Improving Response Time by Search Pruning in a Content-Based ImageRetrieval System, Using Inverted File Techniques

Bibtex entry :

@inproceedings { VG:SMM1999c,
    author = { David McG. Squire and Henning M{\"u}ller and Wolfgang M{\"u}ller },
    title = { Improving Response Time by Search Pruning in a Content-Based ImageRetrieval System, Using Inverted File Techniques },
    booktitle = { IEEE Workshop on Content-based Access of Image and Video Libraries(CBAIVL-99) },
    pages = { 45--49 },
    year = { 1999 },
    address = { Fort Collins, Colorado, USA },
    month = { 22~June },
    url = { http://vision.unige.ch/publications/postscript/99/SquireMuellerMueller_cbaivl99.ps.gz },
    abstract = { This paper describes several methods for improving query evaluationspeed in a content-based image retrieval system (CBIRS). Responsetime is an extremely important factor in determining the usefulnessof any interactive system, as has been demonstrated by human factorsstudies over the past thirty years. In particular, response timesof less than one second are often specified as a usability requirement.It is shown that the use of inverted files facilitates the reductionof query evaluation time without significantly reducing the accuracyof the response. The performance of the system is evaluated usingprecision \vs recall graphs, which are an established evaluationmethod in information retrieval (IR), and are beginning to be usedby CBIR researchers. },
    owner = { steph },
    timestamp = { 2008.05.04 },
    url1 = { http://vision.unige.ch/publications/postscript/99/SquireMuellerMueller_cbaivl99.pdf },
    vgclass = { refpap },
    vgproject = { viper },
}
--

Keywords: machine learning, information geometry, data mining, Big Data, affective information retrieval (recherche d'information), information visualisation, content-based image and video retrieval (CBIR, CBR, CBVR, CBMR, CBMIR), information mining, classification, multimedia and multimodal information management, semantic web, knowledge base (RDF, OWL, XML, metadata, auto-annotation, description), multimodal information fusion