Developing Ontology Systems as a Base of an Environmental Quality Management Model in México

The process of identifying the attributes and relationships considered in an ontology is a complex task because there are many factors involved in the deterioration of environmental quality, the diversity of sources and data dispersion. This work presents an ontology that integrates the data required by an Environmental Quality Synoptic System (EQSS), which to date scatters in different Internet sites and concentrates by different agencies for example INEGI, CONABIO, SEMARNAT, CNA, among others. The methodology process consists of the collection of environmental information in Mexico through the application of computational techniques resulting ontology with environmental knowledge that will be processed by the system EQSS. Among the main advantages is than the selection and structure of information allow the automated generation of results in an environmental statement. The ontology proposal is based on knowledge of EQSS system that is based on the architecture of expert systems and through this important information for decision-making in regard to environmental quality and interaction with Geographic Information System (GIS) is obtained.

Ontology-Based Crime News Semantic Retrieval System

Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis.Crime news exists on the Internet in unstructured formats such as books,websites,documents,and journals.From such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement agencies.Keyword-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant results.They are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given word.Therefore,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the data.An ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal cases.The semantic system retrieves information in view of the similarity of the semantics among indexed data and user queries.In this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two experiments.In the first experiment,we implemented a keyword-based textual IR systemusing Apache Lucene.In the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL queries.The keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.

An Ontology-Based Question Answering System for University Admissions Advising

Question-Answer systems are now very popular and crucial to support human in automatically responding frequent questions in manyfields.However,these systems depend on learning methods and training data.Therefore,it is necessary to prepare such a good dataset,but it is not an easy job.An ontol-ogy-based domain knowledge base is able to help to reason semantic information and make effective answers given user questions.This study proposes a novel chatbot model involving ontology to generate efficient responses automatically.A case study of admissions advising at the International University–VNU HCMC is taken into account in the proposed chatbot.A domain ontology is designed and built based on the domain knowledge of university admissions using Protégé.The Web user interface of the proposed chatbot system is developed as a prototype using NetBeans.It includes a search engine reasoning the ontology and generat-ing answers to users’questions.Two experiments are carried out to test how the system reacts to different questions.Thefirst experiment examines questions made from some templates,and the second one examines normal questions taken from frequent questions.Experimental results have shown that the ontology-based chatbot can release meaningful and long answers.The results are analysed to prove the proposed chatbot is usable and promising.

Marx’s Ontology of Social Power System for Ecological Justice

Historical materialism provides the ontology basis to understand the contemporary ecological justice problem,which is the perspective for analyzing ecological interests from the nature,structure,and transition of the social power system.The transcendence of Marx’s thoughts on western mainstream environmental justice theory lies that it does not based on the“speculative ontology”of metaphysics,but on the basis of“realistic ontology”of social power system.

Ontology-Driven Analytic Models for Pension Management and Decision Support System

Ontology-Driven Analytic Models for Pension Management are sophisticated approaches that integrate the principles of ontology and analytics to optimize the management and decision-making processes within pension systems. While Ontology-Driven Analytic Models offer significant benefits for pension management, there are also challenges associated with implementing and utilizing the models. Developing a comprehensive and accurate ontology for pension management requires a deep understanding of the domain, including regulatory frameworks, investment strategies, retirement planning, and integration of data from heterogenous sources. Integrating these data into a cohesive ontology can be challenging. This research work leverages on semantic ontology as an approach for structured representation of knowledge about concepts and their relationships, and applies it to analyze and optimize decision support for pension management. The proposed ontology presents a formal and explicit specification of concepts (classes), their attributes, and the relationships between them and provides a shared and standardized understanding of the domain;enabling precise communication and knowledge representation for decision-support. The ontology deploys computational frameworks and analytic models to assess and evaluate data, generate insights, predict future pension fund performance as well as assess risk exposure. The research adopts the Reasoner, SPARQL query and OWL Visualizer executed over Java IDE for modelling the ontology-driven analytics. The approach encapsulated and integrated semantic ontologies with analytical models to enhance the accuracy, contextuality, and comprehensiveness of analyses and decisions within pension systems.

Using ontology and rules to retrieve the semantics of disaster remote sensing data

Remote sensing data plays an important role in natural disaster management.However,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster field retrieve remote sensing data.To improve this problem,this paper proposes an ontology and rule based retrieval(ORR)method to retrieve disaster remote sensing data,and this method introduces ontology technology to express earthquake disaster and remote sensing knowledge,on this basis,and realizes the task suitability reasoning of earthquake disaster remote sensing data,mining the semantic relationship between remote sensing metadata and disasters.The prototype system is built according to the ORR method,which is compared with the traditional method,using the ORR method to retrieve disaster remote sensing data can reduce the knowledge requirements of data users in the retrieval process and improve data retrieval efficiency.

