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images automatically. Cluster IDs are adopted to index the characters. A Dream of Red Mansions, a famous classical Chinese literature work including near one million characters, is used to evaluate the performance of Chinese keyword spotting. Experimental results confirm the effectiveness of knowledge-based clustering and
Ranking solutions is an important issue in Information Retrieval because it greatly influences the quality of results. In this context, keyword based search approaches use to consider solutions sorting as least step of the overall process. Ranking and building solutions are completely separate steps running
single machine. Our motivating application is recommenders, which typically deal with big numbers of users and items, but other applications might benefit as well, like keyword search. In this paper, we propose a parallel top-k MapReduce algorithm that, unlike existing MapReduce solutions, manages to handle cases in which
aggregation function for textual data. Our approach is based on the affinity between keywords and uses the search of cycles in a graph to find the aggregated keywords. We also present performances and a comparison with three other methods. The experimental study shows good results for our approach.
of terms or keywords. The keywords for one cluster may not occur in the documents of other clusters. This is a data sparsity problem faced in clustering high-dimensional data. In the new algorithm, we extend the k-means clustering process to calculate a weight for each dimension in each cluster and use the weight values
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.