The Third International Conference on Knowledge Discovery and Data Mining

August 14–17 1997, Newport Beach, California

Sponsored by the American Association for Artificial Intelligence KDD-97: A Preview The rapid growth of data and information has created a need and an opportunity for extracting knowl- edge from databases, and both researchers and application developers have been responding to that need. Knowledge discovery in databases (KDD), also referred to as data mining, is an area of common interest to researchers in machine discovery, statistics, databases, knowledge acquisition, machine learning, data visualization, high performance computing, and knowledge-based systems. KDD applications have been developed for astronomy, biology, finance, insurance, marketing, medicine, and many other fields. The Third International Conference on Knowledge Discovery and Data Mining (KDD-97) will follow up the success of KDD-95 and KDD-96 by bringing together researchers and application devel- opers from different areas focusing on unifying themes.

Keynote Address: From Large to Huge. A Statistician’s Reactions to KDD and DM Peter Huber, Universität Bayreuth, Germany The statistics and AI communities are confronted by the same challenge, the onslaught of ever larger data collections, but the two com- munities have reacted independently and differently. What could they learn from each other if they looked over the fence? What is amiss on either side? KDD-97 Organization General Conference Chair Gregory Cooper, University of Pittsburgh Eric Mjolsness, University of California at Robert Cowell, City University, UK San Diego Ramasamy Uthurusamy, General Motors Bruce Croft, University of Massachusetts Sally Morton, Rand Corporation Corporation at Amherst Richard Muntz, University of California at William Eddy, Carnegie Mellon University Los Angeles Program Cochairs Charles Elkan, University of California at Raymond Ng, University of British David Heckerman, Microsoft Research San Diego Columbia Heikki Mannila, University of Helsinki, Usama Fayyad, Microsoft Research Steve Omohundro, NEC Research Finland Ronen Feldman, Bar-Ilan University, Israel Gregory Piatetsky-Shapiro, Daryl Pregibon, AT&T Laboratories Jerry Friedman, Stanford University GTE Laboratories Dan Geiger, Technion, Israel Daryl Pregibon, Bell Laboratories Publicity Chair Clark Glymour, Carnegie-Mellon Raghu Ramakrishnan, University of University Wisconsin, Madison Paul Stolorz, Jet Propulsion Laboratory Moises Goldszmidt, SRI International Patricia Riddle, Boeing Computer Services Georges Grinstein, University of Ted Senator, NASD Regulation Inc. Tutorial Chair Massachusetts, Lowell Jude Shavlik, University of Wisconsin at Padhraic Smyth, University of California, Jiawei Han, Simon Fraser University, Madison Irvine Canada Wei-Min Shen, University of Southern David Hand, Open University, UK California Demo and Trevor Hastie, Stanford University Arno Siebes, CWI, Netherlands David Heckerman, Microsoft Corporation Avi Silberschatz, Bell Laboratories Poster Sessions Chair Haym Hirsh, Rutgers University Evangelos Simoudis, IBM Almaden Tej Anand, NCR Corporation Jim Hodges, University of Minnesota Research Center Se June Hong, IBM T .J. Watson Research Andrzej Skowron, University of Warsaw Awards Chair Center Padhraic Smyth, University of California Tomasz Imielinski, Rutgers University at Irvine Gregory Piatetsky-Shapiro, Yannis Ioannidis, University of Wisconsin Ramakrishnan Srikant, IBM Almaden GTE Laboratories Lawrence D. Jackel, AT&T Laboratories Research Center David Jensen, University of Massachusetts John Stasko, Georgia Institute of Technology Program Committee Members Michael Jordan, Massachusetts Institute of Salvatore J. Stolfo, Columbia University Helena Ahonen, University of Helsinki Technology Paul Stolorz, Jet Propulsion Laboratory Tej Anand, NCR Daniel Keim, University of Munich Hanna Toivonen, University of Helsinki Ron Brachman, AT&T Laboratories Willi Kloesgen, GMD, Germany Alexander Tuzhilin, New York University, Carla Brodley, Purdue University Ronny Kohavi, Silicon Graphics Stern School Dan Carr, George Mason University David D. Lewis, AT&T Laboratories – Ramasamy Uthurusamy, General Motors Peter Cheeseman, Research R&D Center NASA AMES Research Center David Madigan, University of Washington Graham Wills, Bell Laboratories David Cheung, University of Hong Kong Heikki Mannila, University of Helsinki David Wolpert, IBM Almaden Research Wesley Chu, University of California at Brij Masand, GTE Laboratories Center Los Angeles Gary McDonald, General Motors Research Jan Zytkow, Wichita State University

