Adaptive Windows For Duplicate Detection

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Adaptive Windows for Duplicate Detection

Uwe Draisbach,Felix Naumann,Sascha Szott,Oliver Wonneberg
Adaptive Windows for Duplicate Detection Book PDF

Author : Uwe Draisbach,Felix Naumann,Sascha Szott,Oliver Wonneberg
Publisher : Universitätsverlag Potsdam
Page : 46 pages
File Size : 44,7 Mb
Release : 2012
Category : Computers
ISBN : 9783869561431

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Adaptive Windows for Duplicate Detection by Uwe Draisbach,Felix Naumann,Sascha Szott,Oliver Wonneberg Pdf

Duplicate detection is the task of identifying all groups of records within a data set that represent the same real-world entity, respectively. This task is difficult, because (i) representations might differ slightly, so some similarity measure must be defined to compare pairs of records and (ii) data sets might have a high volume making a pair-wise comparison of all records infeasible. To tackle the second problem, many algorithms have been suggested that partition the data set and compare all record pairs only within each partition. One well-known such approach is the Sorted Neighborhood Method (SNM), which sorts the data according to some key and then advances a window over the data comparing only records that appear within the same window. We propose several variations of SNM that have in common a varying window size and advancement. The general intuition of such adaptive windows is that there might be regions of high similarity suggesting a larger window size and regions of lower similarity suggesting a smaller window size. We propose and thoroughly evaluate several adaption strategies, some of which are provably better than the original SNM in terms of efficiency (same results with fewer comparisons).

Model-driven engineering of adaptation engines for self-adaptive software

Thomas Vogel,Holger Giese
Model driven engineering of adaptation engines for self adaptive software Book PDF

Author : Thomas Vogel,Holger Giese
Publisher : Universitätsverlag Potsdam
Page : 74 pages
File Size : 49,8 Mb
Release : 2013
Category : Computers
ISBN : 9783869562278

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Model-driven engineering of adaptation engines for self-adaptive software by Thomas Vogel,Holger Giese Pdf

The development of self-adaptive software requires the engineering of an adaptation engine that controls and adapts the underlying adaptable software by means of feedback loops. The adaptation engine often describes the adaptation by using runtime models representing relevant aspects of the adaptable software and particular activities such as analysis and planning that operate on these runtime models. To systematically address the interplay between runtime models and adaptation activities in adaptation engines, runtime megamodels have been proposed for self-adaptive software. A runtime megamodel is a specific runtime model whose elements are runtime models and adaptation activities. Thus, a megamodel captures the interplay between multiple models and between models and activities as well as the activation of the activities. In this article, we go one step further and present a modeling language for ExecUtable RuntimE MegAmodels (EUREMA) that considerably eases the development of adaptation engines by following a model-driven engineering approach. We provide a domain-specific modeling language and a runtime interpreter for adaptation engines, in particular for feedback loops. Megamodels are kept explicit and alive at runtime and by interpreting them, they are directly executed to run feedback loops. Additionally, they can be dynamically adjusted to adapt feedback loops. Thus, EUREMA supports development by making feedback loops, their runtime models, and adaptation activities explicit at a higher level of abstraction. Moreover, it enables complex solutions where multiple feedback loops interact or even operate on top of each other. Finally, it leverages the co-existence of self-adaptation and off-line adaptation for evolution.

Population Reconstruction

Gerrit Bloothooft,Peter Christen,Kees Mandemakers,Marijn Schraagen
Population Reconstruction Book PDF

Author : Gerrit Bloothooft,Peter Christen,Kees Mandemakers,Marijn Schraagen
Publisher : Springer
Page : 302 pages
File Size : 53,6 Mb
Release : 2015-07-22
Category : Social Science
ISBN : 9783319198842

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Population Reconstruction by Gerrit Bloothooft,Peter Christen,Kees Mandemakers,Marijn Schraagen Pdf

