9223359
Image browsing for infomediaries
Information intermediary or infomediary is likely to claim a major segment of the revenue of e-commerce transactions. Infomediaries are e-commerce companies leveraging the Internet to unite buyers and suppliers in a single efficient virtual marketplace to facilitate the consummation of a transaction. Most of the search facilities in the infomediaries are text- and navigation-based, for example by keyword and category searches. The search facility can handle most of the products, but it is inefficient to handle feature-based products, such as textile and shoes with different colors and textures. It will be difficult for buyers to speck searches of feature-based products in describing the product features and characteristics. For example, it is hot easy to describe the pattern and color of a T-shirt using textural expression. In this paper, we propose an image browsing technique to facilitate search of feature-based products for infomediaries. We implemented an image-based retrieval system with the proposed image browsing technique for textile industrial and evaluated the performance of the browsing technique.
16166999
Automatic Construction of Cross-Lingual Networks of Concepts from the Hong Kong SAR Police Department
The tragic event of September 11 has prompted the rapid growth of attention of national security and criminal analysis. In the national security world, very large volumes of data and information are generated and gathered. Much of this data and information written in different languages and stored in different locations may be seemingly unconnected. Therefore, cross-lingual semantic interoperability is a major challenge to generate an overview of this disparate data and information so that it can be analysed, searched. The traditional information retrieval (IR) approaches normally require a document to share some keywords with the query. In reality, the users may use some keywords that are different from what used in the documents. There are then two different term spaces, one for the users, and another for the documents. The problem can be viewed as the creation of a thesaurus. The creation of such relationships would allow the system to match queries with relevant documents, even though they contain different terms. Apart from this, terrorists and criminals may communicate through letters, e-mails and faxes in languages other than English. The translation ambiguity significantly exacerbates the retrieval problem. To facilitate cross-lingual information retrieval, a corpusbased approach uses the term co-occurrence statistics in parallel or comparable corpora to construct a statistical translation model to cross the language boundary. However, collecting parallel corpora between European language and Oriental language is not an easy task due to the unique linguistics and grammar structures of oriental languages. In this paper, the text-based approach to align English/Chinese Hong Kong Police press release documents from the Web is first presented. This article then reports an algorithmic approach to generate a robust knowledge base based on 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.
15408418
CatRelate: A New Hierarchical Document Category Integration Algorithm by Learning Category Relationships
We address the problem of integrating documents from a source catalog into a master catalog. Current technologies for solving the problem deem it as a flat category integration problem without considering the useful hierarchy information in the catalog, or deal with it hierarchically but without a rigorous model. In contrast, our method is based on correctly identifying relationships among categories, such as Match, Disjoint, SubConcept, SuperConcept, and Overlap, which come from the relations of sets in Set theory. Compared with traditional Match/NotMatch relationship in literature, our approach is more expressive in defining the relationship. The relationships among categories are first learned in a probabilistic way, and then refined by considering the hierarchy context. Our preliminary experiments show that it can help to correctly identify category relationships, and thus increase the accuracy of document integration.
15657957
Automatic Summarization of Chinese and English
As a result of the rapid growth in Internet access, significantly more information has become available online in real time. However, there is not sufficient time for users to read large volumes of information and make decisions accordingly. The problem of information-overloading can be resolved through the application of automatic summarization. Many summarization systems for documents in different languages have been implemented. However, the performance of summarization system on documents in different languages has not yet been investigated. In this paper, we compare the result of fractal summarization technique on parallel documents in Chinese and English. The grammatical and lexical differences between Chinese and English have significant effect on the summarization processes. Their impact on the performances of the summarization for the Chinese and English parallel documents is compared.
