An application of linear programming to rational approximation

Kaufman, E. H.; Taylor, G. D.

doi:10.1216/rmj-1974-4-2-371

Cited by 55 publications

(56 citation statements)

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“…Various Challenges In [6] we can see an effective HiWE model where the crawler first built an internal representation of searches and then further representation in a vector form. Further the match algorithm compares the internal form representation and current contents and hence assigning a value assignment and then the response is stored in the repository.…”

Section: Amentioning

confidence: 99%

Generating Queries to Crawl Hidden Web Using Keyword Sampling and Random Forest Classifier

Rohatgi

Kundu

2017

ijarcs

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Abstract:One of the most challenging aspects in information retrieval systems is to crawl and index deep web. A deep web is part of World Wide Web which is not visible publically and therefore can't be indexed. There is a huge amount of scholarly data, images and videos available in deep web which if indexed can serve purpose of research and stop illegal activities. We propose an efficient hidden web crawler that uses Sampling and Associativity Rules in order to find the most important and relevant keywords which are used to generate queries that can extract information from databases and web forms. Further, we use random forest technique to index out search results. Our web crawler has capabilities to efficiently overcome various prior challenges that we have stated in this paper.

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Section: Amentioning

confidence: 99%

Generating Queries to Crawl Hidden Web Using Keyword Sampling and Random Forest Classifier

Rohatgi

Kundu

2017

ijarcs

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“…Brown [3] and improved by M. S. Henry and S. E. Weinstein [4]. These approximations will be compared to the differential correction algorithm when used as a method of surface fitting as given in Kaufman and Taylor [5].…”

Section: Grammedmentioning

confidence: 99%

“…The program we used for the differential correction algorithm was written by E. H. Kaufman, Jr. and G. D. Taylor [5]. This program can also be used to obtain a surface fitting approximation of F on a finite set of grid points contained in D.…”

Section: Grammedmentioning

confidence: 99%

Comparison of Algorithms for Multivariate Rational Approximation

Henry¹

1977

Mathematics of Computation

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Abstract.Let F be a continuous real-valued function defined on the unit square [-1,11 x [-1, 1]. When developing the rational product approximation to F, a certain type of discontinuity may arise. We develop a variation of a known technique to overcome this discontinuity so that the approximation can be programmed.Rational product approximations to F have been computed using both the second algorithm of Remez and the differential correction algorithm. A discussion of the differences in errors and computing time for each of these algorithms is presented and compared with the surface fit approximation also obtained using the differential correction algorithm.

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“…Experimental results show an average script-line identification accuracy of 97.52%. Two different approaches have been proposed in [6] for script identification at the word level, from a bilingual document containing Roman and Tamil scripts. In the first approach, words are divided into three distinct spatial zones.…”

Section: Introductionmentioning

confidence: 99%

A Multiple Feature based Novel Approach for Identification of Printed Indian Scripts at Word Level

Prasad¹,

Singh²,

Kumar³

2014

IJCA

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In a country like India where different scripts are in use, automatic identification of printed script facilitates many important applications such as automatic transcription of multilingual documents and for the selection of script specific OCR in a multilingual environment. In this paper a novel method to identify the script type of the collection of documents printed in seven Indian languages at word level is proposed. These languages are Bangla, Hindi, English, Malayalam, Oriya, Tamil and Kannada. The recognition is based upon multiple features extracted using Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). Script classification performance is analyzed using the Knearest neighbor classifier by comparing the majority of voting's between the outputs of DCT and DWT based methods. The proposed scheme utilizes the strength of both the DCT and DWT based features. The results of experimentation found the overall accuracy to be 98.11 % which show the superiority of the proposed multiple features based scheme over several existing schemes of script identification.

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An application of linear programming to rational approximation

Cited by 55 publications

References 1 publication

Generating Queries to Crawl Hidden Web Using Keyword Sampling and Random Forest Classifier

Generating Queries to Crawl Hidden Web Using Keyword Sampling and Random Forest Classifier

Comparison of Algorithms for Multivariate Rational Approximation

A Multiple Feature based Novel Approach for Identification of Printed Indian Scripts at Word Level

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