Content-Aware DataGuides for Indexing Large Collections of XML Documents

XML is well-suited for modelling structured data with textual content. However, most indexing approaches perform structure and content matching independently, combining the retrieved path and keyword occurrences in a third step. This paper shows that retrieval in XML documents can be accelerated significantly by processing text and structure simultaneously during all retrieval phases. To this end, the Content-Aware DataGuide (CADG) enhances the wellknown DataGuide with (1) simultaneous keyword and path matching and (2) a precomputed content/structure join. Extensive experiments prove the CADG to be 50-90% faster than the DataGuide for various sorts of query and document, including difficult cases such as poorly structured queries and recursive document paths. A new query classification scheme identifies precise query characteristics with a predominant influence on the performance of the individual indices. The experiments show that the CADG is applicable to many real-world applications, in particular large collections of heterogeneously structured XML documents

Accessing Information Based on a Combination of Document Structure and Content: Exploiting XML tags in indexing and searching to enhance content retrieval of online document-centric XML encoded texts

This study explores the challenges of using traditional information retrieval methods to retrieve document-centric XML encoded text. It demonstrates how coupling structure and content in query and index formulation improves retrieval performance. Native XML database (NXD) and search engine technologies were evaluated in a baseline experiment, and in a second test after alterations were made to their respective indexes. Documents were retrieved for simple and complex forms of 30 XPath and keyword queries from a corpus of 95 XML/TEI encoded texts. Overall results indicated that query augmentation using document structure improves retrieval performance. Complex queries submitted to the NXD produced the most satisfying results, with an average precision of 93.3% and an average recall of 86.3%. Performance improvements were also achieved using complex, structured queries and indexes in the search engine. Study findings suggest that effective XML retrieval models might result from a combination of unstructures and structured retrieval techniques

Visual exploration and retrieval of XML document collections with the generic system X2

This article reports on the XML retrieval system X2 which has been developed at the University of Munich over the last five years. In a typical session with X2, the user first browses a structural summary of the XML database in order to select interesting elements and keywords occurring in documents. Using this intermediate result, queries combining structure and textual references are composed semiautomatically. After query evaluation, the full set of answers is presented in a visual and structured way. X2 largely exploits the structure found in documents, queries and answers to enable new interactive visualization and exploration techniques that support mixed IR and database-oriented querying, thus bridging the gap between these three views on the data to be retrieved. Another salient characteristic of X2 which distinguishes it from other visual query systems for XML is that it supports various degrees of detailedness in the presentation of answers, as well as techniques for dynamically reordering and grouping retrieved elements once the complete answer set has been computed

Exploiting Query Structure and Document Structure to Improve Document Retrieval Effectiveness

In this paper we present a systematic analysis of document retrieval using unstructured and structured queries within the score region algebra (SRA) structured retrieval framework. The behavior of di®erent retrieval models, namely Boolean, tf.idf, GPX, language models, and Okapi, is tested using the transparent SRA framework in our three-level structured retrieval system called TIJAH. The retrieval models are implemented along four elementary retrieval aspects: element and term selection, element score computation, score combination, and score propagation. The analysis is performed on a numerous experiments evaluated on TREC and CLEF collections, using manually generated unstructured and structured queries. Unstructured queries range from the short title queries to long title + description + narrative queries. For generating structured queries we exploit the knowledge of the document structure and the content used to semantically describe or classify documents. We show that such structured information can be utilized in retrieval engines to give more precise answers to user queries then when using unstructured queries

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

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

A Database Approach to Content-based XML retrieval

This paper describes a rst prototype system for content-based retrieval from XML data. The system's design supports both XPath queries and complex information retrieval queries based on a language modelling approach to information retrieval. Evaluation using the INEX benchmark shows that it is beneficial if the system is biased to retrieve large XML fragments over small fragments