| More and more resource exists on Internet and this makes possible to improve the quality of resource sharing and task collaboration on Internet. But, the increase of resource amount and categories adds the complexity of managing and utilizing resource. How to find the required resource, how to transfer resource quickly and accurately, these are nontrivial functions in current web applications. Semantic technology and social computing provide some new ways to realize web resource shared on application layer.Base on semantic computing and social computing, this dissertation aims at providing some new methods to enhance Web resource sharing and interoperability. We firstly analyze web resource's characteristics and put forward the concept of web knowledge resource. This concept explains what web knowledge resource is and why most web resource can be considered as knowledge resource. Then to realize the widerly, high quality web resource sharing, a knowledge communication framework is projected, which is to deliver web knowledge resource by knowledge engineering and communication technology. In knowledge communication framework, the mechanism for connecting different resource by semantic content, effectively organizing and managing resource, intelligent communication protocol, constitute the infrastructure of knowledge communication. Focusing on the three core problems, we introduce some new methods and Content awareness and context awareness are these methods'medium objectives and resource widely shared is their final goal. The main contributions and innovations of our work include the following:â‘ After deeply analyzing the mechanism for resource interoperability, we build multi-dimensions web resource ontology model RSM for resource semantic interaction. RSM includes metadata-based unification resource representation, semantic relationship and resource collaboration. In RSM, knowledge collaboration ontology is set up that is composed of cognize process class and knowledge collaboration class. They can respectively describe the user's cognizing process and resource collaboration process. RSM could support high quality resource location and intelligent recommend on WWW.Another important notion about semantic interaction between heterogeneous resources is semantic relativity evaluation. We focus on OWL that is recommended by W3C and introduce an easy-to-use, flexible algorithm for computing semantic relativity between concepts in OWL, based on ontology structure and concepts'semantic relation, which does not need other lexical base such as WordNet, nor machine learning from quite large quantity of individuals. It just occurs in a domain ontology base. Because in DL, subsumption is an important relation, the detailed subsumption theories and computing lemma are given. According to these principles, we can deduce the subsumption subgraph and calculate their semantic similarity and then obtain their relativity degree by original ontology graph.â‘¡Community is one important structure in social network and web resource network. And it is one key structure for organizing web resource. We research community detection algorithms in macro view and self-organizing community formation in micro view. The work in macro view could help designing suitable micro self-organizing topology and the actions in micro world would influence the macro network structure.In macro view, we study overlapping community and dynamic community detection algorithms. There are some common problems in overlapping community research, such as lacking of suitable evaluation function, incapable of deciding suitable granularity community, computing performance and so on. This dissertation build a new overlapping community evaluation method that computes both community clustering degree and the overlapping degree. This function could calculate the structure quality for both disjoint community and overlapping community.Moreover. It can optimize the community granularity by controlling the overlapping degree.One new algorithm NHOC is proposed to detect overlapping or disjoint community. The difference between NHOC and current published algorithms is that NHOC utilizes the relationship of nodes'sharing neighbors, not nodes'direct interaction. Comparing it with overlapping algorithm CONGA, experiments show it can find more accurate community structure than CONGA, whether the real network has disjoint or overlapping communities.Community structure will change with time because social network is dynamic evolving. To find stable community in large social datasets that maybe have noise data, is one key problem. Different from current optimized dynamic community model algorithms, we introduce a graph transfer-based algorithm NDCD that computes history information and snapshot information. NDCD could detect community structure when the observed snapshot network is 0-1 (unweighted graph) graph or weighted graph. Experiments shows NDCD could discover the stable community whenever observed graph is 0-1 graph or weighted graph.In micro view, for autonomous community, we consider peer to peer modal as background because its sociality and widely applications on Internet. An expert-driven multi-semantic self-organized P2P semantic community model is built to resolve the two principle problems of resource organizing and management, which are how to possess enormous number of high quality shared resource, how to find the resource quickly and accurately. We set up Autonomic Semantic Community (ASC) model, design local domain-related trust function and self-evaluation function that takes requirement and owned resource two aspects into account to value one autonomous peer (AP). We also put forward a procedure to collaboratively elect expert APe and a Self-organized community formation algorithm --SoFA. In SoFA, APs gather its communication information and evaluate itself and other APs locally, build and dynamically adjust local topology, elect the domain expert APe and then an expert-driven ASC is established. Furthermore, we describe the dynamic changing of peers'routing table before or after that ASCs are formed. Experiment shows SoFA could not only adaptively optimize network to improve the efficiency of service discovery and routing, but also base on the synthesized trust degree to discriminate the low quality service peers and to keep them within limits.â‘¢Inspired by human's communication way, we proposed a kind of content and context awareness protocol (abbr. KC2A2P) base on knowledge to satisfy the intelligent knowledge communication. A common shared protocol ontology is built that includes content, context and act in order to not only guide the different protocol terms mapping but also provide an intelligent protocol encoding framework. To avoid unnecessary communication load, event calculus is used to build the axiom of communication cognition and three basic encoding rules are made that can adjust the message entity base on the application context. Furthermore, some experiments are given to show KC2A2P would improve the meaning delivery and even help to build trust relationship.Finally a knowledge communication test system"higher education resource sharing platform"is introduced and some tests results show that knowledge communication is one effective infrastructure for web resource sharing.
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