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- W162769501 abstract "The amount of on-line information is growing exponentially. Much of this information is unstructured and language-based. To deal with this flood of information, a number of tools and language technologies have been developed. Progress has been made in areas such as information retrieval, information extraction, filtering, speech recognition, machine translation, and data mining. Other more specific areas such as cross-lingual retrieval, summarization, categorization, distributed retrieval, and topic detection and tracking are also contributing to the proliferation of technologies for managing information. Currently these tools are based on many different approaches, both formal and ad hoc. Integrating them is very diffcult, yet this will be a critical part of building effective information systems in the future. In this paper, we discuss an approach to providing a framework for integration based on language models." @default.
- W162769501 created "2016-06-24" @default.
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- W162769501 date "2000-01-01" @default.
- W162769501 modified "2023-09-22" @default.
- W162769501 title "Information Retrieval Based on Statistical Language Models" @default.
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- W162769501 doi "https://doi.org/10.1007/3-540-39963-1_1" @default.
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