Adaptive Windows For Duplicate Detection
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Adaptive Windows For Duplicate Detection
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Author : Uwe Draisbach
language : en
Publisher: Universitätsverlag Potsdam
Release Date : 2012
Adaptive Windows For Duplicate Detection written by Uwe Draisbach and has been published by Universitätsverlag Potsdam this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
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).
Adaptive Detection Of Approximately Duplicate Database Records And The Database Integration Approach To Information Discovery
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Author : Alvaro Edmundo Monge
language : en
Publisher:
Release Date : 1997
Adaptive Detection Of Approximately Duplicate Database Records And The Database Integration Approach To Information Discovery written by Alvaro Edmundo Monge and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Model Driven Engineering Of Adaptation Engines For Self Adaptive Software
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Author : Thomas Vogel
language : en
Publisher: Universitätsverlag Potsdam
Release Date : 2013
Model Driven Engineering Of Adaptation Engines For Self Adaptive Software written by Thomas Vogel and has been published by Universitätsverlag Potsdam this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.
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.
Linking And Mining Heterogeneous And Multi View Data
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Author : Deepak P
language : en
Publisher: Springer
Release Date : 2018-12-13
Linking And Mining Heterogeneous And Multi View Data written by Deepak P and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-13 with Technology & Engineering categories.
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.
Population Reconstruction
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Author : Gerrit Bloothooft
language : en
Publisher: Springer
Release Date : 2015-07-22
Population Reconstruction written by Gerrit Bloothooft and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-22 with Social Science categories.
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
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Author : Juanzi Li
language : en
Publisher: Springer
Release Date : 2018-01-18
Knowledge Graph And Semantic Computing Language Knowledge And Intelligence written by Juanzi Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-18 with Computers categories.
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.
Proceedings Of The 9th Ph D Retreat Of The Hpi Research School On Service Oriented Systems Engineering
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Author : Meinel, Christoph
language : en
Publisher: Universitätsverlag Potsdam
Release Date : 2017-03-23
Proceedings Of The 9th Ph D Retreat Of The Hpi Research School On Service Oriented Systems Engineering written by Meinel, Christoph and has been published by Universitätsverlag Potsdam this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-23 with Computers categories.
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.
Recent Trends In Image Processing And Pattern Recognition
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Author : K. C. Santosh
language : en
Publisher: Springer Nature
Release Date : 2021-02-25
Recent Trends In Image Processing And Pattern Recognition written by K. C. Santosh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-25 with Computers categories.
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.
Advances In Knowledge Discovery And Data Mining
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Author : Dinh Phung
language : en
Publisher: Springer
Release Date : 2018-06-16
Advances In Knowledge Discovery And Data Mining written by Dinh Phung and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-16 with Computers categories.
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
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Author : Felix Nauman
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
An Introduction To Duplicate Detection written by Felix Nauman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
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