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The Complexity of Dependency Detection and Discovery in Relational Databases [article]

Thomas Bläsius, Tobias Friedrich, Martin Schirneck
2021 arXiv   pre-print
The detection problem is to decide whether a dependency of a certain type and size holds in a given database, the discovery problem asks to enumerate all valid dependencies of that type.  ...  Multi-column dependencies in relational databases come associated with two different computational tasks.  ...  in the introduction.  ... 
arXiv:2103.13331v1 fatcat:tyocbt3hwzf3lgjlr3zlb4tqii

Discovery of constraints and data dependencies in relational databases (Extended abstract) [chapter]

Siegfried Bell, Peter Brockhausen
1995 Lecture Notes in Computer Science  
Introduction Data dependencies are the most common type of semantic constraints in relational databases which determine the database design.  ...  Despite the advent of highly automated tools, database design still consists basically of two types of activities: first, reasoning about data types and data dependencies and, second, normalizing the relations  ... 
doi:10.1007/3-540-59286-5_64 fatcat:imjelub44jblpfhawgpqbpr3j4

Database Issues in Knowledge Discovery and Data Mining

Chris Rainsford, John Roddick
1999 Australasian Journal of Information Systems  
The terms "Knowledge Discovery in Databases" and "Data Mining" have been adopted for a field of research dealing with the automatic discovery of knowledge impb'cit within databases.  ...  In recent years both the number and the size of organisational databases have increased rapidly.  ...  -The utility of functional dependencies is not restricted to traditional relational databases.  ... 
doi:10.3127/ajis.v6i2.310 fatcat:57zzkqzw2bdgndhjp5tumgicd4

Certain Investigations on Methods Developed for Efficient Discovery of Matching Dependencies
english

R.San thya, S.La tha, Prof.S.Bala murugan
2015 International Journal of Innovative Research in Computer and Communication Engineering  
This paper details about various methods prevailing in literature for efficient discovery of matching dependencies.  ...  The problem of discovering similarity constraints for matching dependencies from a given database instance is taken into consideration.  ...  Therefore, data dependencies, which have been widely used in the relational database design to set up the integrity constraints.  ... 
doi:10.15680/ijircce.2015.0301041 fatcat:cvxdcvdfx5gzbdnyy5pmlxy53e

Performance Appraisal Of KDD Technique In Shopping Complex Dataset

Dr. K. Kavitha
2016 International Journal Of Engineering And Computer Science  
In this survey, lot of information from the customer and vendors of shopping mall is collected. Vendors are needed to extract the required combination of customers.  ...  To find out the solution of this automatic research application to improve the business strategy is undertaken. This paper highlights the concepts, review the status and limitations.  ...  The importance of deviation detection in data has been recognized in the fields of databases and machine learning for a long time. It has been often viewed as outliers, or noise in data.  ... 
doi:10.18535/ijecs/v5i4.20 fatcat:zoy7skxuvbgwpgwyiisj5bw3oi

Data Profiling

Ziawasch Abedjan, Lukasz Golab, Felix Naumann
2017 Proceedings of the 2017 ACM International Conference on Management of Data - SIGMOD '17  
In particular, we discuss hard problems in data profiling, such as algorithms for dependency discovery and profiling algorithms for dynamic data and streams.  ...  In this tutorial, we highlight the importance of data profiling as part of any data-related usecase, and we discuss the area of data profiling by classifying data profiling tasks and reviewing the state-of-the-art  ...  Dependency discovery We then zoom in on dependency discovery, and give an in-depth technical description of strategies that tackle the exponential complexity of dependency discovery tasks.  ... 
doi:10.1145/3035918.3054772 dblp:conf/sigmod/AbedjanGN17 fatcat:dwqqb6w6pzfu7l5nkz3m67oxsq

A survey of graph-based algorithms for discovering business processes

Riyanarto Sarno, Kelly Rossa Sungkono
2019 IJAIN (International Journal of Advances in Intelligent Informatics)  
Algorithms of process discovery help analysts to understand business processes and problems in a system by creating a process model based on a log of the system.  ...  Those algorithms claimed that those have less time complexity because of the graph-database ability to store relationships.  ...  Graph-based algorithms cannot handle OR relation with two branches because the number of arcs is similar to AND relation in the graph-database.  ... 
doi:10.26555/ijain.v5i2.296 fatcat:oe32uxdf7bhwhlwi7d6fczwahi

Performance mining of large-scale data-intensive applications

C. Carothers, B.K. Szymanski, M. Zaki
2002 Proceedings 16th International Parallel and Distributed Processing Symposium  
PerfMiner will detect opportunities for both the critical path optimization and the beneficial application of speculative execution using parallel data mining on a persistent, run-time generated database  ...  While the performance benefits of this approach can be tremendous, it can be very difficult to determine in large complex systems when and where speculation can be exploited.  ...  While the performance benefits of this approach can be tremendous, it can be very difficult to determine in large complex systems when and where speculation can be exploited.  ... 
doi:10.1109/ipdps.2002.1016582 dblp:conf/ipps/CarothersSZ02 fatcat:tydhl26dfnertiq4kwgcqxkgu4

