
Keyword(s):  
Case Based Reasoning ◽  
Use Case ◽  
Digital Collections ◽  
Distributed Information ◽  
Semantic Framework ◽  
Semantic Metadata ◽  
Common Framework ◽  
Efficient Information ◽  
New Form ◽  
Semantic Search Engine

An enormous quantity of heterogeneous and distributed information is stored in e-government repositories. Access to these collections poses a serious challenge, however, because present search techniques based on manually annotated metadata and linear replay of material selected by the user do not scale effectively or efficiently to large collections. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. This chapter proposes a comprehensive approach for discovering information objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. The authors suggest a conceptual architecture for a semantic search engine. They use case-based reasoning methodology to develop a prototype. OntoloGov is a collaborative effort that proposes a new form of interaction between citizens and e-government repositories, where the latter are adapted to users and their surroundings.

Semantic Framework for an Efficient Information Retrieval in the E-Government Repositories

2018 ◽  
pp. 631-652
Author(s):  
Antonio Martín ◽  
Carlos León
Keyword(s):  
Case Based Reasoning ◽  
Use Case ◽  
Digital Collections ◽  
Distributed Information ◽  
Semantic Framework ◽  
Semantic Metadata ◽  
Common Framework ◽  
Efficient Information ◽  
New Form ◽  
Semantic Search Engine

An enormous quantity of heterogeneous and distributed information is stored in e-government repositories. Access to these collections poses a serious challenge, however, because present search techniques based on manually annotated metadata and linear replay of material selected by the user do not scale effectively or efficiently to large collections. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. This chapter proposes a comprehensive approach for discovering information objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. The authors suggest a conceptual architecture for a semantic search engine. They use case-based reasoning methodology to develop a prototype. OntoloGov is a collaborative effort that proposes a new form of interaction between citizens and e-government repositories, where the latter are adapted to users and their surroundings.

An agent-based supplier selection framework

2015 ◽  
Vol 8 (2/3) ◽  
pp. 180-205 ◽  
Author(s):  
Alireza Jahani ◽  
Masrah Azrifah Azmi Murad ◽  
Md. Nasir bin Sulaiman ◽  
Mohd. Hasan Selamat
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Information Overload ◽  
Case Based Reasoning ◽  
Multi Agent Systems ◽  
Content Type ◽  
Agent Based ◽  
Common Framework ◽  
Multi Agent ◽  
Case Based

Purpose – The purpose of this paper is to propose an approach that integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning. Unsatisfied customers, information overload and high uncertainty are the main challenges that are faced by today’s supply chains. In addition, a few existing agent-based approaches are tied to real-world supply chain functions like supplier selection. These approaches are static and do not adequately take the qualitative and quantitative factors into consideration. Therefore, an agent-based framework is needed to address these issues. Design/methodology/approach – The proposed approach integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning, as a common framework. These perspectives were rarely used together as a common framework in previous studies. Furthermore, an exploratory case study in an office furniture company is undertaken to illustrate the value of the framework. Findings – The proposed agent-based framework evaluates supply offers based on customers’ preferences, recommends alternative products in the case of stock-out and provides a collaborative environment among agents who represent different supply chain entities. The proposed fuzzy case-based reasoning (F-CBR) approach reduces the information overload by organizing them into the relevant cases that causes less overall search between cases. In addition, its fuzzy aspect addresses the high uncertainty of supply chains, especially when there are different customers’ orders with different preferences. Research limitations/implications – The present study does not include the functions of inventory management and negotiation between agents. Furthermore, only the case description and case retrieval phases of the case-based reasoning approach are investigated, and the remaining phases like case retaining, case reusing and case revising are not included in the scope of this paper. Originality/value – This framework balances the interests of different supply chain structural elements where each of them is represented by a specific agent for better collaboration, decision-making and problem-solving in a multi-agent environment. In addition, the supplier selection and order gathering mechanisms are developed based on customers’ orders.

