606471
A dynamic scalable service model for SIP-based video conference
As an extensible signaling protocol, SIP (session initiation protocol) can be applied in developing video conference system. Traditionally, for SIP-based centralized video conference system, conferencing scale is limited by both the capability of conference server and the availability of bandwidth. The paper focuses on how to keep conferencing when the number of conference users increases. Based on the study of the SIP protocol, we analyze the drawback of the existing video conference model, and propose a dynamic scalable service model for SIP-based video conference. By this model, the extra service requests can be transferred and served in the cooperated conference servers. The paper presents the conferencing control policy of the model in detail. We developed a prototype of video conference system based on the above model. Experimental results show this service model works well.
33955645
A Dynamic Scalable Video Conference System Based on SIP
The Session Initiation Protocol (SIP) provides powerful and flexible signaling capabilities for building video conferencing services. Traditionally, for SIP-based centralized video conference systems, the conferencing scale is mainly limited by both the capability of conference server and the availability of bandwidth. In this paper, our design focuses on how to provide dynamic scalability for the SIP-based video conferencing system when the number of conference users increases continually. Based on the study of the SIP protocol and the existing video conferencing models, we propose a dynamic scalable service model that can support to dynamically increase the number of conference servers without negative influence on the stability of system. This enables the extra service requests to be transferred and served in the cooperated conference servers. The paper also addresses the SIP-enabled conferencing flows based on the model in detail. We developed a prototype of video conference system based on the proposed model. Experimental results demonstrate the validity of this service model.
4744078
X-warehouse: building query pattern-driven data
In this paper, we propose an approach to materialize XML data warehouses based on the frequent query patterns discovered from historical queries issued by users. The schemas of integrated XML documents in the warehouse are built using these frequent query patterns represented as Frequent Query Pattern Trees (FreqQPTs). Using hierarchical clustering technique, FreqQPTs are clustered and merged to produce a specified number of integrated XML documents for actual data feeding. Maintenance issue of the data warehouse is also treated in this paper.
24869938
Network Intrusion Active Defense Model Based on Artificial Immune System
Based on artificial immune theory, a new model of active defense for analyzing the network intrusion is presented. Dynamically evaluative equations for self, antigen, immune tolerance, mature-lymphocyte lifecycle and immune memory are presented. The concepts and formal definitions of immune cells are given, the hierarchical and distributed management framework of the proposed model are built. Furthermore, the idea of biology immunity is applied for enhancing the self-adapting and self-learning ability to adapt continuously variety environments. The experimental results show that the proposed model has the features of real-time processing, self-adaptively, and diversity, thus providing a good solution for network surveillance.
16727234
Extraction and mining of an academic social network
This paper addresses several key issues in extraction and mining of an academic social network: 1) extraction of a researcher social network from the existing Web; 2) integration of the publications from existing digital libraries; 3) expertise search on a given topic; and 4) association search between researchers. We developed a social network system, called ArnetMiner, based on proposed methods to the above problems. In total, 448,470 researcher profiles and 981,599 publications were extracted/integrated after the system having been in operation for two years. The paper describes the architecture and main features of the system. It also briefly presents the experimental results of the proposed methods.
293156
A Discriminative Approach to Topic-Based Citation Recommendation
In this paper, we present a study of a novel problem, i.e. topic-based citation recommendation, which involves recommending papers to be referred to. Traditionally, this problem is usually treated as an engineering issue and dealt with using heuristics. This paper gives a formalization of topic-based citation recommendation and proposes a discriminative approach to this problem. Specifically, it proposes a two-layer Restricted Boltzmann Machine model, called RBM-CS, which can discover topic distributions of paper content and citation relationship simultaneously. Experimental results demonstrate that RBM-CS can significantly outperform baseline methods for citation recommendation.
11753174
Discover Gene Specific Local Co-regulations Using Progressive Genetic Algorithm
The problem of gene specific co-regulation discovery is that, for a particular gene of interest, identify its closely coregulated genes and the associated subsets of experimental conditions in which such co-regulations occur. The coregulations are local in the sense that they occur in some subsets of full experimental conditions. In this paper, we propose an innovative method for finding gene specific coregulations using genetic algorithm (GA). Two novel ad hoc GAs, the single-stage and two-stage progressive GA, are proposed. They are called progressive because the initial population for the GA in a window position inherits the top-ranked individuals obtained in the preceding window position, enabling them to achieve better accuracy than the nonprogressive algorithm. Experimental results with real-life gene expression data demonstrate the efficiency and effectiveness of our technique in discovering gene specific coregulations