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The ineffectiveness of information retrieval systems is mostly caused by the inaccurate query formed by a few keywords that reflect actual user information need. One well known technique to overcome this limitation is Automatic Query Expansion (AQE), whereby the user's original query is improved by adding new features with a related meaning. It has long been accepted that capturing term associations...
With the development of natural language processing (NLP) technology, the need for automatic named entity recognition (NER) is highlighted in order to enhance the performance of information extraction systems. In this paper, a hybrid model for Chinese person based on conditional random fields model is proposed, which fuses multiple features. It differentiates from most of the previous approaches,...
Tagging is an increasingly important task in natural language processing domains. As there are many natural language processing tasks which can be improved by applying disambiguation to the text, fast and high quality tagging algorithms are a crucial task in information retrieval and question answering. Tagging aims to assigning to each word of a text its correct tag according to the context in which...
In this paper we describe our work on generating in-domain corpus using auto-induced semantic classes and structures for language model adaptation in a voice search dialogue system. We proposed a novel similarity measure based on co-occurrence probabilities for inducing semantic classes. Clustering with the new similarity measure outperformed that with the widely used distance measure based on Kullback-Leibler...
Aiming at the problem of the "semantic gap" and the "dimensionality curse", this paper discussed the model of cross-media retrieval. The methods of feature extraction and fusion of multimedia were given for processing high-dimensional data, and a nonlinear hybrid classifier based on support vector hidden Markov models was design for implementation semantic mapping and learning...
Nowadays rapid and accurate speech retrieval techniques based on semantics are desired for the overwhelming amounts of speech data. In this paper we mainly study a converted lattice-based approach for Chinese spontaneous speech retrieval. A new confidence measure method is proposed based on context mutual information. In our knowledge, it is firstly used in a lattice construction for speech indexing...
In this paper, one Chinese interrogative sentence words segmentation technology based on the statistics in the intelligent Q/A system was introduced, we elaborated the process of the wordspsila sketchy division, the non-registering words recognition and the words marking which have different means, and the statistical model based on N most short-path's in wordspsila sketchy division was analyzed....
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