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    SECTION 1: Review
    The AGROVOC Concept Scheme-A Walkthrough
    Sachit Rajbhari, Johannes Keizer
    2012, 11(5): 694-699.  DOI: 10.1016/S1671-2927(00)8590
    Abstract ( )   PDF in ScienceDirect  
    The Food and Agriculture Organization is developing a concept based multilingual vocabulary management tool to manage thesauri, authority lists and glossaries expressed as concept schemes ready to be used in a linked data environment. In this paper, we described the evolution of the AGROVOC thesaurus to AGROVOC Concept Scheme based on OWL (web ontology language) model and now shifting to SKOS (simple knowledge organization system) model. The paper explained why and how it evolved highlighting the key differences between different models. The system architecture and significant set of features available in the VocBench was discussed in the paper.
    Construction of the Ontology-Based Agricultural Knowledge Management System
    ZHENG Ye-lu, QIAN Ping, LI Ze
    2012, 11(5): 700-709.  DOI: 10.1016/S1671-2927(00)8591
    Abstract ( )   PDF in ScienceDirect  
    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.
    Dictionary, Thesaurus or Ontology? Disentangling Our Choices in the Semantic Web Jungle
    Armando Stellato
    2012, 11(5): 710-719.  DOI: 10.1016/S1671-2927(00)8592
    Abstract ( )   PDF in ScienceDirect  
    The Semantic Web seems finally close to maintaining its promise about a real world-wide graph of interconnected resources. The SPARQL query language and protocols and the Linked Open Data initiative have laid the way for endless data endpoints sparse around the globe. However, for the Semantic Web to really happen, it does not suffice to get billions of triples out there: these must be shareable, interlinked and conform to widely accepted vocabularies. While more and more data are converted from already available large knowledge repositories of companies and organizations, the question whether these should be carefully converted to semantically consistent ontology vocabularies or find other shallow representations for their content naturally arises. The danger is to come up with massive amounts of useless data, a boomerang which could result to be contradictory for the success of the web of data. In this paper, I provide some insights on common problems which may arise when porting huge amount of existing data or conceptual schemes (very common in the agriculture domain) to resource description framwork (RDF), and will address different modeling choices, by discussing in particular the relationship between the two main modeling vocabularies offered by W3C: OWL and SKOS.
    Review on the Work of Agriculture Ontology Research Group
    SU Xiao-lu, LI Jing, MENG Xian-xue, WANG Yi-qian
    2012, 11(5): 720-730.  DOI: 10.1016/S1671-2927(00)8593
    Abstract ( )   PDF in ScienceDirect  
    This paper introduces efforts and achievements of Agriculture Ontology Service Research Group of Agricultural Information Institute of Chinese Academy of Agriculture Sciences in last 10 years. It summarizes the research on ontology construction methodology, ontology management system, ontology application and etc.
    A Review and Prospects on Collaborative Ontology Editing Tools
    XIAN Guo-jian, ZHAO Rui-xue
    2012, 11(5): 731-740.  DOI: 10.1016/S1671-2927(00)8594
    Abstract ( )   PDF in ScienceDirect  
    Building ontology is a fundamental but also hard work. Collaborative ontology editing tools can make ontology development more efficiently. In this paper, the important features of collaborative ontology development were analyzed, and several tools such as AGROVOC Concept Server Workbench (ACSW), Collaborative Protégé and WebProtégé were studied. Besides, some comparisons among them from several aspects were made and some prospects for the further improvement of these tools were given. Finally, we show it is a good way to build agricultural ontology with these tools collaboratively and simultaneously.
    SECTION 2: Theory, Technology and Method
    Ontology Engineering and Knowledge Services for Agriculture Domain
    Asanee Kawtrakul
    2012, 11(5): 741-751.  DOI: 10.1016/S1671-2927(00)8595
    Abstract ( )   PDF in ScienceDirect  
    This paper presents a knowledge service system for the domain of agriculture. Three key issues for providing knowledge services are how to improve the access of unstructured and scattered information for the non-specialist users, how to provide adequate information to knowledge workers and how to provide the information requiring highly focused and related information. Cyber-Brain has been designed as a platform that combines approaches based on knowledge engineering and language engineering to gather knowledge from various sources and to provide the effective knowledge service. Based on specially designed ontology for practical service scenarios, it can aggregate knowledge from Internet, digital archives, expert, and other resources for providing one-stop-shop knowledge services. The domain specific and task oriented ontology also enables advanced search and allows the system ensures that knowledge service could improve the user benefit. Users are presented with the necessary information closely related to their information need and thus of potential high interest. This paper presents several service scenarios for different end-users and reviews ontology engineering and its life cycle for supporting AOS (Agricultural Ontology Services) Vocbench which is the heart of knowledge services in agriculture domain.