Information systems: Basic notions

1994 ◽  
Vol 61 (1) ◽  
pp. 26-30
Author(s):  
S. Pasquali
Keyword(s):  
Information System ◽  
User Interface ◽  
Basic Structure ◽  
Case Based Reasoning ◽  
Image Management ◽  
Tracking Systems ◽  
Medical Work ◽  
Software Applications ◽  
Efficient Information ◽  
Case Based

This paper deals with the basic structure of computers (hardware and software) and some of the software applications now offered by technology; these applications can make medical work easier. Some features of advanced software applications are presented here, such as expert systems, case-based reasoning technics, image management, and also call tracking systems and user interface systems. The aim of this paper is to offer an overall view of the opportunity of setting up an efficient information system inside a health structure.

scholarly journals Wikidata as a semantic framework for the Gene Wiki initiative

2015 ◽  
Author(s):  
Sebastian Burgstaller-Muehlbacher ◽  
Andra Waagmeester ◽  
Elvira Mitraka ◽  
Julia Turner ◽  
Tim E. Putman ◽  
...  
Keyword(s):  
English Language ◽  
Biological Data ◽  
Use Case ◽  
Data Resource ◽  
Semantic Framework ◽  
Language Version ◽  
Human Genes ◽  
Starting Point ◽  
Human Proteins ◽  
Human And Mouse

Open biological data is distributed over many resources making it challenging to integrate, to update and to disseminate quickly. Wikidata is a growing, open community database which can serve this purpose and also provides tight integration with Wikipedia. In order to improve the state of biological data, facilitate data management and dissemination, we imported all human and mouse genes, and all human and mouse proteins into Wikidata. In total, 59,530 human genes and 73,130 mouse genes have been imported from NCBI and 27,662 human proteins and 16,728 mouse proteins have been imported from the Swissprot subset of UniProt. As Wikidata is open and can be edited by anybody, our corpus of imported data serves as the starting point for integration of further data by scientists, the Wikidata community and citizen scientists alike. The first use case for this data is to populate Wikipedia Gene Wiki infoboxes directly from Wikidata with the data integrated above. This enables immediate updates of the Gene Wiki infoboxes as soon as the data in Wikidata is modified. Although Gene Wiki pages are currently only on the English language version of Wikipedia, the multilingual nature of Wikidata allows for a usage of the data we imported in all 280 different language Wikipedias. Apart from the Gene Wiki infobox use case, a powerful SPARQL endpoint and up to date exporting functionality (e.g. JSON, XML) enable very convenient further use of the data by scientists. In summary, we created a fully open and extensible data resource for human and mouse molecular biology and biochemistry data. This resource enriches all the Wikipedias with structured information and serves as a new linking hub for the biological semantic web.

scholarly journals Copyright and Embargoes on Digital Collections

2017 ◽  
Author(s):  
Benjamin John Keele
Keyword(s):  
Fair Use ◽  
Use Case ◽  
Digital Collections ◽  
Working Paper

Working paper--comments welcome.This paper argues that libraries collecting digital works should consider imposing temporary discovery and access embargoes on some copyrighted works. These embargoes can strengthen the library's fair use case for creating and preserving digital copies.

Case reusing systems — survey, framework and guidelines

1997 ◽  
Vol 12 (01) ◽  
pp. 59-89 ◽  
Author(s):  
ANGI VOSS
Keyword(s):  
Case Based Reasoning ◽  
Common Framework ◽  
Key Issues ◽  
Global Strategies ◽  
Case Based

The discipline of case-based reasoning develops techniques to retrieve and reuse old solutions for new problems. To reuse solutions, several case adaptation systems have been built and many are under development. They deal with different tasks in different domains, but a methodology is still lacking. From an analysis of up-to-date case adaptation systems, this article moves towards a methodology by providing a common framework and some guidelines. As key issues case adaptation techniques, global strategies, and the tailoring of cases are discussed.

scholarly journals THE FOUR-MASTED BARQUE PEKING IN VIRTUAL REALITY AS A NEW FORM OF KNOWLEDGE TRANSFER

2020 ◽  
Vol V-4-2020 ◽  
pp. 155-162
Author(s):  
T. P. Kersten ◽  
D. Trau ◽  
F. Tschirschwitz
Keyword(s):  
Virtual Reality ◽  
Knowledge Transfer ◽  
Virtual Environment ◽  
Spatial Data ◽  
Use Case ◽  
Virtual Model ◽  
User Input ◽  
New Form ◽  
Immersive Visualization ◽  
Object Models

Abstract. Virtual Reality (VR) has established itself in recent years in the geosciences through its application in the immersive visualization of spatial data. In particular, VR offers new possibilities for the user to acquire knowledge through playful interaction within a virtual environment. This paper details the development and implementation of a new form of knowledge transfer, based on interactivity within a VR system. The particular use-case discussed is a VR application focusing on the four-masted barque Peking. From 2023 on, the restored ship will form an important exhibit in the future German Hafenmuseum in Hamburg. The new VR application offers users the possibility to enter and explore a virtual model of the Peking and find out more information at three separate points of interaction (3D object models, sails and ship flags). These interaction points provide a timely opportunity to examine several of the theoretical aspects of knowledge transfer through interactivity and integrate them in the development of the VR application. Above all, the VR application should be an important part of the learning process for the user. There remains still much potential for further research into more advanced approaches such as support for user-input questions and tailored content.

