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This Festschrift volume, published in honour of Peter Buneman,
contains contributions written by some of his colleagues, former
students, and friends. In celebration of his distinguished career a
colloquium was held in Edinburgh, Scotland, 27-29 October, 2013.
The articles presented herein belong to some of the many areas of
Peter's research interests.
Data quality is one of the most important problems in data
management. A database system typically aims to support the
creation, maintenance, and use of large amount of data, focusing on
the quantity of data. However, real-life data are often dirty:
inconsistent, duplicated, inaccurate, incomplete, or stale. Dirty
data in a database routinely generate misleading or biased
analytical results and decisions, and lead to loss of revenues,
credibility and customers. With this comes the need for data
quality management. In contrast to traditional data management
tasks, data quality management enables the detection and correction
of errors in the data, syntactic or semantic, in order to improve
the quality of the data and hence, add value to business processes.
While data quality has been a longstanding problem for decades, the
prevalent use of the Web has increased the risks, on an
unprecedented scale, of creating and propagating dirty data. This
monograph gives an overview of fundamental issues underlying
central aspects of data quality, namely, data consistency, data
deduplication, data accuracy, data currency, and information
completeness. We promote a uniform logical framework for dealing
with these issues, based on data quality rules. The text is
organized into seven chapters, focusing on relational data. Chapter
One introduces data quality issues. A conditional dependency theory
is developed in Chapter Two, for capturing data inconsistencies. It
is followed by practical techniques in Chapter 2b for discovering
conditional dependencies, and for detecting inconsistencies and
repairing data based on conditional dependencies. Matching
dependencies are introduced in Chapter Three, as matching rules for
data deduplication. A theory of relative information completeness
is studied in Chapter Four, revising the classical Closed World
Assumption and the Open World Assumption, to characterize
incomplete information in the real world. A data currency model is
presented in Chapter Five, to identify the current values of
entities in a database and to answer queries with the current
values, in the absence of reliable timestamps. Finally,
interactions between these data quality issues are explored in
Chapter Six. Important theoretical results and practical algorithms
are covered, but formal proofs are omitted. The bibliographical
notes contain pointers to papers in which the results were
presented and proven, as well as references to materials for
further reading. This text is intended for a seminar course at the
graduate level. It is also to serve as a useful resource for
researchers and practitioners who are interested in the study of
data quality. The fundamental research on data quality draws on
several areas, including mathematical logic, computational
complexity and database theory. It has raised as many questions as
it has answered, and is a rich source of questions and vitality.
Table of Contents: Data Quality: An Overview / Conditional
Dependencies / Cleaning Data with Conditional Dependencies / Data
Deduplication / Information Completeness / Data Currency /
Interactions between Data Quality Issues
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Advances in Web-Age Information Management - 6th International Conference, WAIM 2005, Hangzhou, China, October 11-13, 2005, Proceedings (Paperback, 2005 ed.)
Wenfei Fan, Zhaohui Wu, Jun Yang
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R3,478
Discovery Miles 34 780
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are essential to the quality of the program. We are grateful to
Weiyi Meng, X. Sean Wang, Stratis D. Viglas, and Je?rey Xu Yu for
their valuable help in leading and monitoring the discussions on
our behalf. We also thank Jun Yang for his work in preparing the
proceedings. Finally, we are deeply indebted to Yu Zhang and Mengya
Tang, the Web Masters, who took on tremendous pain and extra work,
and ably modi?ed, extended and maintained the conference management
tool; for three long months they worked until late night every day,
seven days a week; the necessary extension of the tool also
received help from Kun Jing, Chengchao Xie, Shiqi Peng, Heng Wang,
Cheng Jin and Ruizhi Ye; without their hardande?ectiveworkthe
onlinediscussionswouldnothavebeen possible, among other things.
October 2005 Wenfei Fan, Zhaohui Wu Program Committee Co-chairs
WAIM 2005 Dedication: Hongjun Lu (1945-2005) On behalf of the
Program Committee, it is with sincere gratitude and great sorrow
that we would like to dedicate WAIM 2005 proceedings to Hongjun Lu,
who left us on March 3, 2005. Hongjun was not only an excellent
researcher and highly productive scholar of the database community,
but also a wond- ful colleague and dear friend. For many years, he
has been the ambassador for database research to China, and
tremendously fostered the growth of this community.
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Big Data - 8th CCF Conference, BigData 2020, Chongqing, China, October 22-24, 2020, Revised Selected Papers (Paperback, 1st ed. 2021)
Hong Mei, Wei-Guo Zhang, Wenfei Fan, Zili Zhang, Yihua Huang, …
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R1,557
Discovery Miles 15 570
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This book constitutes the proceedings of the 8th CCF Conference on
Big Data, BigData 2020, held in Chongqing, China, in October 2020.
The 16 full papers presented in this volume were carefully reviewed
and selected from 65 submissions. They present recent research on
theoretical and technical aspects on big data, as well as on
digital economy demands in big data applications.
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Web Technologies and Applications - 13th Asia-Pacific Web Conference, APWeb 2011, Beijing, Chiina, April 18-20, 2011. Proceedings (Paperback, Edition.)
Xiaoyong Du, Wenfei Fan, Jianmin Wang, Zhiyong Peng, Mohamed A. Sharaf
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R1,622
Discovery Miles 16 220
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This book constitutes the proceedings of the 13th Asia-Pacific
Conference APWeb 2011 held in conjunction with the APWeb 2011
Workshops XMLDM and USD, in Beijing, China, in April 2011. The 26
full papers presented together with 10 short papers, 3 keynote
talks, and 4 demo papers were carefully reviewed and selected from
104 submissions. The submissions range over a variety of topics
such as classification and clustering; spatial and temporal
databases; personalization and recommendation; data analysis and
application; Web mining; Web search and information retrieval;
complex and social networks; and secure and semantic Web.
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