Ontology Engineering and Knowledge Services for Agriculture Domain

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.

From Web Resources to Agricultural Ontology:a Method for Semi-Automatic Construction

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.

Review on the Work of Agriculture Ontology Research Group

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.

Capability-based context ontology modeling and reasoning for C^4ISR communication

Modeling and reasoning on domain contexts play a key role for adding intelligence to communication services, and the approach of capability-based requirement engineering ensures the scientificity and accuracy of requirement elicitation. This paper presents a capability-based context ontology modeling approach for command and control, communication, computer, intelligence, surveillance and reconnaissance（C^4ISR） communication. Primarily, a capability-based C^4ISR communication meta-concept model and a C^4ISR communication context meta-ontology are constructed. The context ontology is established under the constraints of the C^4ISR communication context meta-ontology, and furthermore, algorithms are proposed to support context reasoning based on description logic. A case study is presented to demonstrate applicability of the proposed method.

AN IMPROVED HYBRID SEMANTIC MATCHING ALGORITHM WITH LEXICAL SIMILARITY

In this paper, we proposed an improved hybrid semantic matching algorithm combining Input/Output (I/O) semantic matching with text lexical similarity to overcome the disadvantage that the existing semantic matching algorithms were unable to distinguish those services with the same I/O by only performing I/O based service signature matching in semantic web service discovery techniques. The improved algorithm consists of two steps, the first is logic based I/O concept ontology matching, through which the candidate service set is obtained and the second is the service name matching with lexical similarity against the candidate service set, through which the final precise matching result is concluded. Using Ontology Web Language for Services (OWL-S) test collection, we tested our hybrid algorithm and compared it with OWL-S Matchmaker-X (OWLS-MX), the experimental results have shown that the proposed algorithm could pick out the most suitable advertised service corresponding to user's request from very similar ones and provide better matching precision and efficiency than OWLS-MX.