Hierarchical dirichlet trees for information retrieval
We propose a principled probabilisitc framework which uses trees over the vocabulary to capture similarities among terms in an information retrieval setting. This allows the retrieval of documents based not just on occurrences of specific query terms, but also on similarities between terms (an effec...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2009
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| Summary: | We propose a principled probabilisitc framework which uses trees over the vocabulary to capture similarities among terms in an information retrieval setting. This allows the retrieval of documents based not just on occurrences of specific query terms, but also on similarities between terms (an effect similar to query expansion). Additionally our principled generative model exhibits an effect similar to inverse document frequency. We give encouraging experimental evidence of the superiority of the hierarchical Dirichlet tree compared to standard baselines. © 2009 Association for Computational Linguistics. |
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