Result merging method based on combined kernels for distributed information retrieval
To enhance the performance of result merging for distributed information retrieval（DIR）,a novel merging method was put forward,which was based on relevance between retrieved results and query.Improved latent semantic kernel（LSK） was combined with analysis of variance（ANOVA） kernel to calculate the r...
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| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2011-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/74418569/ |
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| Summary: | To enhance the performance of result merging for distributed information retrieval（DIR）,a novel merging method was put forward,which was based on relevance between retrieved results and query.Improved latent semantic kernel（LSK） was combined with analysis of variance（ANOVA） kernel to calculate the relevance.Experimental results showed that the result merging precision of the combination of LSK and ANOVA kernel（CLA） is 16.79%,30.73%,20.37%,24.17%,14.25%,13.50% and 7.53% higher than that of Round-robin,ComMNZ,Bayesian,Borda,SDM,MEM and regression SVM respectively.CLA kernel method has better performance for result merging and is a practical method for result merging in DIR. |
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| ISSN: | 1000-436X |