mirzal andri (12 risultati)

Taschenbuch. Condizione: Neu. Neuware -Ranking algorithms have been widely used in search engines like Google to return the most relevant and informative pages to the users. The ranking algorithms have also been utilized to characterize pages in the web network in an attempt to cluster them based on the similarity in their characteristics. However, as formulations of the algorithms depend on the link addition process, the same algorithms cannot be extended to other type of complex networks such as trading networks and online auction networks. In this monograph, we study the link addition process in trading networks, and point out the fundamental differences between web network and trading networks. Based on these differences, we formulate a family of new ranking algorithms for trading networks, and then extend them to be used for clustering purpose. Our proposed algorithms seem to be working excellently in real data sets and also are extendable as clustering methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch.

Taschenbuch. Condizione: Neu. Neuware -Clustering and latent semantic indexing (LSI) are the most common data analysis in text mining. Yet, usually these tasks are discussed separately even though both involve computing the same factors. In this book, we will treat these two seemingly different concepts as two aspects of the same mathematical formula. The standard methods in clustering and LSI produce mixed signed factors which are unintuitive since most real datasets are nonnegative. Hence, it is natural to consider the using of nonnegative matrix factorizations which can offer more interpretable results. The discussions in this book are both theoretical and practical since we give mathematical proofs for some important results and accompany our algorithms with working codes in Matlab/Octave scripts. Thus, both scholarly and practical readers can benefit from this book.Books on Demand GmbH, Überseering 33, 22297 Hamburg 152 pp. Englisch.

Paperback. Condizione: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock.

Paperback. Condizione: Brand New. 52 pages. 8.66x0.12x5.91 inches. In Stock.

Paperback. Condizione: Like New. Like New. book.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mirzal AndriAndri Mirzal received PhD and MSc in Information Sci. & Tech. from Hokkaido U., and BEng in Electrical Eng. from ITB, Indonesia. Currently, he is an Associate Professor of Information Technology at Arabian Gulf University.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mirzal AndriAndri Mirzal received PhD and MSc from Hokkaido University, Japan, and BEng from Institut Teknologi Bandung, Indonesia. His research interests include Machine Learning, Computational Intelligence, Optimization Methods, We.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Ranking algorithms have been widely used in search engines like Google to return the most relevant and informative pages to the users. The ranking algorithms have also been utilized to characterize pages in the web network in an attempt to cluster them based on the similarity in their characteristics. However, as formulations of the algorithms depend on the link addition process, the same algorithms cannot be extended to other type of complex networks such as trading networks and online auction networks. In this monograph, we study the link addition process in trading networks, and point out the fundamental differences between web network and trading networks. Based on these differences, we formulate a family of new ranking algorithms for trading networks, and then extend them to be used for clustering purpose. Our proposed algorithms seem to be working excellently in real data sets and also are extendable as clustering methods. 84 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mirzal AndriAndri Mirzal receives PhD in Information Science and Technology from Hokkaido University and B.Eng in Electrical Engineering from Bandung Institute of Technology. His research interests are in Machine Learning and Web .

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Ranking algorithms have been widely used in search engines like Google to return the most relevant and informative pages to the users. The ranking algorithms have also been utilized to characterize pages in the web network in an attempt to cluster them based on the similarity in their characteristics. However, as formulations of the algorithms depend on the link addition process, the same algorithms cannot be extended to other type of complex networks such as trading networks and online auction networks. In this monograph, we study the link addition process in trading networks, and point out the fundamental differences between web network and trading networks. Based on these differences, we formulate a family of new ranking algorithms for trading networks, and then extend them to be used for clustering purpose. Our proposed algorithms seem to be working excellently in real data sets and also are extendable as clustering methods.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Clustering and latent semantic indexing (LSI) are the most common data analysis in text mining. Yet, usually these tasks are discussed separately even though both involve computing the same factors. In this book, we will treat these two seemingly different concepts as two aspects of the same mathematical formula. The standard methods in clustering and LSI produce mixed signed factors which are unintuitive since most real datasets are nonnegative. Hence, it is natural to consider the using of nonnegative matrix factorizations which can offer more interpretable results. The discussions in this book are both theoretical and practical since we give mathematical proofs for some important results and accompany our algorithms with working codes in Matlab/Octave scripts. Thus, both scholarly and practical readers can benefit from this book. 152 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Clustering and latent semantic indexing (LSI) are the most common data analysis in text mining. Yet, usually these tasks are discussed separately even though both involve computing the same factors. In this book, we will treat these two seemingly different concepts as two aspects of the same mathematical formula. The standard methods in clustering and LSI produce mixed signed factors which are unintuitive since most real datasets are nonnegative. Hence, it is natural to consider the using of nonnegative matrix factorizations which can offer more interpretable results. The discussions in this book are both theoretical and practical since we give mathematical proofs for some important results and accompany our algorithms with working codes in Matlab/Octave scripts. Thus, both scholarly and practical readers can benefit from this book.