17665082
Generating Cross-lingual Concept Space from Parallel Corpora on the Web
The information available in languages other than English on the World Wide Web is increasing significantly. To cross language boundaries between different languages, dictionaries are the most typical tools. However, the general-purpose dictionary is less sensitive in genre and domain and it is impractical to manually construct tailored bilingual dictionaries or sophisticated multilingual thesauri for large applications. Corpus-based approaches, which do not have the limitation of dictionaries, provide a statistical translation model to cross the language boundary. The objective of this research work is to mine English/Chinese parallel documents automatically from the World Wide Web and generate a crosslingual concept space automatically for cross-lingual information retrieval. The alignment method is developed based on dynamic programming to identify the one-to-one Chinese and English title pairs for building parallel corpus. The Hopfield network is then employed to generate the cross-lingual concept space based on the statistical correlation analysis of the semantics (knowledge) embedded in the bilingual press release corpus. The research output consisted of a thesaurus-like, semantic network knowledge base, which can aid in semantics-based cross-lingual information management and retrieval.
17560673
Multi-document Summarization for Terrorism Information Extraction
Counterterrorism is one of the major challenges to the society. In order to flight again the terrorists, it is very important to have a through understanding of the terrorism incidents. However, it is impossible for a human to read all the information related to a terrorism incident because of the large volume of information. Summarization technique is urgently required for analysis of terrorism incident. In this work, we propose a multi-document summarization system to extract the critical information from terrorism incidents. News stories of a terrorism incident are organized into a hierarchical tree structure. Fractal summarization model is employed to generate a summary for all the news stories. Experimental results show that our system can effectively extract the most important information for the incident.
16530408
Searching behavior in peer-to-peer communities
The focus of this paper is the searching behavior in peer-to-peer (P2P) communities and in that context, will discuss potential for enhancement of the P2P protocol using searching behavior. Due to excessive network traffic, network scalability is a major P2P problem. The purpose of this paper is to study searching behavior by using log files and subsequently, will propose solutions to reduce the amount of redundant searching activities. In the current research, log data containing over 5 million query messages was collected over seven consecutive days using a Gnutella-based P2P program. The results of this study will be instrumental in providing ways to reduce existing problems with P2P network traffic.
13186184
Discovering event evolution graphs from newswires
In this paper, we propose an approach to automatically mine event evolution graphs from newswires on the Web. Event evolution graph is a directed graph in which the vertices and edges denote news events and the evolutions between events respectively, in a news affair. Our model utilizes the content similarity between events and incorporates temporal proximity and document distributional proximity as decaying functions. Our approach is effective in presenting the inside developments of news affairs along the timeline, which can facilitate users' information browsing tasks.
15850495
Automatic Summarization for Financial News Delivery on Mobile Devices
Christopher C. C. Yang and Fu Lee Wang Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China {yang, flwang}@se.cuhk.edu.hk ABSTRACT Wireless access with mobile devices is a promising addition to the WWW and traditional electronic business. Mobile devices provide convenience and portable access to the huge information space on the Internet. It is desire to access the most updated financial information through mobile devices in order to make critical and urgent decision for most of the investors. In this paper, we present a financial news delivery system on mobile devices based on the fractal summarization model. Fractal summarization is developed based on the fractal theory. It generates a brief skeleton of summary at the first stage, and the details of the summary on different levels of the document are generated on demands of users. Such interactive summarization reduces the computation load in comparing with the generation of the entire summary in one batch by the traditional summarization, which is ideal for wireless access.
6650274
Building parallel corpora by automatic title alignment using length-based and text-based approaches
Cross-lingual semantic interoperability has drawn significant attention in recent digital library and World Wide Web research as the information in languages other than English has grown exponentially. Cross-lingual information retrieval (CLIR) across different European languages, such as English, Spanish, and French, has been widely explored; however, CLIR across European languages and Oriental languages is still in the initial stage. To cross language boundary, corpus-based approach is promising to overcome the limitation of the knowledge-based and controlled vocabulary approaches but collecting parallel corpora between European language and Oriental language is not an easy task. Length-based and text-based approaches are two major approaches to align parallel documents. In this paper, we investigate several techniques using these approaches and compare their performances in aligning English and Chinese titles of parallel documents available on the Web.
