-------- Original-Nachricht -------- Betreff: [computational.science] Last CFP for IEEE DMIR 07 Datum: Sat, 18 Nov 2006 12:43:39 -0500 Von: Tony Hu thu@cis.drexel.edu Organisation: "OptimaNumerics" An: Computational Science Mailing List computational.science@lists.optimanumerics.com

The 2007 IEEE International Symposium on Data Mining and Information Retrieval (IEEE DMIR-07) in conjunction with The IEEE 21st International Conference on Advanced Information Networking and Applications (AINA-07) May 21-23, 2007 Sheraton Fallsview Hotel, Niagara Falls, Ontario, Canada Indexing, retrieval, management and mining of abundant text data on the web or digital library have become very important nowadays. The large number of text documents and the lack of formal structure in the natural-language narrative make the text search and processing very difficult, thus it is essential to develop efficient and effective text searching, retrieval and mining techniques from this ever-expanding collection of text data. Recently data mining has been successfully applied to a number of information retrieval tasks, such as statistical inference, machine learning and information retrieval, supervised learning and its application to text classification, unsupervised/semi-supervised learning, and its applications to collaborative filtering and text clustering. In these applications, data mining models are able to assist the process of information retrieval more efficiently and effectively. These include providing information retrieval process patterns that are found by the data mining models. Industry practitioners have realized that using data mining techniques in information retrieval will result in clear benefits and enhance information retrieval. Many large enterprises are believed to have been using data mining techniques in their online businesses, such as including a list of recommendations when a web user is browsing or searching for a particular product. Many of the ranking systems in information retrieval also gain performance benefits when adopting certain data mining techniques, including clustering, association patterns, etc. The goal of this symposium is to encourage researchers and practitioners from these two disciplines to address some of these challenges, help cross fertilization of ideas, and provide a common forum for the exchange of ideas in an informal environment. This 2007 IEEE International Symposium on Data Mining and Information Retrieval (DMIR-07) focuses on the latest research work in the interrelationship between data mining, information retrieval and information extraction, new methods, techniques that take advantages of the full mutual benefits of the three components in the same framework, topics include but not limit to: Theory and Models for Information Retrieval Efficiency and Performance of IR Evaluation and Test of Text Collections, Evaluation methods and metrics, Experimental design, Data collection and analysis methods Indexing, Query representation, Query reformulation, Structure-based representation, XML, Metadata, and Summarization Natural language processing and representation for IR and Data Mining Tracking, Filtering, Topic detection, Collaborative filtering, Agents, Routing and Email spam Text Categorization and Clustering Text Data Mining and Machine Learning for IR Cross-language and multilingual Information Retrieval Text content representation (Indexing), Structure-based representation, XML, Metadata, Request representation, Queries, and Summarization Web IR and Digital Libraries Machine Translation for IR and Data Mining Topic detection and tracking, Content-based filtering, Collaborative filtering, Agents, Routing, Email spam Question Answering and Extraction: Question answering, Information extraction, Lexical acquisition Domain Specific IR Applications: Genomic IR, IR for chemical structures, etc Information Retrieval and Data mining applications in bioinformatics, electronic commerce, Web, intrusion detection, finance, marketing, healthcare Data mining models: Statistical techniques for generation of a robust, consistent data model Declarative/algebraic languages for data mining: Integration of database languages such as SQL and XML with data mining, Coupling between database, data warehouse and data mining systems Post-processing, data transformations: Incremental mining and knowledge-base refinement, Foundational concepts for exploratory data analysis, Model scoring, meta learning, meta-data model management, Privacy preserving data mining models and algorithms Optimization techniques Multimedia and multimodal information access and retrieval: Content-based information

PAPER SUBMISSION: Authors should submit the softcopy of their paper in PDF, PostScript, or MS Word format online. The paper must be at most 15 pages (single space, one column), including abstract, keywords, and references, and include the e-mail address of the corresponding author. Accepted papers with at most 6 pages (single space, 2-columns) will be published by IEEE Computer Society Press. Please use the online paper submission to submit your paper.

SPECIAL ISSUE OF JOURNAL: Selected papers will be extended for a submission to a special issue in the International Journal of Web Information Systems ( http://www.troubador.co.uk/ijwis).

