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On scores in tournaments

References [1] P. Avery, Score sequences of oriented graphs, J. Graph Theory , 15, 3 (1991) 251–257. ⇒257 [2] R. A. Brualdi and J. Shen, Landau’s inequalities for tournament scores and a short proof of a Theorem on transitive sub-tournaments, J. Graph Theory , 38 (2001) 244–254. ⇒258 [3] R. A. Brualdi and J. Shen, Landau’s inequalities for tournament scores and a short proof of a Theorem on transitive sub-tournaments, J. Graph Theory , 38 (2001) 244–254. ⇒258 [4] J. R. Griggs and K. B. Reid, Landau’s theorem revisited

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Reconstruction of score sets

References [1] G. Chartrand, L. Lesniak, J. Roberts, Degree sets for digraphs, Periodica Math. Hung., 7 (1976) 77-85. ⇒212 [2] T. H. Cormen, Ch. E. Leiserson, R. L. Rivest, C. Stein, Introduction to Algorithms (third edition), The MIT Press/McGraw Hill, Cambridge/New York, 2009. ⇒216 [3] J. L. Gross, J. Yellen, P. Zhang, Handbook of Graph Theory, CRC Press, Boca Raton, FL, 2013. ⇒210 [4] M. Hager. On score sets for tournaments, Discrete Math., 58 (1986) 25-34. ⇒ 210, 212 [5] A

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On the scores and degrees in hypertournaments

[5] G. Gutin, A. Yeo, Hamiltonian paths and cycles in hypertournaments, J. Graph Theory 25 (1997), 277–286. ⇒201 [6] K. K. Kayibi, M. A. Khan, S. Pirzada, Uniform sampling of k -hypertournaments, Linear and Multilinear Algebra 61, 1 (2013), 123–138. ⇒201 [7] Y. Koh, S. Ree, On k -hypertournament matrices, Lin. Alg. Appl. 373 (2002) 183–195. ⇒202, 203 [8] M. A. Khan, S. Pirzada, K. K. Kayibii, Scores, Inequalities and regular hypertournaments, J. Math. Inequal. Appl. 15, 2 (2012) 343–351. ⇒203, 204 [9] H. G. Landau, On

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Speaker Identification Using Data-Driven Score Classification

Abstract

We present a comparative evaluation of different classification algorithms for a fusion engine that is used in a speaker identity selection task. The fusion engine combines the scores from a number of classifiers, which uses the GMM-UBM approach to match speaker identity. The performances of the evaluated classification algorithms were examined in both the text-dependent and text-independent operation modes. The experimental results indicated a significant improvement in terms of speaker identification accuracy, which was approximately 7% and 14.5% for the text-dependent and the text-independent scenarios, respectively. We suggest the use of fusion with a discriminative algorithm such as a Support Vector Machine in a real-world speaker identification application where the text-independent scenario predominates based on the findings.

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#DontTweetThis: Scoring Private Information in Social Networks

. Liu and E. Terzi. A framework for computing the privacy scores of users in online social networks. ACM Transactions on Knowledge Discovery from Data , 5(1), 2010. [46] W. Liu and D. Ruths. What’s in a name? using first names as features for gender inference in twitter. In AAAI spring symposium: Analyzing microtext , volume 13, page 01, 2013. [47] B. Luo and D. Lee. On protecting private information in social networks: a proposal. In IEEE ICME Workshop of M3SN . IEEE, 2009. [48] A. Machanavajjhala, D. Kifer, J. Gehrke, and M. Venkitasubramaniam

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Prediction of e-Learning Efficiency by Neural Networks

Abstract

A model for prediction of the outcome indicators of e-Learning, based on Balanced ScoreCard (BSC) by Neural Networks (NN) is proposed. In the development of NN models the problem of a small sample size of the data arises. In order to reduce the number of variables and increase the examples of the training sample, preprocessing of the data with the help of the methods Interpolation and Principal Component Analysis (PCA) is performed. A method for optimizing the structure of the neural network is applied over linear and nonlinear neural network architectures. The highest accuracy of prognosis is obtained applying the method of Optimal Brain Damage (OBD) over the nonlinear neural network. The efficiency and applicability of the method suggested is proved by numerical experiments on the basis of real data.

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Group Decision Making in Evaluation and Ranking of Students by Extended Simple Multi-Attribute Rating Technique

Abstract

The paper deals with evaluation and ranking of students taking into account two main criteria of the learning – theoretical knowledge and practical skills. These criteria are divided into several sub-criteria to reflect different aspects of the learning outcomes. To make such complex evaluation the proper utility function based on simple multi-attribute rating technique is proposed. This new utility function includes not only the evaluation score and weighted coefficients for criteria importance, but considers also additional coefficients that indicate how theoretical knowledge and practical skills will take part in the aggregated final assessment. The formulated model is applied for the assessing of the students on web programming. The students are ranked under three different cases where the theoretical knowledge and practical skills take different part in the aggregated assessment. The obtained results demonstrate the applicability of the described approach by providing different ranking depending on the importance of the theoretical and practical aspects.

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Summarizing News Paper Articles: Experiments with Ontology- Based, Customized, Extractive Text Summary and Word Scoring

Abstract

The method for filtering information from large volumes of text is called Information Extraction. It is a limited task than understanding the full text. In full text understanding, we express in an explicit fashion about all the information in a given text. But, in Information Extraction, we delimit in advance, as part of the specification of the task and the semantic range of the result. Only extractive summarization method is considered and developed for the study. In this article a model for summarization from large documents using a novel approach has been proposed by considering one of the South Indian regional languages (Kannada). It deals with a single document summarization based on statistical approach. The purpose of summary of an article is to facilitate the quick and accurate identification of the topic of the published document. The objective is to save prospective readers’ time and effort in finding the useful information in a given huge article. Various analyses of results were also discussed by comparing it with the English language.

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Measuring the Significance of Writing Style for Recommending Where to Publish – A Case Study

Hierarchical Classification Approach to Automated Essay Scoring. – Assessing Writing, Vol. 23 , 2015, No 1, pp. 35-39. 4. Karnalim, O. A Low-Level Structure-Based Approach for Detecting Source Code Plagiarism. – IAENG International Journal of Computer Science, Vol. 44 , 2017, No 4, pp. 501-522. 5. Wang, D., Y. Liang, D. Xu, X. Feng, R. Guan. A Content-Based Recommender System for Computer Science Publications. – Knowledge-Based Systems, Vol. 157 , 2018, No 1, pp. 1-9. 6. Beel, J., B. Gipp, S. Langer, C. Breitinger. Research-Paper Recommender Systems: A

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On linear programming duality and Landau’s characterization of tournament

References [1] G. G. Alway, Matrices and sequences, Math. Gazette 46 (1962) 208-213. ⇒21 [2] C. M. Bang, H. Sharp, An elementary proof of Moon’s theorem on generalized tournaments, J. Comb. Theory, Ser. B 22, 3 (1977) 299-301. ⇒21 [3] C. M. Bang, H. Sharp, Score vectors of tournaments, J. Comb. Theory, Ser. B 26, 1, (1979) 81-84. ⇒31 [4] A. Brauer, I. C. Gentry, K. Shaw, A new proof of a theorem by H. G. Landau on tournament matrices, J. Comb. Theory 5, 3 (1968) 289-292. ⇒21 [5] R

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