    Agricultural Ontology Based Feature Optimization for Agricultural Text Clustering
    SU Ya-ru, WANG Ru-jing, CHEN Peng, WEI Yuan-yuan, LI Chuan-xi
    2012, 11(5): 752-759.  DOI: 10.1016/S1671-2927(00)8596
    Abstract ( )   PDF in ScienceDirect  
    Feature optimization is important to agricultural text mining. Usually, the vector space model is used to represent text documents. However, this basic approach still suffers from two drawbacks: the curse of dimension and the lack of semantic information. In this paper, a novel ontology-based feature optimization method for agricultural text was proposed. First, terms of vector space model were mapped into concepts of agricultural ontology, which concept frequency weights are computed statistically by term frequency weights; second, weights of concept similarity were assigned to the concept features according to the structure of the agricultural ontology. By combining feature frequency weights and feature similarity weights based on the agricultural ontology, the dimensionality of feature space can be reduced drastically. Moreover, the semantic information can be incorporated into this method. The results showed that this method yields a significant improvement on agricultural text clustering by the feature optimization.
    Constructing the Ontology for Modeling the Fish Production in Pearl River Basin
    HE Qi-yun, ZHENG Ye-lu, XU Jian-ning
    2012, 11(5): 760-768.  DOI: 10.1016/S1671-2927(00)8597
    Abstract ( )   PDF in ScienceDirect  
    This paper puts forward a construction method based on ontology for the Pearl River Basin fish production, to facilitate the domain knowledge analysis and information retrieval. By converting the concepts and terms in domain ordinally, the fish production ontology was constructed with the definition of classes, properties, instances, and relationships. The developed ontology model of the fish production knowledge is proposed and applied in the system of fish diseases diagnosis primarily. The research lays the semantic foundation for the further efficient knowledge management and practical application.
    World-Wide Semantic Web of Agriculture Knowledge
    Dickson Lukose
    2012, 11(5): 769-774.  DOI: 10.1016/S1671-2927(00)8598
    Abstract ( )   PDF in ScienceDirect  
    The rapid increase in the publication of knowledge bases as linked open data (LOD) warrants serious consideration from all concerned, as this phenomenon will potentially scale exponentially. This paper will briefly describe the evolution of the LOD, the emerging world-wide semantic web (WWSW), and explore the scalability and performance features of the service oriented architecture that forms the foundation of the semantic technology platform developed at MIMOS Bhd., for addressing the challenges posed by the intelligent future internet. This paper concludes with a review of the current status of the agriculture linked open data.
    From Web Resources to Agricultural Ontology: a Method for Semi-Automatic Construction
    WEI Yuan-yuan, WANG Ru-jing, HU Yi-min, WANG Xue
    2012, 11(5): 775-783.  DOI: 10.1016/S1671-2927(00)8599
    Abstract ( )   PDF in ScienceDirect  
    In recent years, with the rapid development of information science, ontology becomes a popular research topic in the fields of knowledge engineering and information management. The reason for ontology being so popular is in large part due to what they promise: a shared and common understanding of some domain that can be communicated across people and computers. In the field of agriculture, FAO has started up the Agricultural Ontology Service (AOS) study project since 2001, AOS aims at providing knowledge service by agricultural domain ontology, it is the new seedtime for agricultural information service. However, establishing the ontology necessitates a great deal of expert assistance; manually setting it up would entail a lot of time, not to mention that there are only a handful of experts available. For this reason, using automatic technology to construct the ontology is a subject worth pursuing. A semi-automatic construction method for agricultural professional ontology from web resources is presented in this paper. For semi-structured web pages, the method automatically extracted and stored structured data through a program, built pattern mapping between relational database and ontology through human-computer interaction, and automatically generated a preliminary ontology, finally completed checking and refining by domain experts. The method provided a viable approach for ontology construction based on network resources in the actual work.
    Structured AJAX Data Extraction Based on Agricultural Ontology
    LI Chuan-xi, SU Ya-ru, WANG Ru-jing, WEI Yuan-yuan, HUANG He
    2012, 11(5): 784-791.  DOI: 10.1016/S1671-2927(00)8600
    Abstract ( )   PDF in ScienceDirect  
    More web pages are widely applying AJAX (Asynchronous JavaScript XML) due to the rich interactivity and incremental communication. By observing, it is found that the AJAX contents, which could not be seen by traditional crawler, are well-structured and belong to one specific domain generally. Extracting the structured data from AJAX contents and annotating its semantic are very significant for further applications. In this paper, a structured AJAX data extraction method for agricultural domain based on agricultural ontology was proposed. Firstly, Crawljax, an open AJAX crawling tool, was overridden to explore and retrieve the AJAX contents; secondly, the retrieved contents were partitioned into items and then classified by combining with agricultural ontology. HTML tags and punctuations were used to segment the retrieved contents into entity items. Finally, the entity items were clustered and the semantic annotation was assigned to clustering results according to agricultural ontology. By experimental evaluation, the proposed approach was proved effectively in resource exploring, entity extraction, and semantic annotation.
    Fishery Web Service Composition Method Based on Ontology
    YU Qing-mei, WANG Lan, HUANG Dong-mei
    2012, 11(5): 792-799.  DOI: 10.1016/S1671-2927(00)8601
    Abstract ( )   PDF in ScienceDirect  
    Various fishery information systems have been developed in different times and on different platforms. Web service application composition is crucial in the sharing and integration of fishery data and information. In the present paper, a heuristic web service composition method based on fishery ontology is presented, and the proposed web services are described. Ontology reasoning capability was applied to generate a service composition graph. The heuristic function was introduced to reduce the searching space. The experimental results show that the algorithm used considers the services semantic similarity and adjusts web service composition plan by dynamically relying on the empirical data.
