Dear Mr Resende, i welcome your announcement of a new book, titled HANBOOK OF MASSIVE DATA SETS as a court expert in information science, co-founder of world's first virtual corporation (internet based corporation) Globewide Network Academy Inc., Texas and ex-director of lecal chapter of Global University i would like to review your book.
Frankly speaking i am aware of the state-of-the-art in massive data sets management, especially information retrieval on the Web. So please tell me, what problems lie behing Internet Web Search Engines working so badly. Just name me one or two web search engines retrieving relevant information only from the Internet. First, let's go to "Did you mean" from Altavista search engine search for "sssss" response: Did you mean: "sss" no, i didn't , i meant "sssss" search for "wwwwww" response: Did you mean "www www" no, i didn't, i meant "wwwwww" search for "ssssss" response: Did you mean "sss sss" no, i didn't, i meant "ssssss" search for "@", "@@", "@@@", .... response: We found 0 results. Suggestions: - Check your spelling. - Try different or fewer keywords. - Remove quotation marks or plus signs. - Search for @ in: Images Video MP3/Audio News Sorry. Altavista was first choice, as First Part of your Book: Algorithmic Aspects of Information Retrieval on the Web comes from Mr. Broder from Altavista Andrei Broder and Monika Henzinger But we can go to any known web/internet/usenet search engines. So please send me your book for review. greetings, Dariusz Jacek "Mauricio G. C. Resende" wrote: > > >>>>>>>>>Sorry for multiple postings<<<<<<<<< > ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ > > Dear Colleague, > > We are pleased to announce a new book, titled > > HANDBOOK OF MASSIVE DATA SETS > > Edited by James Abello, Panos M. Pardalos, and Mauricio G. C. Resende. > > Published in May 2002 by Kluwer Academic Publishers, Dordrecht. > > Check the link: http://www.research.att.com/~mgcr/hmds.html for > table of contents, abstracts, list of contributors, and ordering > information. > > PREFACE > > The proliferation of massive data sets brings with it a series of special > computational challenges. This "data avalanche" arises in a wide range > of scientific and commercial applications. With advances in computer > and information technologies, many of these challenges are beginning to > be addressed by diverse inter-disciplinary groups, that include computer > scientists, mathematicians, statisticians and engineers, working in close > cooperation with application domain experts. High profile applications > include astrophysics, bio-technology, demographics, finance, geographical > information systems, government, medicine, telecommunications, the > environment and the internet. > > John R. Tucker of the Board on Mathematical Sciences has stated: > > "My interest in this problem (Massive Data Sets) is that I see it > as the most important cross-cutting problem for the mathematical > sciences in practical problem solving for the next decade, because > it is so pervasive.'' > > The Handbook of Massive Data Sets is comprised of articles written by > experts on selected topics that deal with some major aspect of massive > data sets. It contains chapters on information retrieval both in the > internet and in the traditional sense, web crawlers, massive graphs, > string processing, data compression, clustering methods, wavelets, > optimization, external memory algorithms and data structures, the US > national cluster project, high performance computing, data warehouses, > data cubes, semi-structured data, data squashing, data quality, billing > in the large, fraud detection, and data processing in astrophysics, > air pollution, biomolecular data, earth observation and the environment. > > We would like to take the opportunity to thank the authors of the > chapters, the anonymous referees, AT&T Labs Research, and the Center > for Applied Optimization, University of Florida for supporting this > effort. The first editor wants to express his appreciation to Dave > Belanger for his continued support. Special thanks and appreciation go > to Dr. Hong-Xuan Huang for assisting us with LaTeX and other issues in > the preparation of the camera-ready copy of this handbook. Finally, we > would like to thank the Kluwer Academic Publishers for their assistance. > > ------------------------------------------------------------------------- > Handbook of Massive Data Sets > Kluwer Academic Publishers > [EMAIL PROTECTED] > > James Abello (Information Visualization Research Department, AT&T Labs > Research, Shannon Laboratory, 180 Park Avenue, Florham Park, NJ 07932 > USA, [EMAIL PROTECTED]) > > Panos M. Pardalos (Center for Applied Optimization, ISE Department, > 303 Weil Hall, University of Florida, Gainesville, FL 32605 USA, > [EMAIL PROTECTED]) > > Mauricio G. C. Resende (Algorithms and Optimization Research Department, > AT&T Labs Research, Shannon Laboratory, 180 Park Avenue, Florham Park, > NJ 07932 USA, [EMAIL PROTECTED]) > > Editors > ------------------------------------------------------------------------- > > Check the link: http://www.research.att.com/~mgcr/hmds.html for > table of contents, abstracts, list of contributors, and ordering > information. -- True Shape Self(EGO) Nesting Technology world-wide. Inquiries should be e-mailed to: [EMAIL PROTECTED] . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