Ontology-based proactive knowledge system

With the aim to address the problems presented in knowledge utilization in knowledge-intensive enterprises, the ontology-based proactive knowledge system （OPKS） is put forward to improve knowledge utilization. Proactive knowledge service is taken as the basic idea in the OPKS. The user knowledge requirement is taken as the driving factor and described by the user knowledge requirement. Ontologies are used to present the semantic of heterogeneous knowledge sources and ontology mapping is used to realize the interoperation of heterogeneous knowledge sources. The required knowledge is found by matching the user knowledge requirement with knowledge sources and is provided to the user proactively. System analysis and design of OPKS is carded on by adopting UML. The OPKS is implemented in Java language. Application in a certain institute shows that the OPKS can raise efficiency of knowledge utilization in knowledge-intensive enterprises.

Construction of the Ontology-Based Agricultural Knowledge Management System

Ontology is the formal representation of concepts and their mutual relations. It has wide application potential in the classification of agricultural information, the construction of information and knowledge database, the research and development of intelligent search engine, as well as the realization of cooperative information service, etc. In this research, an ontology-based agricultural knowledge management system framework is proposed, which includes modules of ontology-based knowledge acquisition, knowledge representation, knowledge organization, and knowledge mining, etc. The key technologies, building tools and applications of the framework are explored. Future researches on the theoretical refinement and intelligent simulation knowledge service are also envisioned.

A Dairy Industry Information Cooperative Service System Based on a Production Process Ontology

Agricultural information cooperative services （AICS） are now becoming an important aspect of agriculture informatization. This study offers an ontological conception of the agricultural production process, establishing operational divisions corresponding to both the stages and the fundamental information requirements of the dairy industry production process in China, yielding a process ontology for the dairy industry as well as a business chain model. A framework for a dairy industry information cooperative service system was established, with service functions realized in a prototype system. The resulting agricultural process ontology built on the basis of biological characteristics has advantages as a classification standard for agricultural information; whereas the business chain model based on this agricultural process ontology allows for an effective distribution of agricultural information cooperative services. This study outlines a concept and demonstrates a prototype of a cooperative service capable of integrating diverse online agricultural information relevant to the dairy industry in China.

Agricultural Market Name Geo-Locating System Based on an Administrative Ontology and Web Search Engine

The problem of associating the agricultural market names on web sites with their locations is essential for geographical analysis of the agricultural products. In this paper, an algorithm which employs the administrative ontology and the statistics from the search results were proposed. The experiments with 100 market names collected from web sites were conducted. The experimental results demonstrate that the algorithm proposed obtains satisfactory performance in resolving the problem above, thus the effectiveness of the method is verified.

Construction of an ontology-based nursing knowledge system

This study proposes the establishment of a knowledge-system ontology in the nursing field. It uses advanced data mining techniques,digital publishing technologies, and new media concepts to comprehensively integrate and deepen nursing knowledge and to aggregate sources of knowledge in specialized technical fields. This study applies all forms of media and transmission channels, such as personal computers and mobile devices, to establish a knowledge-transmission system that provides knowledge services such as knowledge search, update retrieval, evaluation, questions and answers(Q&As), online viewing, information subscription, expert services, push notifications, review forums, and online learning. In doing so, this study creates an authoritative and foundational knowledge service engine for the nursing field, which provides convenient, flexible, and comprehensive knowledge services to members of the nursing industry in a digital format.

On the Philosophical Ontology for a General System Theory

System is a very general concept and theoretically speaking, every problem encountered can be modeled as a system. Thus, the general system theory (GST) proposed by Bertalanffy (1968) and developed by many others e.g. Bunge (1977;1979;1983a;1983b) and Maturana and Varela (1980;1987) could be treated as a theory of everything (TOE). However, it is well-known that the present version of GST has not reached the level of TOE because it lacks a clear ontology. Currently, quantum mechanics (QM), Newtonian mechanics (NM) and general relativity (GR), suitable for microscopic, macroscopic and cosmic phenomena respectively are based on very different ontologies. In this paper, a unified ontology for the general system theory which could be applied to any scale from micro to cosmic is proposed. It is expected that this could lay a foundation to generalize GST to TOE.

Location Service Information Supporting System Based on Ontology

In order to solve the problem of how to collect and manage large amount of location information and improve the accuracy of location service, interactive information supporting system based on ontology and location service is presented in this paper. It can transmit special information about users＇ location to front-end instantaneously, so it is very convenient for their daily life. It makes full use of the available wireless communication, which is easy to arrange and convenient for users.

