the INEX 2005 ad hoc track, covering the Thorough, Focused, and Fetch-Browse tasks and their structured (+S) counterparts. Our research questions for this round of INEX were threefold. Our first and main research question was to investigate the contribution of structural constraints to improved retrieval performance. Our main results were that the two types of structural constraints have different effects. Constraining the target of result elements gives improvements in terms of early precision. Constraining the context of result elements improves mean average precision. Our second research question was to experiment with selective indexing strategies based on either the length of elements, the tag-name of elements considered relevant in earlier INEX years, or simply by indexing all sections or articles. Our experiments show that disregarding 80–90% of the total number of elements does not decrease retrieval performance. Third, we considered the automatic creation of structured queries using blind feedback. Here, our results are inconclusive, mainly due to few queries used and lack of comparison to traditional blind feedback. 1

In this report, we unify two quite distinct approaches to information retrieval: region models and language models. Region models were developed for structured document retrieval. They provide a well-defined behaviour as well as a simple query language that allows application developers to rapidly develop applications. Language models are particularly useful to reason about the ranking of search results, and for developing new ranking approaches. The unified model allows application developers to define complex language modeling approaches as logical queries on a textual database. We show a remarkable one-to-one relationship between region queries and the language models they represent for a wide variety of applications: simple ad-hoc search, cross-language retrieval, video retrieval, and web search. 1

In this paper we present the extension of our prototype three-level database system (TIJAH) developed for structured information retrieval. The extension is aimed at modeling vague search on XML elements. All three levels (conceptual, logical, and physical) of the TIJAH system are enhanced to support vague search concepts. The vague search is implemented as vague selection of XML elements using XML element name expansion lists and rewriting techniques. We test the performance of retrieval models using automatically generated expansion lists and compared them with models that use manual ones. The goal is to find the best approach for structured information retrieval with vague structural constraints on element names expressed in the query. 1.

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We address two open problems involving algebraic execution of full-text search queries. First, we show how to correctly apply traditional database rewrite optimizations to full-text algebra plans with integrated scoring, and explain why existing techniques fail. Second, we show how our techniques are applied in a generic scoring framework that supports a wide class of scoring algorithms, including algorithms seen in the literature and user-defined scoring. Categories and Subject Descriptors