    An Ontology-Based Information Retrieval Model for Vegetables E-Commerce
    TAO Teng-yang, ZHAO Ming
    2012, 11(5): 800-807.  DOI: 10.1016/S1671-2927(00)8602
    Abstract ( )   PDF in ScienceDirect  
    With the rapid increment of the information on the web, traditional information retrieval based on the keywords is far from user’s satisfaction in recall and precision. In order to improve the recall ratio and the precision radio of IR engine in the vegetables e-commerce, an information retrieval model based on the vegetables e-commerce ontology is presented in this paper, vegetables e-commerce ontology was constructed by gathering and the analyzing vegetables e-commerce domain information on the web. The vegetables e-commerce ontology is composed of some kinds of vegetable classes and hierarchy relationship of vegetables classes. In the process of information retrieval, domain ontology helps to index information and information inference. An ontology-based information retrieval model is implemented, and which has more functions than the keyword-based web information retrieval engines. The experiment results show that the recall ratio and the precision ratio of ontology-based information retrieval model are higher than that of the information retrieval engine based on keyword at a certain extent.
    SECTION 3: Application
    Large-Scale Ontology Development and Agricultural Application Based on Knowledge Domain Framework
    MENG Xian-xue, SU Xiao-lu, HU Hai-yan, WANG Yi-qian
    2012, 11(5): 808-822.  DOI: 10.1016/S1671-2927(00)8603
    Abstract ( )   PDF in ScienceDirect  
    The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management - the knowledge domain framework (KDF), and introduces an integrated development environment (IDE) named large-scale ontology development environment (LODE), which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the principle of knowledge domain framework and LODE was described briefly.
    Design and Implementation of the ZH/EN Bilingual Retrieval System Based on the CAT/AGROVOC Mapping
    SUN Wei, Ahsan Morshed, Johannes Keizer, Stefano Anibald, LI Nan, LIU Jia-yi
    2012, 11(5): 823-830.  DOI: 10.1016/S1671-2927(00)8604
    Abstract ( )   PDF in ScienceDirect  
    For the users’ convenience of accessing the AGRIS resources quickly and using them fully, the paper decomposes the structure of AGRIS Search net, analyzes the users’ requirement met for conducting a bilingual (ZH/EN) retrieval, the system function extensions based on AGRIS English retrieval system and the key issues which the core function module should resolve. Derived by the application requirement, the paper also puts forward to a bilingual retrieval model on the basis of CAT/AGROVOC mapping, designs and realizes the ZH/EN bilingual retrieval prototype system.
    Study of Ontology-Based Swine Diagnosis Technology
    CUI Yun-peng, SU Xiao-lu, LIU Shi-hong
    2012, 11(5): 831-838.  DOI: 10.1016/S1671-2927(00)8605
    Abstract ( )   PDF in ScienceDirect  
    The computer swine disease diagnosis is an important tool for swine farming industry, but the traditional expert system cannot meet the requirement of practical application. To improve the situation, a swine disease ontology is constructed, which can model the knowledge of swine disease diagnosis into a concept system, and a mechanism that can save the ontology into relational database is established, further more a computer system is developed to implement ontologybased swine disease diagnosis, so make the diagnosis results extended and more precise.
    A Dairy Industry Information Cooperative Service System Based on a Production Process Ontology
    XU Yong, Luke Bergmann, WANG Zhi-qiang, WANG Jian
    2012, 11(5): 839-848.  DOI: 10.1016/S1671-2927(00)8606
    Abstract ( )   PDF in ScienceDirect  
    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
    HU Yi-min, SONG Liang-tu, WEI Yuan-yuan, HUANG He, WANG Xue
    2012, 11(5): 849-857.  DOI: 10.1016/S1671-2927(00)8607
    Abstract ( )   PDF in ScienceDirect  
    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.
    Location Service Information Supporting System Based on Ontology
    HUANG Dong-mei, FANG Qian, YU Qing-mei
    2012, 11(5): 858-864.  DOI: 10.1016/S1671-2927(00)8608
    Abstract ( )   PDF in ScienceDirect  
    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.
    Research on Development of Agricultural Geographic Information Ontology
    HUANG Yong-qi, CUI Wei-hong, ZHANG Yang-jian, DENG Gao-yan
    2012, 11(5): 865-877.  DOI: 10.1016/S1671-2927(00)8609
    Abstract ( )   PDF in ScienceDirect  
    This paper first analyzes the reason that agricultural geographic information gives rise to semantic heterogeneity and solution thereof. Although OWL (web ontology language) is the standard of ontology representation language in semantic web, it is insufficient in representing spatial characteristics, especially spatial relationship. Consequently it is pointed out to build geo-ontology by virtue of three theories such as mereology, location theory and topology in this paper. This paper introduces mereology, location theory and topology, and then discusses how to adopt these three theories to build geo-ontology. The outcome of experiment shows that solution put forward by this paper is feasible.