Using Cohesion-Model for Story Link Detection System
نویسندگان
چکیده
Cohesion-Model is a new Story Link Detection (SLD) System that is inspired by the relevance model of TDT. Task in hand is to detect whether given two documents are linked. Each document is expanded using corresponding relevant documents. Each term in the relevant document is weighted according to the cohesion factor. The two models then are compared using the modified fractional similarity. Performance of this model shows distinct improvement when compared with most effective Link Detection System, which measures similarity between the given two documents using cosine method. The model is also compared with a system using modified fractional method without building Cohesion-Model. The experimental results show the performance of Cohesion-Model tested with TDT4 data and proves the effectiveness of the new model.
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