2 KDD–97 KDD-97 Tutorial Program All tutorials will be presented on Thursday, August 14, 1997. The times listed below are tentative. Admission to the tutorials is included in your conference registration fee. Registrants can attend up to four consecutive tutorials, including four tutorial syllabi.

TIME SESSION 1 SESSION 2 8:00 to 10:00 AM T1 – Fayyad and Simoudis (single session) 10:30 AM to 12:30 PM T2 – Hand T3 – Feldman 1:30 to 3:30 PM T4 – Swayne and Cook T5 – Chaudhuri and Dayal 4:00 to 6:00 PM T6 – Keim T7 – DuMouchel

Tutorial 1: 8:00–10:00 AM Tutorial 2: 10:30 AM–12:30 PM Tutorial 3: 10:30 AM–12:30 PM Data Mining and KDD: Modeling Data and Text Mining— An Overview Discovering Knowledge Theory and Practice

Usama Fayyad, Microsoft Research and Evangelos David Hand, Open University, UK Ronen Feldman, Bar-Ilan University, Israel Simoudis, IBM ur aim is to extract knowledge from nowledge discovery in databases e present a basic tutorial of this new Olarge bodies of data. The size of these K(KDD) focuses on the computerized Wand emerging area and emphasize bodies mean that we cannot do it unaid- exploration of large amounts of data and relations to constituent communities, in- ed, but must use fast computers, applying on the discovery of interesting patterns cluding statistics, databases, pattern recog- sophisticated statistical tools. Attempts to within them. While most work on KDD nition, learning, and visualization. The tu- automate the process of knowledge ex- has been concerned with structured torial provides a basic overview of the traction date from at least the early 1980s, databases, there has been little work on KDD process for extracting knowledge with the work on statistical expert sys- handling the huge amount of information from databases and covers the basics of tems. We examine this work, noting its that is available only in unstructured textu- each step in the process including: data successes and failures and especially what al form. In this tutorial we will present the warehousing, selection and cleaning, data researchers in data mining and knowledge general theory of text mining and will transformation, data mining, evaluation, discovery can learn from those efforts. We demonstrate several systems that use these and visualization. We also cover a sam- examine what data are, what information principles to enable interactive exploration pling of successful applications and out- is, and what knowledge is. We contrast of large textual collections. We will de- line challenges and issues to be addressed. modeling with discovery, especially in the scribe generic techniques for text catego- Usama Fayyad is a senior researcher at context of large data sets. We examine rization and information extraction that Microsoft Research, the Decision Theory high level modeling issues, such as over- are used by these systems. The systems that & Adaptive Systems Group. His research fitting, generalisability, overmodeling, will be presented are KDT which is the sys- interests include knowledge discovery in and model evaluation. And we examine tem for knowledge discovery in texts; large databases, data mining, machine high level exploration issues such as the FACT, which discovers associations among learning, statistical pattern recognition, discovery of accidental artifacts. The con- keywords labeling the items in a collection and clustering. After receiving a Ph.D. de- fluence of computing and statistics in of textual documents; and the Text Explor- gree in 1991, he joined the Jet Propulsion some areas provides a nice backdrop er, which is a system that provides a high Laboratory (JPL), California Institute of against which to examine these issues, level language for interactive exploration Technology (until 1996). At JPL, he head- and we briefly discuss neural networks of textual collections. We will present a ed the Machine Learning Systems Group and classification trees from these two general architecture for text mining and where he developed data mining systems perspectives. will outline the algorithms and data struc- for analysis of large scientific databases. David Hand is a professor of statistics tures behind the systems. We will give spe- Evangelos Simoudis is Vice President, at the Open University. His research inter- cial emphasis to incremental algorithms Global Business Intelligence Solutions – ests include the foundations of statistics, and to efficient data structures. IBM North America, where he is respon- statistical computing, and multivariate Ronen Feldman is a lecturer at the sible for the development and deploy- statistics, the latter especially as applied to Mathematics and Computer Science De- ment of data mining and decision sup- classification problems. His applications partment of Bar-Ilan University in Israel. port solutions to IBM’s customers interests include medicine, finance, and He received his B.Sc. in math, physics and worldwide. Simoudis received a B.A. in psychology. He is editor-in-chief of Statis- computer science from the Hebrew Uni- physics from Grinnell College, a B.S. in tics and Computing and has published versity, and his Ph.D. in computer science electrical engineering from California In- fourteen books, the most recent of which from Cornell University. His main re- stitute of Technology, an M.S. in comput- is Construction and Assessment of Classifi- search is in the area of machine learning er science from the University of Oregon, cation Rules, (Wiley, January 1997). and data mining. He is currently coordi- and a Ph.D. in computer science from nating several research projects for devel- Brandeis University. oping dedicated text mining systems. These systems work on plain text collec- tions and on the Internet.

