This paper explores in detail new image enhancement techniques for assessing tuft geometry and concomitant appearance changes in new and worn carpets. Using im proved algorithms and more advanced tuft geometry, saxony tufted carpets of nylon and polyester BCF yams are capable of being extensively and reliably characterized as to texture and changes in appearance with laboratory or floor wear. While still using a relatively low resolution grey level imaging system, the newly developed al gorithms demonstrate how tuft size distribution, number of tufts, evenness of tuft spatial distribution, and aspect ratio (shape factor) of tufts can be objectively measured. Statistical analysis confirms that customary wear levels, and their visual appearance change in carpet, can be separated and correctly grouped by these new techniques. Some limitations of these and other texture-sensitive image analysis techniques are also discussed.
Electronic mail poses a number of unusual challenges for the design of information retrieval systems and test collections, including informal expression, conversational structure, variable document granularity (e.g., messages, threads, or longer-term interactions), a naturally occuring integration between free text and structural metadata, and incompletely characterized user needs. This paper reports on initial experiments with a large collection of public mailing lists from the World Wide Web consortium that will be used for the TREC 2005 Enterprise Search Track. Automatic subject-line threading and removal of duplicated text were found to have little effect in a small pilot study. Those observations motivated development of a question typology and more detailed analysis of collection characteristics; preliminary results for both are reported.
This article reports the method of enriching a thesaurus by differentiating the related term relationship with specific semantic relations and expanding related terms. It also tests the usefulness of an enriched thesaurus as a better question-answering tool and information retrieval aid based on users’ perceptions. A small portion of the Education Resources Information Center (ERIC) thesaurus was enriched, and two enriched mini-thesauri were compiled with different levels of detail. A total of 22 participants were recruited to test the usefulness of the three mini-thesauri for facilitating question-answering and information retrieval within the ERIC Abstracts of the EBSCOHost Database and on the Web using Google. The experimental results suggest that the enriched thesauri are better question-answering tools and information retrieval aids than the original thesaurus. The findings imply that thesauri enriched with semantic relations are useful in question-answering and modern information retrieval, although the role of the traditional thesaurus in modern information retrieval has diminished.
This paper explores topic aspect (i.e., subtopic or facet) classification for English and Chinese collections. The evaluation model assumes a bilingual user who has found documents on a topic and identified a few passages in each language on aspects of that topic. Additional passages are then automatically labeled using a k-Nearest-Neighbor classifier and local (i.e., result set) Latent Semantic Analysis. Experiments show that when few training examples are available in either language, classification using training examples from both languages can often achieve higher effectiveness than using training examples from just one language. When the total number of training examples is held constant, classification effectiveness correlates positively with the fraction of same-language training examples in the training set. These results suggest that supervised classification can benefit from hand-annotating a few same-language examples, and that when performing classification in bilingual collections it is useful to label some examples in each language.
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