This book addresses the problems that are encountered, and solutions that have been proposed, when we aim to identify people and to reconstruct populations under conditions where information is scarce, ambiguous, fuzzy and sometimes erroneous. The process from handwritten registers to a reconstructed digitized population consists of three major phases, reflected in the three main sections of this book. The first phase involves transcribing and digitizing the data while structuring the information in a meaningful and efficient way. In the second phase, records that refer to the same person or group of persons are identified by a process of linkage. In the third and final phase, the information on an individual is combined into a reconstruction of their life course. The studies and examples in this book originate from a range of countries, each with its own cultural and administrative characteristics, and from medieval charters through historical censuses and vital registration, to the modern issue of privacy preservation. Despite the diverse places and times addressed, they all share the study of fundamental issues when it comes to model reasoning for population reconstruction and the possibilities and limitations of information technology to support this process. It is thus not a single discipline that is involved in such an endeavor. Historians, social scientists, and linguists represent the humanities through their knowledge of the complexity of the past, the limitations of sources, and the possible interpretations of information. The availability of big data from digitized archives and the need for complex analyses to identify individuals calls for the involvement of computer scientists. With contributions from all these fields, often in direct cooperation, this book is at the heart of the digital humanities, and will hopefully offer a source of inspiration for future investigations.

Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence

Juanzi Li,Ming Zhou,Guilin Qi,Ni Lao,Tong Ruan,Jianfeng Du
Knowledge Graph and Semantic Computing Language Knowledge and Intelligence Book PDF

Author : Juanzi Li,Ming Zhou,Guilin Qi,Ni Lao,Tong Ruan,Jianfeng Du
Publisher : Springer
Page : 173 pages
File Size : 53,5 Mb
Release : 2018-01-18
Category : Computers
ISBN : 9789811073595

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Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence by Juanzi Li,Ming Zhou,Guilin Qi,Ni Lao,Tong Ruan,Jianfeng Du Pdf

This book constitutes the refereed proceedings of the Second China Conference on Knowledge Graph and Semantic Computing, CCKS 2017, held in Chengdu, China, in August 2017. The 11 revised full papers and 6 revised short papers presented were carefully reviewed and selected from 85 submissions. The papers cover wide research fields including the knowledge graph, the Semantic Web, linked data, NLP, knowledge representation, graph databases.

Recent Trends in Image Processing and Pattern Recognition

K. C. Santosh,Bharti Gawali
Recent Trends in Image Processing and Pattern Recognition Book PDF

Author : K. C. Santosh,Bharti Gawali
Publisher : Springer Nature
Page : 555 pages
File Size : 45,7 Mb
Release : 2021-02-25
Category : Computers
ISBN : 9789811605079

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Recent Trends in Image Processing and Pattern Recognition by K. C. Santosh,Bharti Gawali Pdf

This two-volume set constitutes the refereed proceedings of the Third International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2020, held in Aurangabad, India, in January 2020. The 78 revised full papers presented were carefully reviewed and selected from 329 submissions. The papers are organized in topical sections in the two volumes. Part I: Computer vision and applications; Data science and machine learning; Document understanding and Recognition. Part II: Healthcare informatics and medical imaging; Image analysis and recognition; Signal processing and pattern recognition; Image and signal processing in Agriculture.

Trends and Applications in Knowledge Discovery and Data Mining

Jiuyong Li,Longbing Cao,Can Wang,Kay Chen Tan,Bo Liu,Jian Pei,Vincent S. Tseng
Trends and Applications in Knowledge Discovery and Data Mining Book PDF

Author : Jiuyong Li,Longbing Cao,Can Wang,Kay Chen Tan,Bo Liu,Jian Pei,Vincent S. Tseng
Publisher : Springer
Page : 556 pages
File Size : 51,8 Mb
Release : 2013-08-23
Category : Computers
ISBN : 9783642403194

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Trends and Applications in Knowledge Discovery and Data Mining by Jiuyong Li,Longbing Cao,Can Wang,Kay Chen Tan,Bo Liu,Jian Pei,Vincent S. Tseng Pdf

This book constitutes the refereed proceedings at PAKDD Workshops 2013, affiliated with the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held in Gold Coast, Australia in April 2013. The 47 revised full papers presented were carefully reviewed and selected from 92 submissions. The workshops affiliated with PAKDD 2013 include: Data Mining Applications in Industry and Government (DMApps), Data Analytics for Targeted Healthcare (DANTH), Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE), Biologically Inspired Techniques for Data Mining (BDM), Constraint Discovery and Application (CDA), Cloud Service Discovery (CloudSD).

