We present an efficient query evaluation method based on a two level approach: at the first level, our method iterates in parallel over query term postings and identifies candidate documents using an approximate evaluation taking into account only partial information on term occurrences and no query independent factors; at the second level, promising candidates are fully evaluated and their exact scores are computed. The efficiency of the evaluation process can be improved significantly using dynamic pruning techniques with very little cost in effectiveness. The amount of pruning can be controlled by the user as a function of time allocated for query evaluation. Experimentally, using the TREC Web Track data, we have determined that our algorithm significantly reduces the total number of full evaluations by more than 90%, almost without any loss in precision or recall.At the heart of our approach there is an efficient implementation of a new Boolean construct called WAND or Weak AND that might be of independent interest.

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Abstract. Modern document collections often contain groups of documents with overlapping or shared content. However, most information retrieval systems process each document separately, causing shared content to be indexed multiple times. In this paper, we describe a new document representation model where related documents are organized as a tree, allowing shared content to be indexed just once. We show how this representation model can be encoded in an inverted index and we describe algorithms for evaluating free-text queries based on this encoding. We also show how our representation model applies to web, email, and newsgroup search. Finally, we present experimental results showing that our methods can provide a significant reduction in the size of an inverted index as well as in the time to build and query it.

Many information systems keep multiple versions of documents. Examples include content management systems, version control systems (e.g. ClearCase, CVS), Wikis, and backup and archiving solutions. Often, it is desired to enable free-text search over such repositories, i.e. to enable submitting queries that may match any version of any document. We propose an indexing method that takes advantage of the inherent redundancy present in versioned documents by solving a variant of the multiple sequence alignment problem. The scheme produces an index that is much more compact than a standard index that treats each version independently. In experiments over publicly available versioned data, our method achieved compaction ratios of 81% as compared with standard indexing, while supporting the same retrieval capabilities.

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