Product Type
Condition
Binding
Collectible Attributes
Free Shipping
Seller Location
Seller Rating
Published by Atlantic Publishers and Distributors, 2019
ISBN 10: 8126922648ISBN 13: 9788126922642
Seller: Books Puddle, New York, NY, U.S.A.
Book
Condition: New. pp. 222.
Published by Khanna Publishing House, 2019
ISBN 10: 9382609814ISBN 13: 9789382609810
Seller: Books Puddle, New York, NY, U.S.A.
Book
Condition: New. pp. 300.
Published by Atlantic Publishers and Distributors, 2019
ISBN 10: 8126922648ISBN 13: 9788126922642
Seller: Majestic Books, Hounslow, United Kingdom
Book
Condition: New. pp. 222.
Published by Khanna Publishing House, 2019
ISBN 10: 9382609814ISBN 13: 9789382609810
Seller: Majestic Books, Hounslow, United Kingdom
Book
Condition: New. pp. 300.
Published by Atlantic, 2016
ISBN 10: 8126922656ISBN 13: 9788126922659
Seller: Books in my Basket, New Delhi, India
Book
Soft cover. Condition: New. ISBN:9788126922659,222pp.
Published by Atlantic, 2019
ISBN 10: 8126922648ISBN 13: 9788126922642
Seller: Books in my Basket, New Delhi, India
Book
Hardcover. Condition: New. ISBN:9788126922642,222pp.
Published by Atlantic, 2016
ISBN 10: 8126922656ISBN 13: 9788126922659
Seller: Kanic Books, London, LONDO, United Kingdom
Book
Condition: New. Ship within 24hrs. Satisfaction 100% guaranteed. I Ships from multiple Locations I "Special Note" We do not Provide Service On APO & PO BOX Box addresses. Delivery with In 7-14 working Day Only. This Books ship from the United Kingdom & USA other locations in India depending on your location and availability.
Published by Atlantic, 2019
ISBN 10: 8126922648ISBN 13: 9788126922642
Seller: Kanic Books, London, LONDO, United Kingdom
Book
Condition: New. Ship within 24hrs. Satisfaction 100% guaranteed. I Ships from multiple Locations I "Special Note" We do not Provide Service On APO & PO BOX Box addresses. Delivery with In 7-14 working Day Only. This Books ship from the United Kingdom & USA other locations in India depending on your location and availability.
Published by Khanna Publishing House, 2019
ISBN 10: 9382609814ISBN 13: 9789382609810
Seller: GF Books, Inc., Hawthorne, CA, U.S.A.
Book
Condition: New. Book is in NEW condition. 0.93.
Published by Anchor Academic Publishing Jan 2017, 2017
ISBN 10: 3960671040ISBN 13: 9783960671046
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Book Print on Demand
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With the opening of the Indian economy, many multinational corporations are shifting their manufacturing base to India. This includes setting up green field projects or acquiring established business firms of India. The region of this business unit is expanding globally. The variety and size of the customer base is expanding and the business risk related to bad debts is increasing. Close monitoring and analysis of payment trends helps to predict customer behavior and predict the chances of customer financial strength.The present manufacturing companies generate and store tremendous amount of data. The amount of data is so huge that manual analysis of the data is difficult. This creates a great demand for data mining to extract useful information buried within these data sets. One of the major concerns that affect companies' investments and profitability is bad debts; this can be reduced by identifying past customer behavior and reaching the suitable payment terms. The Clustering and Prediction module was implemented in WEKA - a free open source software written in Java. This study model can be extended to the development of a general purpose software package to predict payment trends of customers in any organisation. 76 pp. Englisch.
Published by Anchor Academic Publishing, 2017
ISBN 10: 3960671040ISBN 13: 9783960671046
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Book
Condition: New.
Published by Anchor Academic Publishing, 2017
ISBN 10: 3960671040ISBN 13: 9783960671046
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
Book Print on Demand
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by Khanna Publisher, 2018
ISBN 10: 938617359XISBN 13: 9789386173591
Seller: dsmbooks, Liverpool, United Kingdom
Book
Paperback. Condition: New. New. book.
Published by Anchor Academic Publishing, 2017
ISBN 10: 3960671040ISBN 13: 9783960671046
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Book Print on Demand
Condition: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Published by Anchor Academic Publishing, 2017
ISBN 10: 3960671040ISBN 13: 9783960671046
Seller: AHA-BUCH GmbH, Einbeck, Germany
Book Print on Demand
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - With the opening of the Indian economy, many multinational corporations are shifting their manufacturing base to India. This includes setting up green field projects or acquiring established business firms of India. The region of this business unit is expanding globally. The variety and size of the customer base is expanding and the business risk related to bad debts is increasing. Close monitoring and analysis of payment trends helps to predict customer behavior and predict the chances of customer financial strength.The present manufacturing companies generate and store tremendous amount of data. The amount of data is so huge that manual analysis of the data is difficult. This creates a great demand for data mining to extract useful information buried within these data sets. One of the major concerns that affect companies' investments and profitability is bad debts; this can be reduced by identifying past customer behavior and reaching the suitable payment terms. The Clustering and Prediction module was implemented in WEKA - a free open source software written in Java. This study model can be extended to the development of a general purpose software package to predict payment trends of customers in any organisation.
