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Functional and embedded dependency inference: a data mining point of view

Noël Novelli, Rosine Cicchetti
2001 Information Systems  
The two algorithms fitting in such a trend are TANE and Dep-Miner. They strongly improve previous proposals. In this paper, we propose a new approach adopting a data mining point of view.  ...  Embedded dependencies capture a knowledge specially relevant in all fields where materialized data sets are managed (e.g. materialized views widely used in data warehouses). r  ...  The approach presented in this paper fits in such a trend and aims to discover minimal functional dependencies, and embedded dependencies which are valid over a subset of the original data source.  ... 
doi:10.1016/s0306-4379(01)00032-1 fatcat:wy46xeyt4jevlmgnb2ojqahnqm

Model inference for spreadsheets

Jácome Cunha, Martin Erwig, Jorge Mendes, João Saraiva
2014 Automated Software Engineering : An International Journal  
Thus, we have also introduced a mapping between relational schemas and ClassSheets. A ClassSheet controls further changes to the spreadsheet and safeguards it against a large class of formula errors.  ...  The developed tool is a contribution to spreadsheet (reverse) engineering, because it fills an important gap and allows a promising design method (ClassSheets) to be applied to a huge collection of legacy  ...  e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-010048.  ... 
doi:10.1007/s10515-014-0167-x fatcat:4oho2shmdrf2zftw7vpz7pdgnq

Variational Inference for Gaussian Process Modulated Poisson Processes [article]

Chris Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts
2015 arXiv   pre-print
Such point processes are used in a variety of domains, including neuroscience, geo-statistics and astronomy, but their use is hindered by the computational cost of existing inference schemes.  ...  The resulting algorithm is shown to outperform standard methods on synthetic examples, coal mining disaster data and in the prediction of Malaria incidences in Kenya.  ...  ACKNOWLEDGEMENTS The authors would like to thank James Hensman and Neil Lawrence for helpful discussions. Chris Lloyd is funded by a DSTL National PhD Scheme Studentship.  ... 
arXiv:1411.0254v3 fatcat:h37sshmiqvdsjgblllhiekhg7e

Semantic patch inference

Jesper Andersen, Anh Cuong Nguyen, David Lo, Julia L. Lawall, Siau-Cheng Khoo
2012 Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering - ASE 2012  
Program dependence graph A program dependence graph (PDG) [21] is a graph representation of a program where the nodes of the graph are statements and predicates and edges represent data and control dependencies  ...  In order to find frequently occurring subsequences of statements CP-Miner uses a variant of the sequence data mining algorithm by Agrawal and Srikant [1] .  ...  and thus tu _ merged should also be empty. prgtu_lists is a singleton: In this case there is no other set of patches to fuse with, so we simply let tu _ merged be the only list in prgtu_lists at this point  ... 
doi:10.1145/2351676.2351753 dblp:conf/kbse/AndersenNLLK12 fatcat:4pnomtho6rbhji47sv6u2jhlt4

Combined Survey Sampling Inference

Steven M Lalonde
2004 Technometrics  
BOOK REVIEWS All chapters begin with nice overviews and conclude with sections devoted to "Further Reading."  ...  Competitors for this particular book are limited to books on logistic regression or generalized linear modeling, such as that by Myers, Montgomery, and Vining (2002) , which was reviewed for Technometrics  ...  for a host of unexceptional data mining books.  ... 
doi:10.1198/tech.2004.s750 fatcat:qpilh36ovfgahpfia2l4hevl3a

Structure-based function inference using protein family-specific fingerprints

Deepak Bandyopadhyay, Jun Huan, Jinze Liu, Jan Prins, Jack Snoeyink, Wei Wang, Alexander Tropsha
2006 Protein Science  
In validation experiments, we infer the function of new members added to SCOP families and we discriminate between structurally similar, but functionally divergent TIM barrel families.  ...  We describe a method to assign a protein structure to a functional family using family-specific fingerprints.  ...  For each node of the fingerprints and of a query structure, we create an index vector that stores the labels of neighboring nodes and edges connected to them, and consider a query embedding a node in a  ... 
doi:10.1110/ps.062189906 pmid:16731985 pmcid:PMC2265098 fatcat:qjvjvn6itbavhhlwpqmvtytl2y

Automated API Property Inference Techniques

Martin P. Robillard, Eric Bodden, David Kawrykow, Mira Mezini, Tristan Ratchford
2013 IEEE Transactions on Software Engineering  
Our survey provides a synthesis of this complex technical field along different dimensions of analysis: properties inferred, mining techniques, and empirical results.  ...  This paper provides a comprehensive survey of over a decade of research on automated property inference for APIs.  ...  ACKNOWLEDGMENTS This work has been made possible by the generous support of the Alexander von Humboldt Foundation, the German Federal Ministry of Education and Research (BMBF) within EC SPRIDE and by the  ... 
doi:10.1109/tse.2012.63 fatcat:pmoh6iwdvjfunnk45rmlsqfgxa

The Inference Problem and Pervasive Computing

Catherine Ann Dwyer
2009 Social Science Research Network  
A potential solution to this impasse may be found in a privacy condition from the data mining literature known as the -inference problem.‖ The inference problem occurs in data mining when confidential  ...  This paper will discuss methods used in data mining to limit the inference problem, and discuss their application to pervasive computing.  ...  Pervasive computing depends on the collection of millions of data points from complex sensor and computing structures.  ... 
doi:10.2139/ssrn.1508513 fatcat:koqg2knlvnhcfkr5bokkx5zkb4

