30,412 research outputs found

    Beyond English text: Multilingual and multimedia information retrieval.

    Get PDF
    Non

    Optimising metadata to make high-value content more accessible to Google users

    Get PDF
    Purpose: This paper shows how information in digital collections that have been catalogued using high-quality metadata can be retrieved more easily by users of search engines such as Google. Methodology/approach: The research and proposals described arose from an investigation into the observed phenomenon that pages from the Glasgow Digital Library (gdl.cdlr.strath.ac.uk) were regularly appearing near the top of Google search results shortly after publication, without any deliberate effort to achieve this. The reasons for this phenomenon are now well understood and are described in the second part of the paper. The first part provides context with a review of the impact of Google and a summary of recent initiatives by commercial publishers to make their content more visible to search engines. Findings/practical implications: The literature research provides firm evidence of a trend amongst publishers to ensure that their online content is indexed by Google, in recognition of its popularity with Internet users. The practical research demonstrates how search engine accessibility can be compatible with use of established collection management principles and high-quality metadata. Originality/value: The concept of data shoogling is introduced, involving some simple techniques for metadata optimisation. Details of its practical application are given, to illustrate how those working in academic, cultural and public-sector organisations could make their digital collections more easily accessible via search engines, without compromising any existing standards and practices

    An analysis of the use of graphics for information retrieval

    Get PDF
    Several research groups have addressed the problem of retrieving vector graphics. This work has, however, focused either on domain-dependent areas or was based on very simple graphics languages. Here we take a fresh look at the issue of graphics retrieval in general and in particular at the tasks which retrieval systems must support. The paper presents a series of case studies which explored the needs of professionals in the hope that these needs can help direct future graphics IR research. Suggested modelling techniques for some of the graphic collections are also presented

    Special Libraries, March 1955

    Get PDF
    Volume 46, Issue 3https://scholarworks.sjsu.edu/sla_sl_1955/1002/thumbnail.jp

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

    Get PDF
    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

    Recent Developments in Cultural Heritage Image Databases: Directions for User-Centered Design

    Get PDF
    published or submitted for publicatio

    Indexing large genome collections on a PC

    Full text link
    Motivation: The availability of thousands of invidual genomes of one species should boost rapid progress in personalized medicine or understanding of the interaction between genotype and phenotype, to name a few applications. A key operation useful in such analyses is aligning sequencing reads against a collection of genomes, which is costly with the use of existing algorithms due to their large memory requirements. Results: We present MuGI, Multiple Genome Index, which reports all occurrences of a given pattern, in exact and approximate matching model, against a collection of thousand(s) genomes. Its unique feature is the small index size fitting in a standard computer with 16--32\,GB, or even 8\,GB, of RAM, for the 1000GP collection of 1092 diploid human genomes. The solution is also fast. For example, the exact matching queries are handled in average time of 39\,μ\mus and with up to 3 mismatches in 373\,μ\mus on the test PC with the index size of 13.4\,GB. For a smaller index, occupying 7.4\,GB in memory, the respective times grow to 76\,μ\mus and 917\,μ\mus. Availability: Software and Suuplementary material: \url{http://sun.aei.polsl.pl/mugi}
    corecore