Proceedings of the 9th Ph.D. retreat of the HPI Research School on service-oriented systems engineering

Meinel, Christoph,Plattner, Hasso,Döllner, Jürgen,Weske, Mathias,Polze, Andreas,Hirschfeld, Robert,Naumann, Felix,Giese, Holger,Baudisch, Patrick,Friedrich, Tobias
Proceedings of the 9th Ph D retreat of the HPI Research School on service oriented systems engineering Book PDF

Author : Meinel, Christoph,Plattner, Hasso,Döllner, Jürgen,Weske, Mathias,Polze, Andreas,Hirschfeld, Robert,Naumann, Felix,Giese, Holger,Baudisch, Patrick,Friedrich, Tobias
Publisher : Universitätsverlag Potsdam
Page : 266 pages
File Size : 46,7 Mb
Release : 2017-03-23
Category : Computers
ISBN : 9783869563459

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Proceedings of the 9th Ph.D. retreat of the HPI Research School on service-oriented systems engineering by Meinel, Christoph,Plattner, Hasso,Döllner, Jürgen,Weske, Mathias,Polze, Andreas,Hirschfeld, Robert,Naumann, Felix,Giese, Holger,Baudisch, Patrick,Friedrich, Tobias Pdf

Design and implementation of service-oriented architectures impose numerous research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Service-oriented Systems Engineering represents a symbiosis of best practices in object orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns. Service-oriented Systems Engineering denotes a current research topic in the field of IT-Systems Engineering with high potential in academic research and industrial application. The annual Ph.D. Retreat of the Research School provides all members the opportunity to present the current state of their research and to give an outline of prospective Ph.D. projects. Due to the interdisciplinary structure of the Research School, this technical report covers a wide range of research topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.

Advances in Knowledge Discovery and Data Mining

Vincent S. Tseng,Tu Bao Ho,Zhi-Hua Zhou,Arbee L.P. Chen,Hung-Yu Kao
Advances in Knowledge Discovery and Data Mining Book PDF

Author : Vincent S. Tseng,Tu Bao Ho,Zhi-Hua Zhou,Arbee L.P. Chen,Hung-Yu Kao
Publisher : Springer
Page : 624 pages
File Size : 50,8 Mb
Release : 2014-05-08
Category : Computers
ISBN : 9783319066059

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Advances in Knowledge Discovery and Data Mining by Vincent S. Tseng,Tu Bao Ho,Zhi-Hua Zhou,Arbee L.P. Chen,Hung-Yu Kao Pdf

The two-volume set LNAI 8443 + LNAI 8444 constitutes the refereed proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, held in Tainan, Taiwan, in May 2014. The 40 full papers and the 60 short papers presented within these proceedings were carefully reviewed and selected from 371 submissions. They cover the general fields of pattern mining; social network and social media; classification; graph and network mining; applications; privacy preserving; recommendation; feature selection and reduction; machine learning; temporal and spatial data; novel algorithms; clustering; biomedical data mining; stream mining; outlier and anomaly detection; multi-sources mining; and unstructured data and text mining.

Linking and Mining Heterogeneous and Multi-view Data

Deepak P,Anna Jurek-Loughrey
Linking and Mining Heterogeneous and Multi view Data Book PDF

Author : Deepak P,Anna Jurek-Loughrey
Publisher : Springer
Page : 343 pages
File Size : 54,5 Mb
Release : 2018-12-13
Category : Technology & Engineering
ISBN : 9783030018726

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Linking and Mining Heterogeneous and Multi-view Data by Deepak P,Anna Jurek-Loughrey Pdf

This book highlights research in linking and mining data from across varied data sources. The authors focus on recent advances in this burgeoning field of multi-source data fusion, with an emphasis on exploratory and unsupervised data analysis, an area of increasing significance with the pace of growth of data vastly outpacing any chance of labeling them manually. The book looks at the underlying algorithms and technologies that facilitate the area within big data analytics, it covers their applications across domains such as smarter transportation, social media, fake news detection and enterprise search among others. This book enables readers to understand a spectrum of advances in this emerging area, and it will hopefully empower them to leverage and develop methods in multi-source data fusion and analytics with applications to a variety of scenarios. Includes advances on unsupervised, semi-supervised and supervised approaches to heterogeneous data linkage and fusion; Covers use cases of analytics over multi-view and heterogeneous data from across a variety of domains such as fake news, smarter transportation and social media, among others; Provides a high-level overview of advances in this emerging field and empowers the reader to explore novel applications and methodologies that would enrich the field.

