Applying digital content management to support localisation

The retrieval and presentation of digital content such as that on the World Wide Web (WWW) is a substantial area of research. While recent years have seen huge expansion in the size of web-based archives that can be searched efficiently by commercial search engines, the presentation of potentially relevant content is still limited to ranked document lists represented by simple text snippets or image keyframe surrogates. There is expanding interest in techniques to personalise the presentation of content to improve the richness and effectiveness of the user experience. One of the most significant challenges to achieving this is the increasingly multilingual nature of this data, and the need to provide suitably localised responses to users based on this content. The Digital Content Management (DCM) track of the Centre for Next Generation Localisation (CNGL) is seeking to develop technologies to support advanced personalised access and presentation of information by combining elements from the existing research areas of Adaptive Hypermedia and Information Retrieval. The combination of these technologies is intended to produce significant improvements in the way users access information. We review key features of these technologies and introduce early ideas for how these technologies can support localisation and localised content before concluding with some impressions of future directions in DCM

Beyond English text: Multilingual and multimedia information retrieval.

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PLuTO: MT for online patent translation

PLuTO – Patent Language Translation Online – is a partially EU-funded commercialization project which specializes in the automatic retrieval and translation of patent documents. At the core of the PLuTO framework is a machine translation (MT) engine through which web-based translation services are offered. The fully integrated PLuTO architecture includes a translation engine coupling MT with translation memories (TM), and a patent search and retrieval engine. In this paper, we first describe the motivating factors behind the provision of such a service. Following this, we give an overview of the PLuTO framework as a whole, with particular emphasis on the MT components, and provide a real world use case scenario in which PLuTO MT services are exploited

Multilingual manager: a new strategic role in organizations

Today?s knowledge management (KM) systems seldom account for language management and, especially, multilingual information processing. Document management is one of the strongest components of KM systems. If these systems do not include a multilingual knowledge management policy, intranet searches, excessive document space occupancy and redundant information slow down what are the most effective processes in a single language environment. In this paper, we model information flow from the sources of knowledge to the persons/systems searching for specific information. Within this framework, we focus on the importance of multilingual information processing, which is a hugely complex component of modern organizations

Multilingual adaptive search for digital libraries

This paper describes a framework for Adaptive Multilingual Information Retrieval (AMIR) which allows multilingual resource discovery and delivery using on-the-fly machine translation of documents and queries. Result documents are presented to the user in a contextualised manner. Challenges and affordances of both Adaptive and Multilingual IR, with a particular focus on Digital Libraries, are detailed. The framework components are motivated by a series of results from experiments on query logs and documents from The European Library. We conclude that factoring adaptivity and multilinguality aspects into the search process can enhance the user’s experience with online Digital Libraries

Japanese/English Cross-Language Information Retrieval: Exploration of Query Translation and Transliteration

Cross-language information retrieval (CLIR), where queries and documents are in different languages, has of late become one of the major topics within the information retrieval community. This paper proposes a Japanese/English CLIR system, where we combine a query translation and retrieval modules. We currently target the retrieval of technical documents, and therefore the performance of our system is highly dependent on the quality of the translation of technical terms. However, the technical term translation is still problematic in that technical terms are often compound words, and thus new terms are progressively created by combining existing base words. In addition, Japanese often represents loanwords based on its special phonogram. Consequently, existing dictionaries find it difficult to achieve sufficient coverage. To counter the first problem, we produce a Japanese/English dictionary for base words, and translate compound words on a word-by-word basis. We also use a probabilistic method to resolve translation ambiguity. For the second problem, we use a transliteration method, which corresponds words unlisted in the base word dictionary to their phonetic equivalents in the target language. We evaluate our system using a test collection for CLIR, and show that both the compound word translation and transliteration methods improve the system performance

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems