This paper describes an evaluation of the Kea automatic keyphrase extraction algorithm. Tools that automatically identify keyphrases are desirable because document keyphrases have numerous applications in digital library systems, but are costly and time consuming to manually assign. Keyphrase extraction algorithms are usually evaluated by comparison to author-specified keywords, but this method...

Content-Based Image Retrieval has been a major area of research in recent years. Efficient image retrieval with high precision would require an approach which combines usage of both the color and texture features of the image. In this paper we propose a method for enhancing the capabilities of texture based feature extraction and further demonstrate the use of these enhanced texture features in...

|We introduce a novel method of feature extraction for texture segmentation that relies on multi-channel wavelet frames and two-dimensional envelope detection. We describe and compare two algorithms for envelope detection based on (1) the Hilbert transform and (2) zero-crossings. We present criteria for lter selection and discuss quantitatively their e ect on feature extraction. The performance...

abstract: aqueous enzymatic extraction of oil from pistacia khinjuk was performed using cellulase. the central composite design was used to optimize the parameters that are significant to the process. the influence of three regressors on the percentage of oil recovery from seed was evaluated using second-order polynomial multiple regression model. analysis of variance showed a high coefficient ...

image retrieval is an important research field which has received great attention in the last decades. in this paper, we present an approach for the image retrieval based on the combination of text-based and content-based features. for text-based features, keywords and for content-based features, color and texture features have been used. query in this system contains some keywords and an input...

The paper shows that there is no finite set of forbidden minors which characterizes classes of independence models that are representable by Gaussian, discrete and binary distributions, respectively. In addition, a way to prove the nonexistence of a finite characterization for any other class of independence models is suggested. MSC 2000: 60A99, 68T30, 94A15