Advances in Knowledge Discovery and Data Mining

Dinh Phung,Vincent S. Tseng,Geoffrey I. Webb,Bao Ho,Mohadeseh Ganji,Lida Rashidi
Advances in Knowledge Discovery and Data Mining Book PDF

Author : Dinh Phung,Vincent S. Tseng,Geoffrey I. Webb,Bao Ho,Mohadeseh Ganji,Lida Rashidi
Publisher : Springer
Page : 852 pages
File Size : 42,8 Mb
Release : 2018-06-16
Category : Computers
ISBN : 9783319930404

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Advances in Knowledge Discovery and Data Mining by Dinh Phung,Vincent S. Tseng,Geoffrey I. Webb,Bao Ho,Mohadeseh Ganji,Lida Rashidi Pdf

This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications.

An Introduction to Duplicate Detection

Felix Naumann,Melanie Herschel
An Introduction to Duplicate Detection Book PDF

Author : Felix Naumann,Melanie Herschel
Publisher : Morgan & Claypool Publishers
Page : 77 pages
File Size : 43,8 Mb
Release : 2010
Category : Computers
ISBN : 9781608452200

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An Introduction to Duplicate Detection by Felix Naumann,Melanie Herschel Pdf

With the ever increasing volume of data, data quality problems abound. Multiple, yet different representations of the same real-world objects in data, duplicates, are one of the most intriguing data quality problems. The effects of such duplicates are detrimental; for instance, bank customers can obtain duplicate identities, inventory levels are monitored incorrectly, catalogs are mailed multiple times to the same household, etc. Automatically detecting duplicates is difficult: First, duplicate representations are usually not identical but slightly differ in their values. Second, in principle all pairs of records should be compared, which is infeasible for large volumes of data. This lecture examines closely the two main components to overcome these difficulties: (i) Similarity measures are used to automatically identify duplicates when comparing two records. Well-chosen similarity measures improve the effectiveness of duplicate detection. (ii) Algorithms are developed to perform on very large volumes of data in search for duplicates. Well-designed algorithms improve the efficiency of duplicate detection. Finally, we discuss methods to evaluate the success of duplicate detection. Table of Contents: Data Cleansing: Introduction and Motivation / Problem Definition / Similarity Functions / Duplicate Detection Algorithms / Evaluating Detection Success / Conclusion and Outlook / Bibliography

The Four Generations of Entity Resolution

George Papadakis,Ekaterini Ioannou,Emanouil Thanos,Themis Palpanas
The Four Generations of Entity Resolution Book PDF

Author : George Papadakis,Ekaterini Ioannou,Emanouil Thanos,Themis Palpanas
Publisher : Springer Nature
Page : 152 pages
File Size : 55,5 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031018787

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The Four Generations of Entity Resolution by George Papadakis,Ekaterini Ioannou,Emanouil Thanos,Themis Palpanas Pdf

Entity Resolution (ER) lies at the core of data integration and cleaning and, thus, a bulk of the research examines ways for improving its effectiveness and time efficiency. The initial ER methods primarily target Veracity in the context of structured (relational) data that are described by a schema of well-known quality and meaning. To achieve high effectiveness, they leverage schema, expert, and/or external knowledge. Part of these methods are extended to address Volume, processing large datasets through multi-core or massive parallelization approaches, such as the MapReduce paradigm. However, these early schema-based approaches are inapplicable to Web Data, which abound in voluminous, noisy, semi-structured, and highly heterogeneous information. To address the additional challenge of Variety, recent works on ER adopt a novel, loosely schema-aware functionality that emphasizes scalability and robustness to noise. Another line of present research focuses on the additional challenge of Velocity, aiming to process data collections of a continuously increasing volume. The latest works, though, take advantage of the significant breakthroughs in Deep Learning and Crowdsourcing, incorporating external knowledge to enhance the existing words to a significant extent. This synthesis lecture organizes ER methods into four generations based on the challenges posed by these four Vs. For each generation, we outline the corresponding ER workflow, discuss the state-of-the-art methods per workflow step, and present current research directions. The discussion of these methods takes into account a historical perspective, explaining the evolution of the methods over time along with their similarities and differences. The lecture also discusses the available ER tools and benchmark datasets that allow expert as well as novice users to make use of the available solutions.

