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




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.


Symposium Schedule



Selected papers will be extended for a submission to a special issue in the International Journal of Web Information Systems (



Paper submission deadline:

Dec. 01, 2006

Paper notification deadline:

Feb. 01, 2007

Camera-ready version

Feb 19, 2007

Registration deadline:

Feb 19, 2007


May 21-23, 2007


Steering Chair:

                Laurence T. Yang <>, St. Francis Xavier University, Canada


General Co-Chairs:
                David Taniar <>, Monash University, Australia
                Beniamino Di Martin <>, Second University of Naples, Italy
                Kin F. Li, <> ,University of Victoria, Canada
Program Committee Co-Chairs:
               Xiaohua (Tony) Hu <>, Drexel University, USA
               Zhen Liu <>, Nagasaki Institute of Applied Science, Japan 
               Domenico Talia <>, 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