Structured Index Organizations for High-Throughput Text Querying
Inverted indexes are the preferred mechanism for supporting content-based queries in text retrieval systems, with the various data items usually stored compressed in some way. But different query modalities require that different information be held in the index. For example, phrase querying requires that word offsets be held as well as document numbers. In this study we describe an inverted index organization that provides efficient support for all of conjunctive Boolean queries, ranked queries, and phrase queries. Experimental results on a 426 GB document collection show that the methods we describe provide fast evaluation of all three querying modes.
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