16831415
Automatic construction of English/Chinese parallel corpora
As the demand for global information increases significantly, multilingual corpora has become a valuable linguistic resource for applications to cross-lingual information retrieval and natural language processing. In order to cross the boundaries that exist between different languages, dictionaries are the most typical tools. However, the general-purpose dictionary is less sensitive in both genre and domain. It is also 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 with which to cross the language boundary. There are many domain-specific parallel or comparable corpora that are employed in machine translation and cross-lingual information retrieval. Most of these are corpora between Indo-European languages, such as English/French and English/Spanish. The Asian/Indo-European corpus, especially English/Chinese corpus, is relatively sparse. The objective of the present research is to construct English/ Chinese parallel corpus automatically from the World Wide Web. In this paper, an alignment method is presented which is based on dynamic programming to identify the one-to-one Chinese and English title pairs. The method includes alignment at title level, word level and character level. The longest common subsequence (LCS) is applied to find the most reliable Chinese translation of an English word. As one word for a language may translate into two or more words repetitively in another language, the edit operation, deletion, is used to resolve redundancy. A score function is then proposed to determine the optimal title pairs. Experiments have been conducted to investigate the performance of the proposed method using the daily press release articles by the Hong Kong SAR government as the test bed. The precision of the result is 0.998 while the recall is 0.806. The release articles and speech articles, published by Hongkong & Shanghai Banking Corporation Limited, are also used to test our method, the precision is 1.00, and the recall is 0.948.
2566456
Interval constraint networks for tolerance analysis and synthesis
This paper proposes interval constraint networks and interval propagation techniques for automatic tolerance design. To develop an intelligent automatic tolerance design mechanism, the following interrelated problems are addressed: (1) representing the relationships between the tolerances of the entities, attributes, and the functional requirements of a design component by a constraint network, (2) developing tolerance propagation techniques in the network that will satisfy the constraints between the entities, attributes and functional requirement. For the purpose of tolerance design, we propose new definitions for consistency of constraints and consistency of a constraint network. New forward and backward propagation techniques achieve worst-case tolerance analysis and synthesis, respectively. A tank design problem illustrates the use of the procedures for tolerance analysis and synthesis. The discussion and examples compare the new constraint network and propagation techniques with previous works.
1160125
Foreign Name Backward Transliteration in Chinese-English Cross-Language Image Retrieval
In this paper we propose an approach to deal with the Chinese-English cross-language image retrieval problem. Text-based image retrieval and query translation methods were adopted in the experiments. A similarity-based backward transliteration model with candidate filter was proposed to translate proper nouns that have no entries in a bilingual dictionary. The experimental results showed that using similarity-based backward transliteration increased retrieval performances.
18362603
Apply cluster and grid computing on parallel 3D rendering
A cluster is a collection of independent and cheap machines, used together as a supercomputer to provide a solution. In this paper, a PC cluster consisting of one master node and nine disk-less slave nodes (10 processors), is proposed and built for parallel rendering purposes. The system architecture and benchmark performances of this cluster are also presented. Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. Harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. Also, in this paper, we construct two heterogeneous PC clusters for parallel rendering purpose and install Linux Red Hat 9 on each PC cluster. Then, these clusters are set to the different subnet. Therefore, we use the grid middleware lambdaobus ToolKit, to connect these two clusters to form a grid computing environment on multiple Linux PC clusters. We also install the SUN Grid Engine, to manage and monitor incoming or outgoing computing jobs and schedule the job to achieve high performance computing and high CPU utilization. The system architecture and benchmark performances of this cluster are also presented
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.
1218659
Efficient discovery of error-tolerant frequent itemsets in high dimensions
We present a generalization of frequent itemsets allowing for the notion of errors in the itemset definition. We motivate the problem and present an efficient algorithm that identifies error-tolerant frequent clusters of items in transactional data (customer-purchase data, web browsing data, text, etc.). The algorithm exploits sparseness of the underlying data to find large groups of items that are correlated over database records (rows). The notion of transaction coverage allows us to extend the algorithm and view it as a fast clustering algorithm for discovering segments of similar transactions in binary sparse data. We evaluate the new algorithm on three real-world applications: clustering high-dimensional data, query selectivity estimation and collaborative filtering. Results show that the algorithm consistently uncovers structure in large sparse databases that other traditional clustering algorithms fail to find.
16872458
Decision tree construction for data mining on grid computing environments
In this paper, the authors presented the grid-based decision tree architecture, with the intention of applying it to both parallel and sequential algorithms. Also, it is shown that, based on the scope and model of data mining applied in the grid environment as well as user equivalent perspective, grid roles can be categorized into three types. It was aimed, through these definitions, to help software developers define clear system processes and differentiate the application scope for software applications. To fulfill the architecture, an existing parallel decision tree algorithm was first applied (the SPRINT algorithm) to the grid environment. The performance and differences in many other areas are compared using datasets of different sizes. The experimental results will be used for future reference and further development.