Fishing has become a major threat to marine fishes. Effective conservation requires timely identification of vulnerable fish species. However, evaluation of extinction risk using conventional methods is difficult due to limitations in data that should be gathered about the fish species and required by such methods. This paper presents a fuzzy expert system that integrates life history and ecological characteristics of marine fishes to estimate their intrinsic vulnerability. There are lots of general and special purpose expert systems that help society in a life particular sector. So, a professional one is selected and adapted for helping in marine wealth preservation. Finally, the proposed fuzzy expert system is used as a decision support tool in fishery management and marine conservation planning.
Abstract-In this paper we intends to build an expert system based on semantic web for online search using XML, to help users to find the desired software, and read about its features and specifications. The expert system saves user's time and effort of web searching or buying software from available libraries. Building online search expert system is ideal for capturing support knowledge to produce interactive on-line systems that provide searching details, situation-specific advice exactly like setting a session with an expert. Any person can access this interactive system from his web browser and get some questions answer in addition to precise advice which was provided by an expert. The system can provide some troubleshooting diagnose, find the right products; … Etc.The proposed system further combines aspects of three research topics (Semantic Web, Expert System and XML). Semantic web Ontology will be considered as a set of directed graphs where each node represents an item and the edges denote a term which is related to another term. Organizations can now optimize their most valuable expert knowledge through powerful interactive Web-enabled knowledge automation expert system. Online sessions emulate a conversation with a human expert asking focused questions and producing customized recommendations and advice. Hence, the main powerful point of the proposed expert system is that the skills of any domain expert will be available to everyone.
Most computer technologies focus on end users and their problem solving activities rather than machine. This denotes an evolutionary trend even for recent technologies which include semantic web and much closer to final users. Hence, building a virtual guide for students or visitors based on semantic web using XML is targeted. In this paper, premium services for students and visitor in Taif University are introduced with high professionalism level. Furthermore, innovative solutions to improve these services at faculty and university levels are demonstrated. Also, a virtual image in three-dimensional technique is used in the paper. The proposed system provides two main kinds of service. The first is called Open Navigation Service, which provides a user with free tour in university buildings. The second is called Identify Way, which provide a user with start and end visiting points that may be considered university gate or building. In addition, the proposed system combines three important research topics; Semantic Web, Ontology, and XML.
Abstract-This paper introduces an expert system which demonstrates a new method for accurate estimation of building house cost. This system is simple and decreases the time, the effort, and the money of its beneficiaries. In addition, design and implementation of the proposed expert system are introduced. CLIPS 6.0 and C# are used in implementation phase. Also, this expert system is programmed to be in a standalone package with a platform independency. Furthermore, the developed expert system is tested under several real cases. Finally, an initial evaluation of this expert system is carried out and a positive feedback is received from user's samples, which makes it robust and efficient.
Abstract-A major shortcoming of content-based approaches exists in the representation of the user model. Content-based approaches often employ term vectors to represent each user's interest. In doing so, they ignore the semantic relations between terms of the vector space model in which indexed terms are not orthogonal and often have semantic relatedness between one another.In this paper, we improve the representation of a user model during building user model in content-based approaches by performing these steps. First is the domain concept filtering in which concepts and items of interests are compared to the domain ontology to check the relevant items to our domain using ontology based semantic similarity. Second, is incorporating semantic content into the term vectors. We use word definitions and relations provided by WordNet to perform word sense disambiguation and employ domain-specific concepts as category labels for the semantically enhanced user models. The implicit information pertaining to the user behavior was extracted from click stream data or web usage sessions captured within the web server logs. Also, our proposed approach aims to update user model, we should analysis user's history query keywords. For a certain keyword, we extract the words which have the semantic relationships with the keyword and add them into the user interest model as nodes according to semantic relationships in the WordNet.
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