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There is much regularity in Chinese characters. For example, the characters ... (car), ... (wheel), ... (rail), ... (transport), ... (carry), ... (turn) and ... (the roar of train) are all in relation to "transportation" and at the same time share the component .... An interactive database that can retrieve these characters as linked together can enable students to explore and discover the relationship among the characters. This paper reports our many years of works in designing and developing such databases for learning Chinese characters. Several interesting issues on the implementation are raised, including intuitive interaction, demand for high accuracy, codification of components, decomposition of characters, handling multiple acceptable values, irregularity of Chinese characters and application-oriented development. Unlike most technology-centric research, much of our experience has been gained through an iterative development of the databases with actual contents and in collaboration with the Chinese educators. In this paper, we hope to propose a more humanistic and contextual approach into the study of Chinese computing. [ABSTRACT FROM AUTHOR]

Deep parsing of Chinese sentences is a very challenging task due to their complexity such as ambiguous word boundaries and meanings. An alternative mode of Chinese language processing is to perform shallow parsing of Chinese sentences in which chunk segmentation plays an important role. In this paper, we present a chunk segmentation algorithm using a combined statistical and rule-based approach (CSRA). The decision rules for refining chunk segmentation are generated from incorrectly segmented chunks from a statistical model which is built on a training corpus. Experimental results show that the CSRA works well and produces satisfactory chunk segmentation results for subsequent processes such as chunk tagging and chunk collocation extraction. [ABSTRACT FROM AUTHOR]

Real-time communication platforms such as ICQ, MSN and online chat rooms are popular today over the Internet. The language used on these platforms differs significantly from standard natural language. Comparatively, this language, referred to as chat language, is informal, anomalous and dynamic. In this paper, the NIL corpus — a Chinese chat language text collection — is presented which is constructed to facilitate language study. Also, linguistic characteristics and ecological behaviour of the language are studied. We show that chat language is anomalous and dynamic in nature leading to the out-of-vocabulary, ambiguity and sparse data problems. To tackle these problems, a novel chat language model is proposed. The model is based on phonetic mapping between chat terms and their standard natural language counterparts. [ABSTRACT FROM AUTHOR]

Implementation of legal bilingualism in Hong Kong after 1997 has necessitated the production of voluminous and extensive court proceedings and judgments in both Chinese and English. For the Chinese records, Cantonese, a dialect of Chinese, is the home language of more than 90% of the population in Hong Kong and is thus officially used in the courts. For the court proceedings, Cantonese speech would have to be recorded, and a Cantonese Computer-Aided Transcription system has been developed. The transcription system converts stenographic codes into Chinese text, i.e. from phonetic to orthographic representation of the language. The main challenge lies in the resolution of the severe ambiguity resulting from homocode problems in the conversion process. Cantonese Chinese is typified by problematic homonymy, which presents serious challenges. The N-gram statistical model is employed to estimate the most probable character string of the input transcription codes. Domain-specific corpora have been compiled to support the statistical computation. To improve accuracy, scalable techniques such as domain-specific transcription and special encoding are used. Put together, these techniques deliver 96% transcription accuracy. [ABSTRACT FROM AUTHOR]

The amount of online information in Chinese and the number of Chinese Internet users have been increasing tremendously during the past decade. Since Chinese language is significantly different from English, techniques that have been developed for retrieving information from English Web documents cannot be directly applied to retrieve information from Chinese Web documents. In order to provide high-performance access of Chinese information on the Web, we have developed a Chinese Web query engine that (i) extracts (hierarchical) data of interest from Chinese HTML tables using an information extraction tool called semantic hierarchy, (ii) allows the user to submit queries in Chinese using a menu-driven user interface, and (iii) processes the user's queries (as Boolean expressions) to generate the correct results. Our query engine supports various groups of information that are categorized into various subject areas, such as car ads, house rentals, job ads, stocks, university catalogs, etc. We have tested our information extraction tool on two application domains, car-ads and house-rental. The average F-measure on extracting Chinese data from these two application domains is above 90%. More importantly, our query engine can easily be configured and internationalized to become a worldwide, multilingual query engine with minor changes in system settings on PCs running Windows operating systems. [ABSTRACT FROM AUTHOR]