Evaluation of effective XML information retrieval

XML is being adopted as a common storage format in scientific data repositories, digital libraries, and on the World Wide Web. Accordingly, there is a need for content-oriented XML retrieval systems that can efficiently and effectively store, search and retrieve information from XML document collections. Unlike traditional information retrieval systems where whole documents are usually indexed and retrieved as information units, XML retrieval systems typically index and retrieve document components of varying granularity. To evaluate the effectiveness of such systems, test collections where relevance assessments are provided according to an XML-specific definition of relevance are necessary. Such test collections have been built during four rounds of the INitiative for the Evaluation of XML Retrieval (INEX). There are many different approaches to XML retrieval; most approaches either extend full-text information retrieval systems to handle XML retrieval, or use database technologies that incorporate existing XML standards to handle both XML presentation and retrieval. We present a hybrid approach to XML retrieval that combines text information retrieval features with XML-specific features found in a native XML database. Results from our experiments on the INEX 2003 and 2004 test collections demonstrate the usefulness of applying our hybrid approach to different XML retrieval tasks. A realistic definition of relevance is necessary for meaningful comparison of alternative XML retrieval approaches. The three relevance definitions used by INEX since 2002 comprise two relevance dimensions, each based on topical relevance. We perform an extensive analysis of the two INEX 2004 and 2005 relevance definitions, and show that assessors and users find them difficult to understand. We propose a new definition of relevance for XML retrieval, and demonstrate that a relevance scale based on this definition is useful for XML retrieval experiments. Finding the appropriate approach to evaluate XML retrieval effectiveness is the subject of ongoing debate within the XML information retrieval research community. We present an overview of the evaluation methodologies implemented in the current INEX metrics, which reveals that the metrics follow different assumptions and measure different XML retrieval behaviours. We propose a new evaluation metric for XML retrieval and conduct an extensive analysis of the retrieval performance of simulated runs to show what is measured. We compare the evaluation behaviour obtained with the new metric to the behaviours obtained with two of the official INEX 2005 metrics, and demonstrate that the new metric can be used to reliably evaluate XML retrieval effectiveness. To analyse the effectiveness of XML retrieval in different application scenarios, we use evaluation measures in our new metric to investigate the behaviour of XML retrieval approaches under the following two scenarios: the ad-hoc retrieval scenario, exploring the activities carried out as part of the INEX 2005 Ad-hoc track; and the multimedia retrieval scenario, exploring the activities carried out as part of the INEX 2005 Multimedia track. For both application scenarios we show that, although different values for retrieval parameters are needed to achieve the optimal performance, the desired textual or multimedia information can be effectively located using a combination of XML retrieval approaches

Evaluation campaigns and TRECVid

The TREC Video Retrieval Evaluation (TRECVid) is an international benchmarking activity to encourage research in video information retrieval by providing a large test collection, uniform scoring procedures, and a forum for organizations interested in comparing their results. TRECVid completed its fifth annual cycle at the end of 2005 and in 2006 TRECVid will involve almost 70 research organizations, universities and other consortia. Throughout its existence, TRECVid has benchmarked both interactive and automatic/manual searching for shots from within a video corpus, automatic detection of a variety of semantic and low-level video features, shot boundary detection and the detection of story boundaries in broadcast TV news. This paper will give an introduction to information retrieval (IR) evaluation from both a user and a system perspective, highlighting that system evaluation is by far the most prevalent type of evaluation carried out. We also include a summary of TRECVid as an example of a system evaluation benchmarking campaign and this allows us to discuss whether such campaigns are a good thing or a bad thing. There are arguments for and against these campaigns and we present some of them in the paper concluding that on balance they have had a very positive impact on research progress

Large scale evaluations of multimedia information retrieval: the TRECVid experience

Information Retrieval is a supporting technique which underpins a broad range of content-based applications including retrieval, filtering, summarisation, browsing, classification, clustering, automatic linking, and others. Multimedia information retrieval (MMIR) represents those applications when applied to multimedia information such as image, video, music, etc. In this presentation and extended abstract we are primarily concerned with MMIR as applied to information in digital video format. We begin with a brief overview of large scale evaluations of IR tasks in areas such as text, image and music, just to illustrate that this phenomenon is not just restricted to MMIR on video. The main contribution, however, is a set of pointers and a summarisation of the work done as part of TRECVid, the annual benchmarking exercise for video retrieval tasks

Investigating the document structure as a source of evidence for multimedia fragment retrieval

International audienceMultimedia objects can be retrieved using their context that can be for instance the text surrounding them in documents. This text may be either near or far from the searched objects. Our goal in this paper is to study the impact, in term of effectiveness, of text position relatively to searched objects. The multimedia objects we consider are described in structured documents such as XML ones. The document structure is therefore exploited to provide this text position in documents. Although structural information has been shown to be an effective source of evidence in textual information retrieval, only a few works investigated its interest in multimedia retrieval. More precisely, the task we are interested in this paper is to retrieve multimedia fragments (i.e. XML elements having at least one multimedia object). Our general approach is built on two steps: we first retrieve XML elements containing multimedia objects, and we then explore the surrounding information to retrieve relevant multimedia fragments. In both cases, we study the impact of the surrounding information using the documents structure.Our work is carried out on images, but it can be extended to any other media, since the physical content of multimedia objects is not used. We conducted several experiments in the context of the Multimedia track of the INEX evaluation campaign. Results showed that structural evidences are of high interest to tune the importance of textual context for multimedia retrieval. Moreover, the proposed approach outperforms state of the art approaches

Report on the first Twente Data Management Workshop on XML Databases and Information Retrieval

The Database Group of the University of Twente initiated a new series of workshops called Twente Data Management workshops (TDM), starting with one on XML Databases and Information Retrieval which took place on 21 June 2004 at the University of Twente. We have set ourselves two goals for the workshop series: i) To provide a forum to share original ideas as well as research results on data management problems; ii) To bring together researchers from the database community and researchers from related research fields

The Wikipedia Image Retrieval Task

The wikipedia image retrieval task at ImageCLEF provides a testbed for the system-oriented evaluation of visual information retrieval from a collection of Wikipedia images. The aim is to investigate the effectiveness of retrieval approaches that exploit textual and visual evidence in the context of a large and heterogeneous collection of images that are searched for by users with diverse information needs. This chapter presents an overview of the available test collections, summarises the retrieval approaches employed by the groups that participated in the task during the 2008 and 2009 ImageCLEF campaigns, provides an analysis of the main evaluation results, identifies best practices for effective retrieval, and discusses open issues

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

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Multimedia search without visual analysis: the value of linguistic and contextual information

This paper addresses the focus of this special issue by analyzing the potential contribution of linguistic content and other non-image aspects to the processing of audiovisual data. It summarizes the various ways in which linguistic content analysis contributes to enhancing the semantic annotation of multimedia content, and, as a consequence, to improving the effectiveness of conceptual media access tools. A number of techniques are presented, including the time-alignment of textual resources, audio and speech processing, content reduction and reasoning tools, and the exploitation of surface features

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