PFTijah: text search in an XML database system

This paper introduces the PFTijah system, a text search system that is integrated with an XML/XQuery database management system. We present examples of its use, we explain some of the system internals, and discuss plans for future work. PFTijah is part of the open source release of MonetDB/XQuery

Sound ranking algorithms for XML search

Ranking algorithms for XML should reflect the actual combined content and structure constraints of queries, while at the same time producing equal rankings for queries that are semantically equal. Ranking algorithms that produce different rankings for queries that are semantically equal are easily detected by tests on large databases: We call such algorithms not sound. We report the behavior of different approaches to ranking content-and-structure queries on pairs of queries for which we expect equal ranking results from the query semantics. We show that most of these approaches are not sound. Of the remaining approaches, only 3 adhere to the W3C XQuery Full-Text standard

Structured Text Retrieval Models

Structured text retrieval models provide a formal definition or mathematical framework for querying semistructured textual databases. A textual database contains both content and structure. The content is the text itself, and the structure divides the database into separate textual parts and relates those textual parts by some criterion. Often, textual databases can be represented as marked up text, for instance as XML, where the XML elements define the structure on the text content. Retrieval models for textual databases should comprise three parts: 1) a model of the text, 2) a model of the structure, and 3) a query language [4]: The model of the text defines a tokenization into words or other semantic units, as well as stop words, stemming, synonyms, etc. The model of the structure defines parts of the text, typically a contiguous portion of the text called element, region, or segment, which is defined on top of the text modelâ\u80\u99s word tokens. The query language typically defines a number of operators on content and structure such as set operators and operators like â\u80\u9ccontaining â\u80\u9d and â\u80\u9ccontained-by â\u80\u9d to model relations between content and structure, as well as relations between the structural elements themselves. Using such a query language, the (expert) user can for instance formulate requests like â\u80\u9cI want a paragraph discussing formal models near to a table discussing the differences between databases and information retrievalâ\u80\u9d. Here, â\u80\u9cformal models â\u80\u9d and â\u80\u9cdifferences between databases and information retrieval â\u80\u9d should match the content that needs to be retrieved from the database, whereas â\u80\u9cparagraph â\u80\u9d and â\u80\u9ctable â\u80\u9d refer to structural constraints on the units to retrieve. The features, structuring power, and the expressiveness of the query languages of several models for structured text retrieval are discussed below. HISTORICAL BACKGROUND The STAIRS system (Storage and Information Retrieval System), which was developed at IBM already in the late 1950â\u80\u99s allowed querying both content and structure. Much like todayâ\u80\u99s On-line Public Access Catalogues, it wa

A survey on tree matching and XML retrieval

International audienceWith the increasing number of available XML documents, numerous approaches for retrieval have been proposed in the literature. They usually use the tree representation of documents and queries to process them, whether in an implicit or explicit way. Although retrieving XML documents can be considered as a tree matching problem between the query tree and the document trees, only a few approaches take advantage of the algorithms and methods proposed by the graph theory. In this paper, we aim at studying the theoretical approaches proposed in the literature for tree matching and at seeing how these approaches have been adapted to XML querying and retrieval, from both an exact and an approximate matching perspective. This study will allow us to highlight theoretical aspects of graph theory that have not been yet explored in XML retrieval

A database approach to information retrieval:The remarkable relationship between language models and region models

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