Linking Sensitive Data

Peter Christen,Thilina Ranbaduge,Rainer Schnell
Linking Sensitive Data Book PDF

Author : Peter Christen,Thilina Ranbaduge,Rainer Schnell
Publisher : Unknown
Page : 476 pages
File Size : 55,7 Mb
Release : 2020
Category : Computer security
ISBN : 9783030597061

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Linking Sensitive Data by Peter Christen,Thilina Ranbaduge,Rainer Schnell Pdf

This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques. This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https://dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases. The Book describes how linkage methods work and how to evaluate their performance. It covers all the major concepts and methods and also discusses practical matters such as computational efficiency, which are critical if the methods are to be used in practice - and it does all this in a highly accessible way! David J. Hand, Imperial College, London.

Cache Conscious Column Organization in In-memory Column Stores

David Schwalb,Jens Krüger,Hasso Plattner
Cache Conscious Column Organization in In memory Column Stores Book PDF

Author : David Schwalb,Jens Krüger,Hasso Plattner
Publisher : Universitätsverlag Potsdam
Page : 100 pages
File Size : 48,8 Mb
Release : 2013
Category : Computers
ISBN : 9783869562285

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Cache Conscious Column Organization in In-memory Column Stores by David Schwalb,Jens Krüger,Hasso Plattner Pdf

Cost models are an essential part of database systems, as they are the basis of query performance optimization. Based on predictions made by cost models, the fastest query execution plan can be chosen and executed or algorithms can be tuned and optimised. In-memory databases shifts the focus from disk to main memory accesses and CPU costs, compared to disk based systems where input and output costs dominate the overall costs and other processing costs are often neglected. However, modelling memory accesses is fundamentally different and common models do not apply anymore. This work presents a detailed parameter evaluation for the plan operators scan with equality selection, scan with range selection, positional lookup and insert in in-memory column stores. Based on this evaluation, a cost model based on cache misses for estimating the runtime of the considered plan operators using different data structures is developed. Considered are uncompressed columns, bit compressed and dictionary encoded columns with sorted and unsorted dictionaries. Furthermore, tree indices on the columns and dictionaries are discussed. Finally, partitioned columns consisting of one partition with a sorted and one with an unsorted dictionary are investigated. New values are inserted in the unsorted dictionary partition and moved periodically by a merge process to the sorted partition. An efficient attribute merge algorithm is described, supporting the update performance required to run enterprise applications on read-optimised databases. Further, a memory traffic based cost model for the merge process is provided.

An Introduction to Duplicate Detection

Felix Nauman,Melanie Herschel
An Introduction to Duplicate Detection Book PDF

Author : Felix Nauman,Melanie Herschel
Publisher : Springer Nature
Page : 77 pages
File Size : 49,8 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031018350

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An Introduction to Duplicate Detection by Felix Nauman,Melanie Herschel Pdf

With the ever increasing volume of data, data quality problems abound. Multiple, yet different representations of the same real-world objects in data, duplicates, are one of the most intriguing data quality problems. The effects of such duplicates are detrimental; for instance, bank customers can obtain duplicate identities, inventory levels are monitored incorrectly, catalogs are mailed multiple times to the same household, etc. Automatically detecting duplicates is difficult: First, duplicate representations are usually not identical but slightly differ in their values. Second, in principle all pairs of records should be compared, which is infeasible for large volumes of data. This lecture examines closely the two main components to overcome these difficulties: (i) Similarity measures are used to automatically identify duplicates when comparing two records. Well-chosen similarity measures improve the effectiveness of duplicate detection. (ii) Algorithms are developed to perform on very large volumes of data in search for duplicates. Well-designed algorithms improve the efficiency of duplicate detection. Finally, we discuss methods to evaluate the success of duplicate detection. Table of Contents: Data Cleansing: Introduction and Motivation / Problem Definition / Similarity Functions / Duplicate Detection Algorithms / Evaluating Detection Success / Conclusion and Outlook / Bibliography