6822991
An Integrated Pipeline of Decompression, Simplification and Rendering for Irregular Volume Data
Very large irregular-grid volume data sets are typically represented as tetrahedral mesh and require substantial disk I/O and rendering computation. One effective way to reduce this demanding resource requirement is compression. Previous research showed how rendering and decompression of a losslessly compressed irregular-grid data set can be integrated into a one-pass computation. This work advances the state of the art one step further by showing that a losslessly compressed irregular volume data set can be simplified while it is being decompressed and that simplification, decompression, and rendering can again be integrated into a pipeline that requires only a single pass through the data sets. Since simplification is a form of lossy compression, the on-the-fly volume simplification algorithm provides a powerful mechanism to dynamically create versions of a tetrahedral mesh at multiple resolution levels directly from its losslessly compressed representation, which also corresponds to the finest resolution level. In particular, an irregular-grid volume renderer can exploit this multi-resolution representation to maintain interactivity on a given hardware/software platform by automatically adjusting the amount of rendering computation that could be afforded, or performing so called time-critical rendering. The proposed tetrahedral mesh simplification algorithm and its integration with volume decompression and rendering has been successfully implemented in the Gatun system. Performance measurements on the Gatun prototype show that simplification only adds less than 5% of performance overhead on an average and with multi-resolution pre-simplification the end-to-end rendering delay indeed decreases in an approximately linear fashion with respect to the simplification ratio.
46346058
On Utilization of the Grid Computing Technology for Video Conversion and 3D Rendering
The present invention relates to an implant comprising two or more bone fragments that are combined to form a single unit. Cancellous bone or cortical bone is removed from a source and fashioned into bone components with desirable shapes and sizes. The bone components may be integrated to form implants for implantation in the body. Bone stock may be formed by combining sections of various bones of the body, and the bone stock may be further fashioned for use as implants with particular geometries.
10473585
Metadata design for Chinese medicine digital library using XML
The development of Chinese medicine has been growing rapidly and is beginning to draw significant attention globally. In Hong Kong in particular, the government has targeted Chinese medicine as one of its major future developments. A system for registering Chinese medical practitioners is being set up and a Chinese medicine port for medical manufacturing and research is being investigated. Although it has drawn significant attention, information about Chinese medicine is not yet widely available on the Internet, and searching for such information is extremely difficult. In this paper, we present an XML metadata design for Chinese medicine. The system encompasses a register server, information servers, a search engine and client programs that have been developed to browse and search the XML documents that are available in distributed Chinese medicine digital libraries.
39460490
Localization Techniques for Cluster-Based Data Grid
In this paper, we present an efficient method for optimizing localities of data distribution when executing data parallel applications. The data to logical grid nodes mapping technique is employed to enhance the performance of parallel programs on cluster grid. Cluster grid is a typical computational grid environment consists of several clusters located in multiple campuses that are distributed globally over the Internet. Objective of the proposed technique is to reduce inter-cluster communication overheads and to speed the execution of data parallel programs in the underlying distributed cluster grid. The theoretical analysis and experimental results show improvement of communication costs and scalable of the proposed techniques on different hierarchical cluster grids.
14357839
Clustering-training for Data Stream Mining
Mining data streams has attracted much attention recently. Labeled samples needed by most current stream classification methods are more difficult and expensive to obtain than unlabeled ones. This paper proposed a semi-supervised learning algorithm - clustering-training to utilize the unlabeled samples. It uses clustering to select confidently unlabeled samples, and uses them to re-train the classifier incrementally. Experiments on synthetic and real data set showed the effectiveness of the proposed algorithm