KDD–97 3 Tutorial 4: 1:30–3:30 PM Exploratory Data Analysis Using Interactive Dynamic Graphics

Deborah Swayne, Bell Communications Research and Diane Cook, Iowa State University

esearchers and software designers in Rthe field of data mining are just begin- ning to make extensive use of graphical methods. Interactive dynamic data visual- ization has been explored in the field of statistics for over twenty years, and we propose that much of what has been learned in statistics is relevant for data mining. This class is an introduction to interactive data visualization as it is prac- ticed as part of exploratory data analysis. The XGobi software, publicly available dy- namic visualization software, will be used in the analysis of examples from biology, business, physics, engineering, and Tutorial 5: 1:30–3:30 PM ligent processing of aggregates, complex telecommunications. The examples will il- query processing, extensions to SQL, RO- lustrate a set of general visualization prin- OLAP and Data Warehousing LAP versus MOLAP. 4) Other services for ciples which are embodied in specific OLAP/data warehousing: data cleaning, methods such as brushing and identifica- Surajit Chaudhuri, Microsoft Research and Umesh Dayal, Hewlett Packard Laboratories loading and refresh, tools for warehouse, tion of points in simple scatterplots, three system and process management, meta- dimensional rotations, rotations in higher n-line analytical processing (OLAP) data management and the role of reposi- dimensions such as the grand tour, and Oand data warehousing technologies tory. 5) State of commercial practice. 6) directed searches in higher dimensions for enable enterprises to gain competitive ad- Research issues. interesting two dimensional views using vantage by exploiting the ever-growing The target audience is researchers and projection pursuit and manual control. amount of data that is collected and developers interested in learning about Deborah Swayne has worked at Bell- stored in corporate databases and files for the concepts, products and the technical core since that company’s inception in better and faster decision making. Over innovations in the area of decision sup- 1985, and is currently a member of the the past few years, these technologies have port technologies. Statistics and Data Mining Research experienced explosive growth, both in the Surajit Chaudhuri is a researcher in Group. Her research focuses on software number of products and services offered, the Database Research Group of Mi- methods for visualizing data. She is one of and in the extent of coverage in the trade crosoft Research. From 1992 to 1995, he the authors of the XGobi software, origi- press. Vendors (including database com- was a member of the technical staff at nally developed at Bellcore. She has a B.A. panies) are paying increasing attention to Hewlett-Packard Laboratories, Palo Alto. in African linguistics from the University all aspects of decision support. The area He earned a B.Tech at the Indian Institute of Wisconsin at Madison, and a M.S. in opens up interesting research directions, of Technology, Kharagpur and a Ph.D. at statistics from Rutgers University. with ties to past work in database systems, Stanford University. In addition to query Dianne Cook is an assistant professor but with different assumptions and re- processing and optimization, Chaudhuri in the Department of Statistics, Iowa State quirements. Only very recently, however, is interested in the areas of data mining, University. She received her PhD from has the database research community database design and uses of databases for Rutgers University in May 1993, and has started to understand and address some nontraditional applications. conducted research into dynamic statisti- of these issues. This tutorial presents an Umesh Dayal is a senior researcher at cal graphics. Her interests include using overview of OLAP and data warehousing, Hewlett-Packard Labs, Palo Alto, Califor- these methods for understanding high-di- and an in-depth study of selected aspects. nia. His current research interests are in mensional data, and adapting them for An outline of the tutorial follows: 1) In- distributed information systems, work- analyzing geographically referenced data troduction: definitions, evolution, differ- flow management, data mining, and in- with multiple measurements at each site. ences from OLTP, architectures. 2) Mod- formation management issues related to els and tools: conceptual model for OLAP, the emerging global information infras- front-end tools (e.g., multidimensional tructure. He received his Ph.D. and S.M. spreadsheets), database design (e.g., star degrees from Harvard University, his M.E. and snowflake schema). 3) Database serv- and B.E. degrees from the Indian Institute er technologies for decision support of Science, and his B.S. degree from Os- queries: specialized indexing techniques, mania University, India. specialized join and scan methods, data partitioning and use of parallelism, intel-