IMPORTANT DATES:

Paper submission deadline: Dec. 01, 2006 Paper notification deadline: Feb. 01, 2007 Camera-ready version Feb 19, 2007 Registration deadline: Feb 19, 2007 Conference: May 21-23, 2007

Steering Chair: · Laurence T. Yang lyang@stfx.ca, St. Francis Xavier University, Canada

General Co-Chairs: · David Taniar David.Taniar@infotech.monash.edu.au, Monash University, Australia · Beniamino Di Martin beniamino.dimartino@unina.it, Second University of Naples, Italy · Kin F. Li, kinli@uvic.ca ,University of Victoria, Canada

Program Committee Co-Chairs: · Xiaohua (Tony) Hu thu@cis.drexel.edu, Drexel University, USA · Zhen Liu liuzhen@cc.nias.ac.jp, Nagasaki Institute of Applied Science, Japan · Domenico Talia talia@deis.unical.it, DEIS, Italy

Program Committee Hussein A. Abbass, University of New South Wales, Australia Sixu Bai, Nanchang University, China Stephane Bressan, National University of Singapore, Singapore Longbing Cao, University of Technology Sydney, Australia Mario Cannataro, Univ. di Catanzaro, Italy Somchai Chatvichienchai, Siebolt University of Technology, Japan Kai Cheng, Kyushu Sa ngyo University, Japan Honghua Dai, Deakin University, Australia Mustafa Mat Deris, Kolej Universiti Teknologi Tun Hussein Onn, Malaysia Werner Dubitzky, Univ. of Ulster, UK Vladimir Estivill-Castro , Griffith University, Australia Kazuo Hashimoto, KDD R&D Laboratories Inc., Japan Jimmy Huang, York University, Canada, Hiroyuki Kawano, Nanzan University, Japan Itoh Ken-ichi, Siebolt University of Technology, Japan Zhoujun Li, Beihuang University, China Ee-Peng Lim, Nanyang Technological University, Singapore TY Lin, San Jose State University, USA Jiming Liu, University of Windsor, Canada Yuanning Liu, Jilin University, China Xia Lin, Drexel University, USA Wei Lu, German Research Center for AI, Germany Giuseppe Manco, ICAR-CNR, Italy Richi Nayak, Queensland University of Technology, Australia Michael Ng, HongKong Baptist University, China Rafael Parra-Hernandez, Powertech, Canada John Roddick Flinders University, Australia Assaf Schuster, TECHNION Hao Shi, Victoria University, Australia Yong Shi, University of Nebraska, USA Jim Smith, University of Newcastle, UK Il-Yeok Song, Drexel University, USA Min Song, New Jersey Institute of Technology, USA Andrea Tagarelli, Univ. della Calabria, Italy Chew Lim Tan, National University of Singapore, Singapore Tezuka Taro, Kyoto University, Japan Alex Thomo, University of Victoria, Canada Shusaku Tsumoto, Shimane Medical University, Japan Dianhui Wang, La Trobe University, Australia John Wang, Montclair State University Shengrui Wang, Universite de Sherbrooke, Canada Takashi Washio, Osaka University, Japan Martine Wedlake, IBM, USA Xindong Wu, University of Vermont, USA Hongji Yang, Montfort University, UK Hayato Yamana, Waseda University, Japan Jinmin Yang, Hunan University, China Illhoi Yoo, University of Missouri-Columbia Yi Zhang,University of Electronic Science and Technology of China, China Chunguang Zhou, Jilin University, China Shuigeng Zhou, Fudan University, China Ning Zhong, Maebashi Institute of Technology, Japan Xiaohua (Davis) Zhou, Drexel University, USA

Best regards!

Yours

Xiaohua (Tony) Hu, Ph.D. Assistant Professor Editor-in-Chief, Int. Jour. of Data Mining & Bioinformatics Director, Data Mining and Bioinformatics Lab College of Information Science & Technology Drexel University, Philadelphia PA 19104, USA thu@cis.drexel.edu 215-8950551(O), 215-8952494(fax) http://www.cis.drexel.edu/faculty/thu http://www.inderscience.com/ijdmb http://www.ischool.drexel.edu/dmbio