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Subject: Reminder: ACM Transactions on Internet Technology Special Issue on Machine Learning for the Internet Date: Wed, 20 Mar 2002 10:35:33 +0100 From: Marco Maggini maggini@DII.UNISI.IT To: ISWORLD@LISTSERV.HEANET.IE

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!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ! ! ! REMINDER ! ! Deadline for submissions is May 1 2002 ! ! ! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

******************************************* * * * CALL FOR PAPERS * * ACM Transactions on Internet Technology * * * * Special Issue on * * Machine Learning for the Internet * * * *******************************************

Machine learning methods are becoming increasingly important for the development of several internet related technologies. Tasks such as intelligent searching, organizing, retrieving, and filtering information on the Web are extremely challenging and still much too easy for humans than they are for computers, except that humans are unable to scale up with the enormous amount of available data. Explicit coding of rules in this domain is typically very hard, and even if possible, would require exceptional coordination efforts. In particular, the fast dynamics of the information available on the Internet requires new approaches for indexing. The organization of information in Internet portals is becoming hardly manageable by humans. The users' surfing of the Internet can be made easier by personalized tools like search engines optimized for a specific Web community or even for the single user. For example, finding relevant documents by querying a search engine with a set of keywords may be difficult unless a proper ranking scheme is used to order the results. In this case, techniques based on user profiles, on topic selection and on the use of the Web topology can help in defining authoritative sources of information with respect to the given query and interests.

Searching, organizing and retrieving information from the Web poses new issues that can be effectively tackled by applying machine learning techniques. Learning algorithms can be used to devise new tools which improve the accessibility to the information available on the Web. Learning is particularly useful to automate those tasks in which it is quite easy to collect examples while coding a set of explicit rules is impractical. For example, the fast dynamics of the Internet can be faced by designing new specialized search tools which cover only the parts of the Web related to a given topic. These search tools focus their exploration only on the portion of the Web which contains the information relevant for this topic. Moreover, learning-based search tools can feature a very high precision in retrieving information and can reduce the need for human efforts for many repetitive tasks (like organizing documents in Web directories).

Beside accessing information, understanding and characterizing web structure and usage is essential for future development and organization of new tools and services. In spite of several recent efforts in measuring and producing mathematical models of web connectivity, dynamics, and usage, no definitive answers have emerged and learning may play a fundamental role for advancing our understanding in this field.

Papers are invited on applications of machine learning to all aspects of Internet technology. These include (but are not limited to):

* Automated creation of web directories * Automatic extraction of information from Web pages * Automatic security management * Categorization of web pages * Design and improvement of web servers through prediction of request patterns * Focused crawling * Information retrieval for the design of thematic search engines * Models and laws that characterize the web structure * User modeling for the personalization of Web services

Submissions

Authors are requested to send an intention of submission (with authors, title and abstract) as an email message in plain text to acm-toit@dsi.unifi.it by May 1, 2002. Then, papers must be submitted in electronic format as an attachment to the same email address before May 15, 2002. Preferred formats are PDF and PostScript (compressed with gzip or zip). Manuscripts must not exceed 50 single-column, double-spaced pages (including figures and tables) and must be written in English and set in 10 or 11 point font. Please do not send papers directly to guest editors' email addresses.

Important Dates

Intention of submission: May 1, 2002 Submission deadline: May 15, 2002 Notification: August 1, 2002

Guest editors

Gary William Flake NEC Research Institute 4 Independence Way Princeton, NJ 08540 (USA) flake@research.nj.nec.com Voice: +1 609-951-2795 http://www.neci.nj.nec.com/homepages/flake/

Paolo Frasconi Dept. of Systems and Computer Science University of Florence Via di Santa Marta 3, I-50139 Firenze (Italy) paolo@dsi.unifi.it Voice: +39 055 4796 362 http://www.dsi.unifi.it/~paolo/

C. Lee Giles School of Information Sciences and Technology The Pennsylvania State University 001 Thomas Building, University Park, PA, 16802 (USA) giles@ist.psu.edu Voice: +1 814 865 7884 http://ist.psu.edu/giles/

Marco Maggini Dept. of Information Engineering University of Siena Via Roma 56, I-53100 Siena (Italy) maggini@dii.unisi.it Voice: +39 0577 233696 http://www.dii.unisi.it/~maggini/

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