4 KDD–97 Tutorial 6: 4:00–6:00 PM designing the VisDB system—a visual most de rigeur for someone with a new database exploration system. Keim re- classification technique to compare the Visual Techniques for ceived his diploma (equivalent to an MS proposal to one or more of these standard Exploring Databases degree) in computer science from the methods. The tutorial will focus on log- University of Dortmund in 1990 and his linear and logistic regression models, and Daniel Keim, University of Munich Ph.D. in computer science from the Uni- related models such as probit, poisson re- versity of Munich in 1994. Currently, he is gression, and survival models. In the or data exploration to be effective, it is a teaching and research assistant (approx- short time available, priority will be given important to include the human in F imately equivalent to an assistant profes- to explaining why these techniques are so the exploration process and combine the sor) at the Institute for Computer Science popular among statisticians, and to how flexibility, creativity, and general knowl- of the University of Munich, Germany. the basic models have been extended to edge of the human with the enormous handle variables having more than two storage capacity and the computational Tutorial 7: 4:00–6:00 PM categories or when some of the variables power of today’s computers. Visual have continuous or ordinal scales. Exam- database exploration aims at integrating Statistical Models for ples of model fitting, model search and the human in the exploration process, ap- model comparison using SAS and Splus plying its perceptual abilities to the large Categorical Response Data will be presented and discussed. data sets available in today’s computer William DuMouchel, AT&T Research William DuMouchel has been on the systems. The basic idea of visual data ex- faculties of the University of California, ploration is to present the data in some his tutorial will survey the most com- Berkeley; University of Michigan; Univer- visual form, allowing the human to get mon models and methods statisti- T sity of London; MIT; and Columbia Uni- insight into the data and draw conclu- cians use to fit and test relationships versity. From 1987 to 1992 he was chief sions. Visual data exploration techniques among categorical (discrete) data. Most of statistical scientist at BBN Software Prod- have proven to be of high value in ex- these techniques are described in statistics ucts, helping to design and develop com- ploratory data analysis and they also have texts such as Categorical Data Analysis, by mercial software advisory systems for data a high potential for exploring large Alan Agresti, (Wiley 1990) and are widely analysis and experimental design. He is databases. Visual database exploration is available in popular computer packages currently at AT&T Labs – Research, especially powerful for the first steps of such as SAS and Splus. Therefore it is al- Florham Park, New Jersey. the data mining process, namely under- standing the data and generating hy- potheses about the data, but it may also significantly contribute to the actual knowledge discovery by guiding the search using visual feedback. The goal of this tutorial is to show the potential of visualization technology for exploring large databases. The tutorial provides an overview of the state-of-the- art in data visualization and provides a classification of the existing data visual- ization techniques. Besides describing each of the classes, the tutorial focuses on new developments in data visualization, which are relevant to the area of knowl- edge discovery, and describes a wide range of recently developed techniques for visualizing large amounts of arbitrary multi-attribute data which does not have any two- or three-dimensional semantics and therefore does not lend itself to an easy display. A detailed comparison shows the strength and weaknesses of the exist- ing techniques and reveals potentials for further improvements. Several examples demonstrate the benefits of visualization techniques for exploring databases. The tutorial concludes with an overview of ex- isting database exploration and visualiza- tion systems, including research proto- types as well as commercial products. Daniel Keim is one of the leading ex- perts in the field of visual database explo- ration, and he was the chief engineer in

