38534403
Effective Content Tracking for Digital Rights Management in Digital Libraries
A usual way for content protection of digital libraries is to use digital watermarks and a DRM-based access-control environment. These methods, however, have limitations. Digital watermarks embedded in digital content could be removed by malicious users via post-processing, whereas DRM-based access-control solutions could be hacked. In this paper, we introduce a content tracking mechanism that we have built for multimedia-content near-replica detection as the second line of defense. The integrated framework aims to detect unlawful copyright infringements on the Internet, and combines the strengths of static rights enforcement and dynamic illegal content tracking. The issues of accuracy and huge computation cost in copy detection have been addressed by the introduced content-based techniques. Our experiments demonstrate the efficacy of proposed copy detector.
31426414
An Enhanced DHCP-based Infrastructure for Intranet Management
30494509
Translating unknown cross-lingual queries in digital libraries using a web-based approach
94229
Translating unknown queries with web corpora for cross-language information retrieval
It is crucial for cross-language information retrieval (CLIR) systems to deal with the translation of unknown queries due to that real queries might be short. The purpose of this paper is to investigate the feasibility of exploiting the Web as the corpus source to translate unknown queries for CLIR. We propose an online translation approach to determine effective translations for unknown query terms via mining of bilingual search-result pages obtained from Web search engines. This approach can alleviate the problem of the lack of large bilingual corpora, translate many unknown query terms, provide flexible query specifications, and extract semantically-close translations to benefit CLIR tasks -- especially for cross-language Web search.
21909317
Generating Concept Hierarchies from Text for Intelligence Analysis
It is important to automatically extract key information from sensitive text documents for intelligence analysis. Text documents are usually unstructured and information extraction from texts usually focuses on named entity extraction that is insufficient to reflect the concepts contained within documents. Other research on texts focuses on classifying the whole text into categories. However, texts might be diverse in subjects and suffer from classification accuracy. In this paper, our goal is to present a feasible approach to extract relevant information from texts and organize into concept hierarchies with the help of Web corpora. The approach is designed considering the need of information intelligence and the adaptation to different application domains.
14678674
Enhanced intranet management in a DHCP-enabled environment
The DHCP (dynamic host configuration protocol) is widely deployed in resource allocation and intranet management. However the DHCP mechanism is not mandatory and the DHCP server can neither force DHCP clients to release their leases, nor enforce cooperation from externally configured hosts that are DHCP-unaware. Although new DHCP options such as DHCP reconfigure extension have been proposed, the basic problems inherent in DHCP mechanism cannot be solved without first strengthening its operations. In the paper a DHCP-based infrastructure for intranet management is proposed by combining the resource allocation functions of the DHCP server with the packet filtering features of MAC (Medium Access Control) bridges such as Ethernet switches and wireless access points. DHCP clients and DHCP-unaware hosts that do not abide by the DHCP mechanism or our management policy will be denied network accesses by MAC bridges. Resource allocation and access control can be integrated and local configuration conflicts can be reduced to the minimum.
15835310
An Intuitive Formal Approach to Dynamic Workflow Modeling and Analysis
The increasing dynamics and the continuous changes of business processes raise a challenge to the research and implementation of workflows. The significance of applying formal approaches to the modeling and analysis of workflows has been well recognized and many such approaches have been proposed. However, these approaches require users to master considerable knowledge of the particular formalisms, which impacts the application of these approaches on a larger scale. This paper presents a new formal, yet intuitive approach for the modeling and analysis of workflows, which attempts to overcome the above problem. In addition to the abilities of supporting workflow validation and enactment, this new approach possesses the distinguishing feature of allowing users who are not proficient in formal methods to build up and dynamically modify the workflow models that address their business needs.
1151748
Scalable and Efficient Data Streaming Algorithms for Detecting Common Content in Internet Traffic
Recent research on data streaming algorithms has provided powerful tools to efficiently monitor various characteristics of traffic passing through a single network link or node. However, it is often desirable to perform data streaming analysis on the traffic aggregated over hundreds or even thousands of links/nodes, which will provide network operators with a holistic view of the network operation. Shipping raw traffic data to a centralized location (i.e., “raw aggregation”) for streaming analysis is clearly not a feasible approach for a large network. In this paper, we propose a set of novel distributed data streaming algorithms that allow scalable and efficient monitoring of aggregated traffic without the need for raw aggregation. Our algorithms target the specific network monitoring problem of finding common content in the Internet traffic traversing several nodes/links, which has applications in network-wide intrusion detection, early warning for fast propagating worms, and detection of hot objects and spam traffic. We evaluate our algorithms through extensive simulations and experiments on traffic traces collected from a tier-1 ISP. The experimental results demonstrate that our algorithms can effectively detect common content in the traffic traversing across a large network.
11520313
Linear Vertex Arboricity, Independence Number and Clique Cover Number
The linear vertex-arboricity of a graph G is defined to the minimum number of subsets into which the vertex-set G can be partitioned so that every subset induces a linear forest. In this paper, we give the upper and lower bounds for sum and product of linear vertex-arboricity with independence number and with clique cover number respectively. All of these bounds are sharp.
12301513
A Comparative Study of Skin-Color Models
In this paper, we report the results of a comparative study on skin-color models generally used for facial region location. These include two 2D Gaussian models developed in normalized RGB and HSV color spaces respectively, a 1D lookup table model of hue histogram, and an adaptive 3D threshold box model. Also, we present a new model – called “adaptive hue lookup table”. The model is developed by introducing the so-called “Continuously Adaptive Mean Shift” (Camshift) technique into a traditional hue lookup table method. With the introduction of Camshift, the lookup table is able to adaptively adjust its parameters to fit the illumination conditions of different test images. In the experiments reported here, we compare the proposed method with the four typical skin-color filters in the scenarios of different human races and illuminations. The obtained results indicate that the proposed method reaches the best balance between false detection and detect rate.
14843520
Deriving knowledge from figures for digital libraries
Figures in digital documents contain important information. Current digital libraries do not summarize and index information available within figures for document retrieval. We present our system on automatic categorization of figures and extraction of data from 2-D plots. A machine-learning based method is used to categorize figures into a set of predefined types based on image features. An automated algorithm is designed to extract data values from solid line curves in 2-D plots. The semantic type of figures and extracted data values from 2-D plots can be integrated with textual information within documents to provide more effective document retrieval services for digital library users. Experimental evaluation has demonstrated that our system can produce results suitable for real-world use.