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Numerous past studies have demonstrated the effectiveness of the relevance modelRM for information retrieval IR. This approach enables relevance or pseudo-relevance feedback to be incorporated within the language modeling framework of IR. In the traditional RM, the feedback information is used to improve the estimate of the query language model. In this article, we introduce an extension of RM in the setting of relevance feedback. Our method provides an additional way to incorporate feedback via the improvement of the document language models. Specifically, we make use of the context information of known relevant and nonrelevant documents to obtain weighted counts of query terms for estimating the document language models. The context information is based on the words unigrams or bigrams appearing within a text window centered on query terms. Experiments on several Text REtrieval Conference TREC collections show that our context-dependent relevance model can improve retrieval performance over the baseline RM. Together with previous studies within the BM25 framework, our current study demonstrates that the effectiveness of our method for using context information in IR is quite general and not limited to any specific retrieval model.

While term independence is a widely held assumption in most of the established information retrieval approaches, it is clearly not true and various works in the past have investigated a relaxation of the assumption. One approach is to use n-grams in document representation instead of unigrams. However, the majority of early works on n-grams obtained only modest performance improvement. On the other hand, the use of information based on supporting terms or "contexts" of queries has been found to be promising. In particular, recent studies showed that using new context-dependent term weights improved the performance of relevance feedback RF retrieval compared with using traditional bag-of-words BM25 term weights. Calculation of the new term weights requires an estimation of the local probability of relevance of each query term occurrence. In previous studies, the estimation of this probability was based on unigrams that occur in the neighborhood of a query term. We explore an integration of the n-gram and context approaches by computing context-dependent term weights based on a mixture of unigrams and bigrams. Extensive experiments are performed using the title queries of the Text Retrieval Conference TREC-6, TREC-7, TREC-8, and TREC-2005 collections, for RF with relevance judgment of either the top 10 or top 20 documents of an initial retrieval. We identify some crucial elements needed in the use of bigrams in our methods, such as proper inverse document frequency IDF weighting of the bigrams and noise reduction by pruning bigrams with large document frequency values. We show that enhancing context-dependent term weights with bigrams is effective in further improving retrieval performance.

This paper describes the design and development of a computer interface for blind and visually-impaired users, who are native speakers of Cantonese (i.e. a Chinese dialect). Apart from enabling the interface to (1) produce Chinese voice output, (2) convert Chinese characters to Braille codes, (3) facilitate Chinese Braille input, and (4) operate in a Microsoft Chinese Windows environment, the significant aspects of this paper include the following: (1) the description of an integrated architecture, which can be used for other languages; (2) a general bilingual Braille input mechanism; (3) a sentence-based input method that can be used for contracted-Braille-to-text conversion with an error rate of about 6%, operating at about 700 characters/second using a Pentium II 300 MHz PC; (4) a code-mixed synthesis module for general bilingual and multilingual applications; (5) the potential to directly adopt the system for use with other ideographic languages (like Japanese and Korean), as well as agglutinating languages like Finnish and Turkish, which have no space between words.

XML holds the promise to yield (1) a more precise search by providing additional information in the elements, (2) a better integrated search of documents from heterogeneous sources, (3) a powerful search paradigm using structural as well as content specifications, and (4) data and information exchange to share resources and to support cooperative search. We survey several indexing techniques for XML documents, grouping them into flat-file, semistructured, and structured indexing paradigms. Searching techniques and supporting techniques for searching are reviewed, including full text search and multistage search. Because searching XML documents can be very flexible, various search result presentations are discussed, as well as database and information retrieval system integration and XML query languages. We also survey various retrieval models, examining how they would be used or extended for retrieving XML documents. To conclude the article, we discuss various open issues that XML poses with respect to information retrieval and database research.

In certain bilingual and multi-lingual societies, translated legal documents are as important as the original legal documents because they have the same legal status as the originals. However, there is little reported work on the retrieval and management of bilingual legal documents. We describe the design and development of a bilingual document retrieval and management prototype, called ELDoS, which is used by court interpreters and judges from the Hong Kong Judiciary. Since the speed of retrieval is a major concern for user acceptance, and therefore for widespread deployment of the system, the architecture of the prototype is designed to balance the workload of the client and server. Extensible Markup Language (XML) is used to mark up the bilingual legal documents for a variety of document retrieval and management tasks. XML enables the use of XML Stylesheet Language Transformation (XSLT) to align bilingual data in the client, instead of the server, and improve alignment speed linearly with respect to the size of the document, using a high-end PC, when the server has no concurrent access. The design of the interface was continually improved after extensive consultation with court interpreters and after the user acceptance tests. In our evaluation, the facilities for highlighting translated terms have a macro-averaged precision of 90+ % and a macro-average recall of 80+ %, which were considered acceptable by our users. We believe that the experience in the design and development of this prototype is applicable to other language pairs as well as to other domains.

Chinese idioms play an important role in Chinese vocabulary learning as well as having cultural and social functions. However, researchers found that Hong Kong students seldom use idioms. Not only are students writing characters incorrectly, they are using the idioms both incorrectly and inappropriately. A survey was conducted to examine the attitudes of Hong Kong students and teachers to learning Chinese idioms. According to the survey, primary teachers believed that computers can assist students in learning Chinese idioms more effectively than an idiom dictionary. Consequently, an experimental program for learning Chinese idioms was designed for students between 9 and 11 years old. As an evaluation, usability tests were carried out by interview and by survey. Both evaluations produced positive responses from the dependent and independent group of subjects which is an encouraging first step.