KDD–  Andreas Wierse KDD Workshop—Issues in the Institute for Computer Applications Integration of Data Mining and Data Visualization Department of Computer Simulation and Visualization Sunday, August 17, 8:30 AM – 5:00 PM Pfaffenwaldring 27 D-70550 Stuttgart, Germany ata visualization deals with the effec- late to KDD and data visualization inte- E-mail: [email protected], Dtive portrayal of data with a goal to- gration. We would like to keep discus- Fax: +49(0)711-682357 wards insight about the data. Typically, sions focused on the end result, which is Phone: +49-711-685-5796 the data is of high volume, multidimen- improving the integration of data mining sional in nature, and does not lend itself and knowledge discovery systems with vi- Usama Fayyad to easy display. The data is also often non- sualization: Microsoft Research spatial and temporal in nature. • Requirements visualization places on Redmond, WA 98052-6399 Data visualization software systems are knowledge discovery systems E-mail: [email protected] very popular with end-user domain sci- • Data models and access structures Fax: (206) 936-7329 entists who require visual tools to explore • Modeling the user—tasks, processes, Phone (206) 703-1528 and analyze their data. These visual tools support issues however are used strictly as output of the • Advanced user interfaces for data exploration process and have received mining Demonstrations and much attention whereas the input issues • Visual languages for data mining Exhibits of Knowledge to the exploration process still have not. • System integration issues The KDD community is concerned with • Computational steering for Discovery Products two aspects of visualization techniques: 1) data mining Following the success of the demonstra- Its use at the “back-end” of the explo- • Scalability to large databases tion sessions in previous KDD confer- ration process to help understand models • Distributed, heterogeneous data set ences, the KDD-97 program will also in- extracted by data mining algorithms, and issues—data and computation sharing clude demonstrations of knowledge 2) Scalability issues in visualization: how • Examples of integrated systems discovery products, knowledge discovery do we make it efficient in presence con- • Applications of integrated systems applications and research prototypes. Un- text of large databases where data access is Additional information about this like previous demonstration sessions, we expensive. The visualization community workshop can be found at the following: will clearly differentiate between com- looks at KDD and analytic methods also www.cs.uml.edu/~grinstei/kddvis- mercial product demonstrations and re- as applications to generate displays. How- workshop.html search demonstrations. ever, visualization can be used as input to Paper Submissions KDD and analytic tools; it can also be Exhibits used to support computational steering. (Deadline June 15.) Papers (and position An effective visualization front-end can papers to be expanded for final publica- We invite commercial vendors to exhibit guide a data mining algorithm in its tion) are solicited that present research at KDD-97. The exhibitor fee for KDD-97 search and may result in much better and results in the integration of data mining will be a nominal $250.00. Exhibitors will more easily acceptable solutions. This and visualization. Papers should be limit- be provided with a 6 foot table top. In this workshop will continue the discussions ed to 5,000 words and may be accompa- space vendors will be allowed to dis- started at the first two workshops and fo- nied by NTSC video. These should de- tribute product or company literature, cus on these and other issues that make a scribe some original research on the show product demonstrations and set up case for integrating KDD and visualiza- particular subject, and how it fits in with signage. Vendors will need to bring all tion technologies. the overall theme of the workshop. Proper necessary hardware and software that Two previous workshops (Siggraph ‘90 references should be cited. they will require for their demonstrations. The exhibit area will be open August and Visualization ‘91) have dealt with ar- Registration Fee eas such as high-level requirements for 15th from 12:30–5:00 PM. data structures and access software, and Registration forms will be sent to the ac- Total attendance at KDD-96 was 457. data visualization environments. The first cepted participants. There is a single reg- Of these 35 percent were affiliated with and second workshops on database issues istration fee of US $100, which covers the universities and 65 percent were affiliated for data visualization were held in 1993 workshop sessions, preprints, and coffee with industry. If you would like to exhibit and 1995 and explored the fundamental breaks. at KDD-97 please fill out the registration issues. A number of experimental, proto- Workshop Organizers form and send it along with the name of type, and research systems were present- your product(s) and/or service(s) and a Georges Grinstein ed. The second workshop also saw a be- 200 word (maximum) description of Institute for Visualization and ginning interest with data mining and product(s)/service(s) to: Perception Research visualization integration. This trend, so AAAI University of Massachusetts at Lowell significant in the commercial sector to- KDD-97 Exhibit Lowell, MA 01854 day, is in its infancy and is in need of 445 Burgess Drive E-mail: [email protected] much research attention. Menlo Park, CA 94025 USA Fax: (508) 934-3551 Position statements and papers are wel- Your description will be published in the Phone: (508) 934-3627 come on the following issues as they re- conference program.