Improving efficiency for discovering business processes containing invisible tasks in non-free choice

Riyanarto Sarno, Kelly Rossa Sungkono, Muhammad Taufiqulsa'di, Hendra Darmawan, Achmad Fahmi, Kuwat Triyana
2021 Journal of Big Data  
The process discovery algorithms have been developed rapidly to discover several types of relations, i.e., choice relations, non-free choice relations with invisible tasks.  ...  The checking processes are time-consuming and result in high computing times of $$\alpha ^{\$ }$$ α $ .  ...  The capability of storing relations in a graph database can simplify the rules of process discovery because several relations of a process model can be constructed based on other discovered relations.  ... 
doi:10.1186/s40537-021-00487-x fatcat:z46gs5jxwrdwnlyyuwaypjdekm

Tracking configuration changes proactively in large IT environments

M. Soni, V. R. Madduri, M. Gupta, P. De
2012 2012 IEEE Network Operations and Management Symposium  
We track cross-product dependency by enhancing the configuration model of the service. We show the efficacy of our techniques by extending the configuration model of a complex IT environment.  ...  Maintaining consistent views of components in complex IT environments is challenging due to frequent changes applied to the systems.  ...  WAS uses a database to store and maintain its application data. Application level dependencies are represented using directed arrows in the figure.  ... 
doi:10.1109/noms.2012.6211946 dblp:conf/noms/SoniMGD12 fatcat:mbrcjyt2qzewzfw7ilks74zbce

Integration of Domain Knowledge for Outlier Detection in High Dimensional Space [chapter]

Sakshi Babbar
2009 Lecture Notes in Computer Science  
The role of outlier or anomaly detection is to discover unusual and rare patterns in data.  ...  The focus of the proposal is to determine whether logic models like Probabilistic Relational Model, Default Reasoning and Ontologies can be used to integrate domain knowledge in the outlier discovery process  ...  The core idea is to investigate the use of Probabilistic Relational Models (PRM), Default Reasoning and Ontologies in the outlier discovery process.  ... 
doi:10.1007/978-3-642-04205-8_32 fatcat:vc2avvzxjnat3acjhga2jyzoue

Detailed Investigation on Strategies Developed for Effective Discovery of Matching Dependencies
english

R.SAN THYA, S.LA THA, PROF.S.BALA MURUGAN, S.CHARA NYAA
2015 International Journal of Innovative Research in Computer and Communication Engineering  
CONCLUSION AND FUTURE WORK This paper detailed about various methods prevailing in literature for efficient discovery of matching dependencies.  ...  This paper details about various methods prevailing in literature for efficient discovery of matching dependencies.  ...  Therefore, data dependencies, which have been widely used in the relational database design to set up the integrity constraints.  ... 
doi:10.15680/ijircce.2015.0301049 fatcat:uto4qs5g4zeephyop4n6iedd3i

DISCOVERY OF MOLECULARLY TARGETED THERAPIES

Kelly Regan, Zachary Abrams, Michael Sharpnack, Arunima Srivastava, Kun Huang, Nigam Shah, Philip R O Payne
2016 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
Overview of Session Contributions The utility and impact of multi-modeling approaches to integrative biological and clinical analyses, including hypothesis discovery operations such as those related to  ...  the prioritization of gene mutations causing drug resistance (Verkhivker), and the facilitation of viable community detection (Yu et al); and 3) the incorporation of prior knowledge into in silico methods  ... 
pmid:26776168 pmcid:PMC4874173 fatcat:ccbs2avjdja3lahhjnaifrqgjq

DISCOVERY OF MOLECULARLY TARGETED THERAPIES

KELLY REGAN, ZACHARY ABRAMS, MICHAEL SHARPNACK, ARUNIMA SRIVASTAVA, KUN HUANG, NIGAM SHAH, PHILIP R.O. PAYNE
2015 Biocomputing 2016  
versions of the database.  ...  Overview of Session Contributions The utility and impact of multi-modeling approaches to integrative biological and clinical analyses, including hypothesis discovery operations such as those related to  ... 
doi:10.1142/9789814749411_0001 fatcat:5zfvhqmbhzb6zcqyo3zezsoyeu

Geographic Data Mining and Knowledge Discovery An Overview [chapter]

Jiawei Han, Harvey Miller
2009 Geographic Data Mining and Knowledge Discovery, Second Edition  
Knowledge discovery from databases Knowledge discovery from databases (KDD) is a response to the enormous volumes of data being collected and stored in operational and scientific databases.  ...  KNOWLEDGE DISCOVERY AND DATA MINING In this section of the chapter, we provide a general overview of knowledge discovery and data mining.  ...  Acknowledgments: Thanks to Mark Gahegan and Phoebe McNeally for some helpful comments on this chapter.  ... 
doi:10.1201/9781420073980.ch1 fatcat:bfh4kasvlbhylgwu2afp5wrqbq
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