Soni swati (35 risultati)

Condizione: New. pp. 358.

Condizione: New. pp. 358.

Condizione: New.

Condizione: New. pp. 358.

Condizione: New. In English.

Condizione: New.

Condizione: New.

Condizione: New.

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

Condizione: New. In English.

Condizione: New. In English.

Condizione: New. In English.

Condizione: New. PRINT ON DEMAND.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A large number of products are available today in various websites for trading. In order to know about the product, the seller or the manufacturer often asks their customers to share their opinions and their experiences on the products which they purchased. Unfortunately, this is a very cumbersome task to go through all review comments and to decide whether the product is up to the satisfaction level of customer or not. The main issue with these review comments is to manage all those comments and make a meaningful summarized form of review whether it represents a positive sense or feedback about the product or the negative or neutral. So, the main task is to build a dictionary of entities from these reviews. This book emphasize on making a model for Lexicon Matching using Hidden Markov Model (HMM) and Fuzzy K-Means Clustering. The outcomes of the results indicate that the trained HMM system is very promising in performing the desired tasks and achieved maximum possible precision and accuracy in case of Lexicon Matching.…

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sharaff AakankshaDr. (Mrs.) Aakanksha Sharaff, Ph.D., worked as an Assistant Professor in Computer Science & Engineering at National Institute of Technology, Raipur India. Her Research Interest are in the area of Data Mining, Text Mi. …

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Un grand nombre de produits sont aujourd'hui disponibles sur différents sites web d'échange. Afin de connaître le produit, le vendeur ou le fabricant demande souvent à ses clients de partager leurs opinions et leurs expériences sur les produits qu'ils ont achetés. Malheureusement, c'est une tâche très lourde que de passer en revue tous les commentaires et de décider si le produit est à la hauteur du niveau de satisfaction du client ou non. Le principal problème est de gérer tous ces commentaires et d'en faire un résumé significatif, qu'il s'agisse d'un avis positif ou d'un retour d'information sur le produit, ou d'un avis négatif ou neutre. La tâche principale consiste donc à construire un dictionnaire d'entités à partir de ces commentaires. Ce livre met l'accent sur la création d'un modèle de correspondance de lexique à l'aide d'un modèle de Markov caché (HMM) et d'un regroupement K-Means flou. Les résultats indiquent que le système HMM entraîné est très prometteur dans l'exécution des tâches souhaitées et atteint une précision et une exactitude maximales dans le cas de l'appariement de lexiques.…

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.