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In real-world information retrieval (IR) tasks, the searched items and/or the users' queries often have implicit information associated with them -- information that describes unspecified aspects of t...
The main goal of this thesis is to investigate query-dependent selection of retrieval alternatives for Information Retrieval (IR) systems. Retrieval alternatives include choices in representing querie...
Providing an effective mechanism for personal information retrieval is important for many applications, and requires different techniques than have been developed for general web search. This thesis f...
Current information retrieval models are optimized for retrieval with short keyword queries. In contrast, in this dissertation we focus on longer, verbose queries with more complex structure that are ...
A growing number of information retrieval applications rely on search behavior aggregated over many users. If aggregated data such as search query reformulations is not handled properly, it can allow ...
The use of information retrieval (IR) systems is evolving towards larger, more complicated queries. Both the IR industrial and research communities have generated significant evidence indicating that ...
Natural language expressions are more familiar to users than choosing keywords for queries. Given that, people can use natural language expressions to represent their sophisticated information needs. ...
Research into term dependencies for information retrieval has demonstrated that dependency retrieval models are able to consistently improve retrieval effectiveness over bag-of-words models. However, ...
The goal of this work is to leverage cross-document entity relationships for improved understanding of queries and documents. We define an entity to be a thing or concept that exists in the world, suc...
Case retrieval in case-based reasoning relies heavily on the design of a good similarity function. This paper provides an approach to utilizing the correlative information among features to compute th...

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