Hai Zhuge

Communities and Emerging Semantics in Semantic Link Network: Discovery and Learning

The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the semantic link network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested.

China's e-science knowledge grid environment

The Internet and World Wide Web are milestones in the history of information sharing. Scientists are increasingly relying on them to support their research. Knowledge is the basis of realizing intelligent services. The knowledge grid is a mechanism that can synthesize knowledge from data through mining and reference methods and enable search engines to make references, answer questions, and draw conclusions from masses of data. The knowledge grid infrastructure supports e-science through a set of relevant application services and semantic resources. We have developed a semantic-link-making tool for users to conveniently describe their understandings of provided resources and background knowledge.

Semantic linking through spaces for cyber-physical-socio intelligence: A methodology

Humans consciously and subconsciously establish various links, emerge semantic images and reason in mind, learn linking effect and rules, select linked individuals to interact, and form closed loops through links while co-experiencing in multiple spaces in lifetime. Machines are limited in these abilities although various graph-based models have been used to link resources in the cyber space. The following are fundamental limitations of machine intelligence: (1) machines know few links and rules in the physical space, physiological space, psychological space, socio space and mental space, so it is not realistic to expect machines to discover laws and solve problems in these spaces; and, (2) machines can only process pre-designed algorithms and data structures in the cyber space. They are limited in ability to go beyond the cyber space, to learn linking rules, to know the effect of linking, and to explain computing results according to physical, physiological, psychological and socio laws. Linking various spaces will create a complex space - the Cyber-Physical-Physiological-Psychological-Socio-Mental Environment CP^3SME. Diverse spaces will emerge, evolve, compete and cooperate with each other to extend machine intelligence and human intelligence. From multi-disciplinary perspective, this paper reviews previous ideas on various links, introduces the concept of cyber-physical society, proposes the ideal of the CP^3SME including its definition, characteristics, and multi-disciplinary revolution, and explores the methodology of linking through spaces for cyber-physical-socio intelligence. The methodology includes new models, principles, mechanisms, scientific issues, and philosophical explanation. The CP^3SME aims at an ideal environment for humans to live and work. Exploration will go beyond previous ideals on intelligence and computing.

A knowledge flow model for peer-to-peer team knowledge sharing and management

Abstract To realize effective knowledge sharing in teamwork, this paper proposes a knowledge flow model for peer-to-peer knowledge sharing and management in cooperative teams. The model consists of the concepts, rules and methods about the knowledge flow, the knowledge flow process model, and the knowledge flow engine. A reference model for coordinating the knowledge flow process with the workflow process is suggested to provide an integrated approach to model teamwork process. We also discuss the peer-to-peer knowledge-sharing paradigm in large-scale teams and propose the approach for constructing a knowledge flow network from the corresponding workflow. The proposed model provides a new way to model and manage teamwork processes.

A knowledge grid model and platform for global knowledge sharing

Abstract This paper proposes a knowledge grid model for sharing and managing globally distributed knowledge resources. The model organizes knowledge in a three-dimensional knowledge space, and provides a knowledge grid operation language, KGOL. Internet users can use the KGOL to create their knowledge grids, to put knowledge to them, to edit knowledge, to partially or wholly open their grids to all or some particular grids, and to get the required knowledge from the open knowledge of all the knowledge grids. The model enables people to conveniently share knowledge with each other when they work on the Internet. A software platform based on the proposed model has been implemented and used for knowledge sharing in research teams.

A timed workflow process model

Abstract An internet-based workflow management system (WfMS) enables business participants to work co-operatively at sites belonging to different time zones. Time-related factors have to be incorporated into the traditional workflow processes so as to adapt to the globally distributed applications. This paper proposes a timed workflow process model through incorporating the time constraints, the duration of activities, the duration of flow, and the activity distribution with respect to the multiple time axes into the conventional workflow processes. The model provides an approach for temporal consistency checking during both build-time and run-time. The proposed model and approach provide a vehicle for global business process modeling, planning and monitoring.

Interactive semantics

Much research pursues machine intelligence through better representation of semantics. What is semantics? People in different areas view semantics from different facets although it accompanies interaction through civilization. Some researchers believe that humans have some innate structure in mind for processing semantics. Then, what the structure is like? Some argue that humans evolve a structure for processing semantics through constant learning. Then, how the process is like? Humans have invented various symbol systems to represent semantics. Can semantics be accurately represented? Turing machines are good at processing symbols according to algorithms designed by humans, but they are limited in ability to process semantics and to do active interaction. Super computers and high-speed networks do not help solve this issue as they do not have any semantic worldview and cannot reflect themselves. Can future cyber-society have some semantic images that enable machines and individuals (humans and agents) to reflect themselves and interact with each other with knowing social situation through time? This paper concerns these issues in the context of studying an interactive semantics for the future cyber-society. It firstly distinguishes social semantics from natural semantics, and then explores the interactive semantics in the category of social semantics. Interactive semantics consists of an interactive system and its semantic image, which co-evolve and influence each other. The semantic worldview and interactive semantic base are proposed as the semantic basis of interaction. The process of building and explaining semantic image can be based on an evolving structure incorporating adaptive multi-dimensional classification space and self-organized semantic link network. A semantic lens is proposed to enhance the potential of the structure and help individuals build and retrieve semantic images from different facets, abstraction levels and scales through time.

A scalable P2P platform for the knowledge grid

The knowledge grid needs to operate with a scalable platform to provide large-scale intelligent services. A key function of such a platform is to efficiently support various complex queries in a dynamic large-scale network environment. This paper proposes a platform to support index-based path queries by incorporating a semantic overlay with an underlying structured P2P network that provides object location and management services. Various distributed indexing structures can be dynamically formed by publishing, semantic objects as indexing nodes. Queries are forwarded along the chains of semantic object pointers to search for objects. We investigate the deployment of a scalable distributed trie index for broadcast queries on key strings, propose a decentralized load balancing method for solving the problem of uneven load distribution incurred by heterogeneity of loads and node capacities and by the distributed trie index, and give an approach for improving the availability of the semantic overlay and its trie index. Experiments demonstrate the scalability of the proposed platform.

Future interconnection environment

The emergence of the Web provided an unprecedented AI research and application platform. By providing access to human-readable content stored in any computer connected to the Internet, it revolutionized business, scientific research, government, and public information services around the globe. Networks pervade nature, society, and virtual worlds, giving structure and function to a variety of resources and behaviors. Discovering the rules that govern the future interconnection environment is a major challenge. The China Knowledge Grid Research Group, is exploring the operating principles of this future interconnection environment.

Peer-to-Peer in Metric Space and Semantic Space

This paper first proposes three improved gossip mechanisms by mapping links into metric space and dynamically adapting the number of selected neighbors to disseminate messages. Experiments and comparisons show that these mechanisms can improve the performance of gossip in peer-to-peer (P2P) networks. This is the effect of mapping a network into a metric space that differentiates nodes and links according to linking characteristics and controlling local information flow with knowing such differences. A further study about query routing on P2P semantic link network shows that mapping a network into a semantic space can also improve the performance. An intrinsic rule is found by experimental comparisons and analysis: the performance of a P2P network can be improved by designing an appropriate mapping from the network into metric space or semantic space. A general framework for networking with metric space and semantic space is suggested