Distributed Human Resource Redistribution System Based on Agent and Ontology

A computer system for human resource （HR） redistribution system is presented to solve the balance problem of the ＂surplus resources＂ and ＂surplus tasks＂ among a group of project units. The system architecture is designed in a compositional manner using the elements of agent technology and knowledge technology. A combination of generic agent models, ontology and knowledge provides an effective approach to address the dynamic, distributed and knowledge-intensive characters of the HR management. In the system, the broker agent acting as intermediary provides matchmaking services to the domain agents, and the individual domain agents communicate directly with each other. The HR ontology provides the semantic match of the surplus task and the surplus resource. Finally, an application example is presented to illustrate the achieved solution for a concrete scenario. This novel way offers a comprehensive HR exchange solution and is snitablc for both intra-organizational and inter-organizational HR management.

TOWARDS AN ONTOLOGY-BASED MULTI-AGENT MEDICAL INFORMATION SYSTEM BASED ON THE WEB

This paper described an ontology based multi agent knowledge process made (MAKM) which is one of multi agents systems (MAS) and uses semantic network to describe agents to help to locate relative agents distributed in the workgroup. In MAKM, an agent is the entity to implement the distributed task processing and to access the information or knowledge. Knowledge query manipulation language (KQML) is adapted to realize the communication among agents. So using the MAKM mode, different knowledge and information on the medical domain could be organized and utilized efficiently when a collaborative task is implemented on the web.

Analysis of Deviations in an Agent and Ontology-Based Dialogue Management System

Algorithms of detecting dialogue deviations from a dialogue topic in an agent and ontology-based dialogue management system（AODMS） are proposed. In AODMS, agents and ontologies are introduced to represent domain knowledge. And general algorithms that model dialogue phenomena in different domains can be realized in that complex relationships between knowledge in different domains can be described by ontologies. An evaluation of the dialogue management system with deviation-judging algorithms on 736 utterances shows that the AODMS is able to talk about the given topic consistently and answer 86.6 % of the utterances, while only 72.1% of the utterances can be responded correctly without deviation-judging module.

Generalized Testability Scheme Modeling of Materiel System Based on Information Ontology

A mode of ontology-based information integration and management( OIIM) for testability scheme was proposed through expatiating on the connotation of the system testability scheme.Aiming at the complexity of influencing factors in optimal design procedure of the testability scheme, the information of concept entities,concept attributions and concept relationships was analyzed and extracted,and then the testability scheme information ontology( TSIO) was built and coded via web ontology language( OWL).Based on the information ontology, the generalized model for testability scheme( GMTS) was founded by defining transformation rules. The primary study shows that the mode of OIIM for testability scheme can make up the deficiencies in knowledge representation and reasoning existing in traditional information models,and achieve the information share and reuse. It provides the effectual model basis for the optimal design of the testability scheme.

Analyzing and Designing Business Processes Management System Based on Transformation of Instantiated Ontology’s State

The paper discusses efforts of finding a simple and transparent method to analyze business processes and developing its management system architecture. By introducing ontology and its state, the approach tried to find a unified representation and a flexible choreography of business processes. The main idea of the paper is the transformation of ontology＇s states, which are the most important scenarios of enterprises. The business activity composition, that is, case composition based on an AI technique, Case Based Reason （CBR）, which is to solve new problems by retrieving solutions to previous problems, and then store the modified solution. The main interest in CBR relies on that it allows a system to avoid past failures and exploit past successes.

KIS/OBT: A Tool to Build Ontology for Knowledge Integrating System

After many years research work, many intelligent systems based on knowledge have been created. But the differences in creating methods and applying background contexts make it difficult to share and reuse knowledge. This situation leads to the difficulty of building knowledge system. Without method using the existing system efficiently, people often build knowledge sys tem from scratch. In order to solve this problem, we use ontology as a foundation to realize know ledge sharing and reusing. As an important research area in AI, ontology building method has not acquired a common view. The method for building ontology was discussed, it’s principles and implementation.

Study of Information Management System for the Population of Yellow Stem Borer [Tryporyza incertulas(walker)] Based on Event Ontology

Based on the representation method of conventional knowledge, a new knowledge representation method for population of yellow stem borer [Tryporyza incertulas（walker）]based on event ontology is proposed, and the new information management system for the population of yellow stem borer is constructed based on the method of knowledge representation. Compared with traditional knowledge representation, representation method of event ontology knowledge adopts higher granularity events as knowledge representation units, which is more accorded with objective reality, having better scalability and integration.