 KDD‒ Research Prototype Early Registration Housing Demonstrations (Postmarked by June 10) AAAI has esr erved a block of rooms at We are also soliciting demonstrations of AAAI Members our headquarters hotel—the Newport research prototypes at KDD-97. This Regular $295 Students $95 Beach Marriott Hotel—at reduced con- demonstration session will be held on Nonmembers ference rates. Conference attendees must A ugust 15 from 12:30 to 5:00 PM. We have Regular $375 Students $155 contact the ho tel directly and identify a limited budget for providing hardware themselves as KDD-97 registrants to qual- for research demonstrations. This year we Late Registration ify for the reduced rates. Rooms will be will give priority to demonstrations that (Postmarked by July 15) assigned on a first-come, first-served ba- are in conjunction with accepted papers AAAI Members sis. A ll rooms are subject to a 10% occu- at KDD-97. Within budget and space Regular $350 Students $125 pancy tax. constraints we will make every effort to Nonmembers Newport Beach Marriott Hotel accommodate as many demonstrations as Regular $425 Students $180 900 Newport Center Drive possible. If you would like your demon- Newport Beach, CA 92660 stration to be considered for KDD-97 On-Site Registration Phone: (714) 640-4000 please provide the following information Fax: (714) 640-4918 to Tej A nand (tej.anand@atlantaga. (Postmarked after July 15 or onsite.) Single: $105.00 (1 person, 1 bed) ncr.com) by June 1, 1997: AAAI Members Double: $115.00 (2 persons, 2 beds) • Name of demonstration Regular $400 Students $150 Check-in time: 4:00PM • Title of paper (if this demonstration is Nonmembers Check-out time: 12:00 n oon in conjunction with a paper/poster at Regular $475 Students $210 Cut-off date for reservations: July 24, KDD-97) 1997. • Development team Workshop Registration A ll reservation requests for arrival after • A ffiliations of development team Registration forms will be sent to the ac- 6:00 PMmust be accompanied by a first members cepted participants. There is a separate night room deposit, or guaranteed with a • Contact telephone number registration fee of US $100 which covers major credit card. The Newport Beach • Description of demonstration (approx- the workshop sessions, preprints, and cof- Marriott Hotel will not hold any reserva- imately 200 words) fee breaks. tions after 6:00 PMunless guaranteed by • What is unique about your system or one of the above methods. Reservations application? (No more than 50 words) Payment Information received after the cut-off time will be ac- • Status: Is the system a research proto- cepted on a space or rate available basis. type, a commercially available product, Prepayment of registration fees is re- Reservations accepted without a credit or a fielded application? quired. Checks, international money or- card guarantee or advance deposit are • Hardware required: A re there any spe- ders, bank transfers and travelers’ checks subject to cancellation at 6:00 PMon the cial memory or disk requirements? must be in US dollars. A merican Express, day of arrival. • Operating system (specific version MasterCard, VISA, and government pur- number) chase orders are also accepted. Registra- • WAN connection needed? (A re there- tion applications postmarked after the Transportation any special modem requirements?) early registration deadline will be subject • Will you bring your own hardware? to the late registration fees. Registration Air Transportation • A ny other requirements? applications postmarked after the late registration deadline will be subject to and Car Rental on-site registration fees. Student registra- Newport Beach, California – G et there for Registration Fees tions must be accompanied by proof of less! Discounted fares have been negotiat- The KDD-97 program registration in- full-time student status. ed for this event. Call Conventions in cludes admission to four tutorials, four A merica at (800) 929-4242 and ask of r tutorial syllabi, technical and demo ses- Refund Requests Group #428. You will receive five to ten percent off the lowest applicable fares on sions, the opening reception, theKDD-97 The deadline for refund requests is July A merican A irlines, or the guaranteed low- Proceedings and mid-morning and after- 25, 1997. A ll refund requests must be est available fare on any carrier. Travel be- noon coffee breaks. Onsite registration made in writing. A $75.00 processing fee tween A ugust 11–21, 1997. A ll attendees will be located in the foyer outside the will be assessed for all refunds. California Ballroom, Newport Beach booking through CIA will receive free Marriott Hotel and Tennis Club, lobby Registration Hours flight insurance and be entered in their level. bi-monthly drawing for worldwide travel Registration hours will be Thursday–Sat- for two on A merican A irlines! Hertz Rent urday, A ugust 14–16, 7:30 A M–6:00 PM A Car is also offering special low confer- and Sunday, A ugust 17, 8:00 A M–3:00PM. ence rates, with unlimited free mileage. A ll attendees must pick up their registra- Call Conventions in America: tion packets for admittance to programs. (800) 929-4242, ask for Group #428. Reservation hours: M-F 6:30 A M–5:00 PMPacific Time.