Published by Anchor Academic Publishing Nov 2016, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Book Print on Demand
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Web Usage Mining, also known as Web Log Mining, is the result of user interaction with a Web server including Web logs, click streams and database transaction or the visits of search engine crawlers at a Website. Log files provide an immense source of information about the behavior of users as well as search engine crawlers. Web Usage Mining concerns the usage of common browsing patterns, i.e. pages requested in sequence from Web logs. These patterns can be utilized to enhance the design and modification of a Website. Analyzing and discovering user behavior is helpful for understanding what online information users inquire and how they behave. The analyzed result can be used in intelligent online applications, refining Websites, improving search accuracy when seeking information and lead decision makers towards better decisions in changing markets, for instance by putting advertisements in ideal places. Similarly, the crawlers or spiders are accessing the Websites to index new and updated pages. These traces help to analyze the behavior of search engine crawlers.The log files are unstructured files and of huge size. These files need to be extracted and pre-processed before any data mining functionality to follow. Pre-processing is done in unique ways for each application. Two pre-processing algorithms are proposed based on indiscernibility relations in rough set theory which generates Equivalence Classes. The first algorithm generates a pre-processed file with successful user requests while the second one generates a pre-processed file for pre-fetching and caching purposes. Two algorithms are proposed to extract usage analytics. The first algorithm identifies the origin of visits, the top referring sites and the most popular keywords used by the visitor to arrive at a Website. The second algorithm extracts user agents like browsers and operating systems used by a visitor to access a Website.In this study, clustering of users based on Entry Pages to a Website is done to analyze the deep linked traffic at a Website. The Top Ten Entry Pages, the traffic and the temporal information of the Top Ten Entry Pages are also studied. 212 pp. Englisch.
Published by Anchor Academic Publishing 2017-01, 2017
ISBN 10: 3960671040ISBN 13: 9783960671046
Seller: Chiron Media, Wallingford, United Kingdom
Book
PF. Condition: New.
Published by Anchor Academic Publishing, 2017
ISBN 10: 3960671040ISBN 13: 9783960671046
Seller: Buchpark, Trebbin, Germany
Book
Condition: Sehr gut. Zustand: Sehr gut - Gepflegter, sauberer Zustand. Innen: Seiten vergilbt. | Seiten: 76.
Published by Anchor Academic Publishing 2016-11, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: Chiron Media, Wallingford, United Kingdom
Book
PF. Condition: New.
Published by Anchor Academic Publishing, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: AHA-BUCH GmbH, Einbeck, Germany
Book Print on Demand
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Web Usage Mining, also known as Web Log Mining, is the result of user interaction with a Web server including Web logs, click streams and database transaction or the visits of search engine crawlers at a Website. Log files provide an immense source of information about the behavior of users as well as search engine crawlers. Web Usage Mining concerns the usage of common browsing patterns, i.e. pages requested in sequence from Web logs. These patterns can be utilized to enhance the design and modification of a Website. Analyzing and discovering user behavior is helpful for understanding what online information users inquire and how they behave. The analyzed result can be used in intelligent online applications, refining Websites, improving search accuracy when seeking information and lead decision makers towards better decisions in changing markets, for instance by putting advertisements in ideal places. Similarly, the crawlers or spiders are accessing the Websites to index new and updated pages. These traces help to analyze the behavior of search engine crawlers.The log files are unstructured files and of huge size. These files need to be extracted and pre-processed before any data mining functionality to follow. Pre-processing is done in unique ways for each application. Two pre-processing algorithms are proposed based on indiscernibility relations in rough set theory which generates Equivalence Classes. The first algorithm generates a pre-processed file with successful user requests while the second one generates a pre-processed file for pre-fetching and caching purposes. Two algorithms are proposed to extract usage analytics. The first algorithm identifies the origin of visits, the top referring sites and the most popular keywords used by the visitor to arrive at a Website. The second algorithm extracts user agents like browsers and operating systems used by a visitor to access a Website.In this study, clustering of users based on Entry Pages to a Website is done to analyze the deep linked traffic at a Website. The Top Ten Entry Pages, the traffic and the temporal information of the Top Ten Entry Pages are also studied.
Published by Anchor Academic Publishing, 2017
ISBN 10: 3960671040ISBN 13: 9783960671046
Seller: moluna, Greven, Germany
Book Print on Demand
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. With the opening of the Indian economy, many multinational corporations are shifting their manufacturing base to India. This includes setting up green field projects or acquiring established business firms of India. The region of this business unit is expan.
Published by Anchor Academic Publishing, 2017
ISBN 10: 3960671040ISBN 13: 9783960671046
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Book Print on Demand
PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by Anchor Academic Publishing, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: GF Books, Inc., Hawthorne, CA, U.S.A.
Book
Condition: New. Book is in NEW condition. 0.57.
Published by Anchor Academic Publishing, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
Book Print on Demand
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by Anchor Academic Publishing, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Book
Condition: New.
Published by Anchor Academic Publishing, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Book Print on Demand
Condition: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book.
Published by Anchor Academic Publishing, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Book Print on Demand
PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by Anchor Academic Publishing, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: Books Unplugged, Amherst, NY, U.S.A.
Book
Condition: Good. Buy with confidence! Book is in good condition with minor wear to the pages, binding, and minor marks within 0.57.
Published by Anchor Academic Publishing, 2016
ISBN 10: 3960670877ISBN 13: 9783960670872
Seller: Book Deals, Tucson, AZ, U.S.A.
Book
Condition: New. New! This book is in the same immaculate condition as when it was published 0.57.