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Protein-protein interaction plays an important role in understanding biological processes. In order to resolve the parsing error resulted from modal verb phrases and the noise interference brought by appositive dependency, an improved tree kernel-based PPI extraction method is proposed in this paper. Both modal verbs and appositive dependency features are(More)
At present, the retrieval approaches could not match the concept with identical meaning but dissimilar expression. To aim at solving the problem, this paper puts forward a retrieval model based on concept extending. The system model is composed of three levels, which are the query level, the concept extending level, and the retrieval level. In the model, an(More)
This paper probes into how to improve Information Retrieval by changing the feature distribution of the text. It introduces Cloud Model theory into Latent Dirichlet Allocation(LDA) Model and build a new feature selection system. LDA Model is used to mine the underlying topical structure. Each topic is associated with a multinomial distribution over words(More)
By introducing cloud model, this paper presents a re-ranking method which improves the accuracy of the IR (information retrieval) while recall is preserved. It is rare in traditional Chinese information retrieval to consider uncertainty while calculating the related degree of the query and each document in the result set. This paper researches IR in a(More)
Genomic Information Retrieval which contains huge highly specific information causes many problems, such as the synonym problem, long term name and rapid growing literature size. In this paper, we use a concept-based model for indexing and querying, which is not like the translation model or the traditional query expansion techniques. We adopt an extraction(More)