Automatically Inferring ClassSheet Models from Spreadsheets

Jacome Cunha, Martin Erwig, Joao Saraiva
2010 2010 IEEE Symposium on Visual Languages and Human-Centric Computing  
The benefit of creating a spreadsheet is lacking since the legacy spreadsheet already exists, and (B) existing data must be transferred into the new model-generated spreadsheet.  ...  The resulting spreadsheet guides further changes and provably safeguards the spreadsheet against a large class of formula errors.  ...  We use data mining techniques to reason about spreadsheet data and to infer functional dependencies among columns.  ... 
doi:10.1109/vlhcc.2010.22 dblp:conf/vl/CunhaES10 fatcat:ibbtezrycvh57krwmnnxwiw2g4

Structural Inference of Sensor-Based Measurements [chapter]

Robert P. W. Duin, Elżbieta Pękalska
2006 Lecture Notes in Computer Science  
In particular it will be discussed when probabilistic assumptions are needed, leading to a statistically-based inference of the structure, and when a pure, non-probabilistic structural inference scheme  ...  This paper aims to summarize the problems and possibilities of general structural inference approaches for the family of sensor-based measurements: images, spectra and time signals, assuming a continuity  ...  However, we hope that a contribution is made towards the solution by our a summary of problems and possibilities in this area, presented from a specific point of view.  ... 
doi:10.1007/11815921_4 fatcat:b57ddbvmz5hs5bylqskvh3wrvm

Causal Inference of Script Knowledge [article]

Noah Weber, Rachel Rudinger, Benjamin Van Durme
2020 arXiv   pre-print
When does a sequence of events define an everyday scenario and how can this knowledge be induced from text?  ...  Through both human and automatic evaluations, we show that the output of our method based on causal effects better matches the intuition of what a script represents  ...  Before a causal query such as Eqn. 1 can be estimated we must first establish identifiability (Shpitser and Pearl, 2008) : can the causal query be written as a function of (only) the observed data?  ... 
arXiv:2004.01174v1 fatcat:rzkmeqbi5vbj3loe4kkqgnqloq

Exploiting Non-Linear Structure in Astronomical Data for Improved Statistical Inference [article]

Ann B. Lee, Peter E. Freeman
2011 arXiv   pre-print
To utilize such data and make accurate inferences, it is crucial to transform the data into a simpler, reduced form.  ...  We outline some computational and statistical challenges that remain, and we discuss some promising future directions for astronomy and data mining.  ...  These eigenmodes can be viewed both as (i) coordinates of the data, as in Fig. 1 , and as (ii) orthogonal basis functions for curve estimation.  ... 
arXiv:1111.0911v1 fatcat:nnbxgxy6rvaz3fe2cr6zosrrou

Fine-Grained Urban Flow Inference [article]

Kun Ouyang, Yuxuan Liang, Ye Liu, Zekun Tong, Sijie Ruan, Yu Zheng,, David S. Rosenblum
2020 arXiv   pre-print
A technique is required to reduce the number of deployed devices, while preventing the degeneration of data accuracy and granularity.  ...  In this paper, we present an approach for inferring the real-time and fine-grained crowd flows throughout a city based on coarse-grained observations.  ...  For instance, areas A and B are "hard areas" to be inferred, as A (Sanyuan bridge, the main entrance to downtown) and B (Sihui bridge, a huge flyover) are two of the top congestion points in Beijing.  ... 
arXiv:2002.02318v1 fatcat:l2jkjhjx2bavzaarcm4sxbdsdu

Inferring event stream abstractions

Sean Kauffman, Klaus Havelund, Rajeev Joshi, Sebastian Fischmeister
2018 Formal methods in system design  
The approach builds a hierarchy of event abstractions for telemetry visualization and querying to aid human comprehension.  ...  We illustrate the solution with several examples, a performance evaluation, and a real telemetry analysis scenario.  ...  In contrast to most runtime verification systems, however, the nfer formalism does not directly operate on such traces from a semantics point of view.  ... 
doi:10.1007/s10703-018-0317-z fatcat:i5226txdwzcprikyjx7xpdmp64

Inferring Neuronal Network Connectivity from Spike Data: A Temporal Datamining Approach [article]

Debprakash Patnaik (Electical Engg. Dept., Indian Institute of Science, Bangalore), and P. S. Sastry (Electrical Engg. Dept., Indian Institute of Science, Bangalore), K. P. Unnikrishnan (General Motors R&D, Warren)
2008 arXiv   pre-print
In the frequent episode discovery framework, the data is viewed as a sequence of events, each of which is characterized by an event type and its time of occurrence and episodes are certain types of temporal  ...  Inferring the underlying neuronal connectivity patterns from such multi-neuronal spike train data streams is a challenging statistical and computational problem.  ...  The main objective of this paper is to show that techniques from Temporal Data mining could offer novel and useful points of view for tackling some of the issues involved in analyzing spike train data.  ... 
arXiv:0803.0450v2 fatcat:nwrjrnxgw5bghjkceaq33kfkkm
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