KDD– Outside US and Canada: AAAI Press Books on KDD (619) 453-3686 (619) 453-7679 (fax). Internet: [email protected] Proceedings of the First International Conference on 24-hour emergency service: Knowledge Discovery and Data Mining (KDD-95) (800) 748-5520. Edited by Usama M. Fayyad and If you call direct: American (800) 433- Ramasamy Uthurusamy 1790, ask for index #S 9485. Hertz: (800) 654-2240, ask for offer Papers in this proceedings focus on unifying themes such as the use of domain knowl- CV#24250. edge, managing uncertainty, interactive (human-oriented) presentation, and applica- tions. Ground Transportation 348 pp. The following information provided is $50.00 paperback the best available at press time. Please ISBN 0-929280-82-2 confirm fares when making reservations. Proceedings of the Second International Conference on Airport Connections Knowledge Discovery and Data Mining (KDD-96) The Newport Beach Marriott Hotel pro- vides complimentary airport transporta- Edited by Evangelos Simoudis, Jia Wei Han, and Usama Fayyad tion to/from John Wayne /Orange Coun- 400 pp. ty Airport. $55.00 paperback Super Shuttle: (714) 517-6600. The ISBN 1-57735-004-9 one-way fare from the Los Angeles Inter- national Airport (LAX) to the Newport Beach Marriott Hotel is $21.00 per per- Advances in Knowledge Discovery and son. Reservations 24 hours in advance are Data Mining recommended. Discover Card, traveller’s checks and cash are accepted. Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth, and Ramasamy Uthurusamy Taxi Published by the AAAI Press / The MIT Press Taxis are available at John Wayne Airport. 625 pp. Approximate fare from the airport to $50.00 downtown Newport Beach is $14.00. Or- ISBN 0-262-56097-6 ange County Yellow Cab Service: (714) 546-1311. The approximate taxi fare from the Los Angeles International Airport to the Newport Beach Marriott Hotel is To order, consult your registration form, see AAAI Press’s web page $75.00 – $80.00. (www.aaai.org/Press/), or call us at (415) 328-3123 Bus Greyhound/Trailways Lines: The depot is located at 100 W. Winston Road, Ana- heim, CA 92805. For information on fares and scheduling, call (714) 999-1256. Rail The Amtrak (Southern Pacific Railroad) stations are located at Santa Ana, Irvine and Anaheim. For general information and ticketing, call (800) 872-7245. City Transit System The Orange County Transit District (OCTD) serves Newport Beach, Balboa Island and Corona del Mar. Basic local fare is $1.00. For general information call (714) 636-RIDE. Parking Parking is available at the Newport Beach Marriott Hotel. The daily rate for valet parking is $6.00, and $8.00 overnight. Self-parking is complimentary.

 KDD‒ Newport Beach, California! Newport Beach is located along the beautiful Pacific Ocean in Orange County, California, nestled south of Los Angeles, north of San Diego, southwest of Disneyland in Anaheim, and adjacent to John Wayne/Orange County Airport. Surrounded by one of the largest small-boat harbors in the world and lazily stretching itself along more than six miles of scenic Pacific coastline, Newport Beach beckons national and international visitors to moor at the magnificent harbor and discover “The Colorful Coast.”

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KDD– 