Abstract. This paper focuses on a comparative evaluation of a wide-range of text categorization methods, including previously published results on the Reuters corpus and new results of additional experiments. A controlled study using three classifiers, kNN, LLSF and WORD, was conducted to examine

calculates an image plane footprint for each data sample and uses the footprint to spread the sample's energy onto the image plane. A result of the technique is that the forward mapping algorithm can support perspective without excessive cost, and support adaptive resampling of the three

, it is necessary to develop evaluation approaches and methods that credit IR methods for their ability to retrieve highly relevant documents. This can be done by extending traditional evaluation methods, i.e., recall and precision based on binary relevance assessments, to graded relevance assessments

of these decisions has important consequences for the obtained results. Recommendations that have been made in the methodological literature are discussed. Analyses of 3 existing empirical data sets are used to illustrate how questionable decisions in conducting factor analyses can yield problematic results

on the memory subsystem. As a result, care must be taken to ensure that such overheads do not exceed the benefits.

the- saurus. The evaluation results show that the the- saurus is significantly closer to WordNet than Roget Thesaurus is.

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 1 interested in comparing their results. TRECVid completed its

We present Scatter/Gather, a cluster-based document browsing method, as an alternative to ranked titles for the organization and viewing of retrieval results. We systematically evaluate Scatter/Gather in this context and find significant improvements over similarity search ranking alone

-view stereo algorithms and compare them qualitatively using a taxonomy that differentiates their key properties. We then describe our process for acquiring and calibrating multiview image datasets with high-accuracy ground truth and introduce our evaluation methodology. Finally, we present the results of our

being used to evaluate alternative proposals for front-end feature extraction. The database has been made publicly available through ELRA so that other speech researchers to evaluate and compare the performance of noise robust algorithms. Recognition results will be presented for the first standard DSR