A Semantic Knowledge-Based Framework for Information Extraction and Exploration

2021 ◽  
Vol 13 (2) ◽  
pp. 85-109
Author(s):  
Abduladem Aljamel ◽  
Taha Osman ◽  
Dhavalkumar Thakker
Keyword(s):  
Open Data ◽  
Semantic Knowledge ◽  
Unstructured Data ◽  
Specific Information ◽  
Use Case ◽  
Binary Relations ◽  
Semantic Framework ◽  
Domain Specific ◽  
Knowledge Based ◽  
Financial Domain

The availability of online documents that describe domain-specific information provides an opportunity in employing a knowledge-based approach in extracting information from web data. This research proposes a novel comprehensive semantic knowledge-based framework that helps to transform unstructured data to be easily exploited by data scientists. The resultant sematic knowledgebase is reasoned to infer new facts and classify events that might be of importance to end users. The target use case for the framework implementation was the financial domain, which represents an important class of dynamic applications that require the modelling of non-binary relations. Such complex relations are becoming increasingly common in the era of linked open data. This research in modelling and reasoning upon such relations is a further contribution of the proposed semantic framework, where non-binary relations are semantically modelled by adapting the semantic reasoning axioms to fit the intermediate resources in the N-ary relations requirements.

scholarly journals Moral Consistency Reasoning Reconsidered

2019 ◽  
Vol 23 (1) ◽  
pp. 107-123 ◽  
Author(s):  
Norbert Paulo
Keyword(s):  
Moral Reasoning ◽  
Moral Psychology ◽  
Case Based Reasoning ◽  
Use Case ◽  
Moral Norms ◽  
Abstract Form ◽  
Moral Intuitions ◽  
Moral Consistency ◽  
Case Based

Abstract Many contemporary ethicists use case-based reasoning to reach consistent beliefs about ethical matters. The idea is that particular cases elicit moral intuitions, which provide defeasible reasons to believe in their content. However, most proponents of case-based moral reasoning are not very explicit about how they resolve inconsistencies and how they abstract principles from judgments about particular cases. The aim of this article is to outline a methodology—called Consistency Reasoning Casuistry—for case-based reasoning in ethics. This methodology draws on Richmond Campbell and Victor Kumar’s naturalistic model for the resolution of inconsistencies between the content of intuitions about particular cases. I argue that reasons similar to those that motivate their model also support a more abstract form of moral reasoning that goes beyond mere resolutions of inconsistencies between case judgments and demands the formulation of more abstract moral norms. Consistency Reasoning Casuistry, it is argued, is a good candidate for a methodology for case-based moral reasoning that is in harmony with paradigms of contemporary moral psychology and that can accommodate the methodology implicit in the work of many contemporary ethicists.

CASE-BASED-REASONING FOR IMAGE SEGMENTATION

2008 ◽  
Vol 22 (05) ◽  
pp. 829-842 ◽  
Author(s):  
MARIA FRUCCI ◽  
PETRA PERNER ◽  
GABRIELLA SANNITI DI BAJA
Keyword(s):  
Image Segmentation ◽  
Case Based Reasoning ◽  
Use Case ◽  
Image Domain ◽  
Segmentation Approach ◽  
Preliminary Study ◽  
Image Segmentation Algorithm ◽  
Grey Level Image ◽  
Case Based ◽  
Selection Of

This paper proposes to use case-based-reasoning for grey-level image segmentation. Different approaches to image segmentation have been proposed in the literature. The selection of the segmentation approach and the assignment of the values to the parameters involved in the selected algorithm depend on image domain and on the specific application. Case-based-reasoning seems a promising way to make the above selection automatic. In this paper, we describe the results of a preliminary study done in this respect. In particular, we refer to the automatic selection of the values of the parameters for a new watershed image segmentation algorithm.

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