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A Tool for Inference Detection and Knowledge Discovery in Databases [chapter]

Surath Rath, Dominic Jones, John Hale, Sujeet Shenoi
1996 IFIP Advances in Information and Communication Technology  
This paper uses a powerful knowledge discovery formalism for modeling and identifying latent inference channels in relational databases.  ...  The inference discovery methodology supports the analysis of precise and imprecise inference in database schemes and extensions.  ...  INFERENCE DETECTION AND KNOWLEDGE DISCOVERY The process of knowledge discovery in relational databases involves the manipulation of multiple relations (Agrawal et al., 1993; Kaufman et al., 1991; Matheus  ... 
doi:10.1007/978-0-387-34932-9_20 fatcat:xlkbmzopebd6fbkflu4lj3q4pa

Proposal of Chance Index in Co-occurrence Visualized Network

Yukihiro Takayama, Ryosuke Saga
2015 International Journal of Knowledge Engineering-IACSIT  
However, this reasoning process has problem that chance discovery is difficult because chance discovery depends on experience or background knowledge of analysts.  ...  In prior research of chance discovery, in the chance discovery process, it is required that analysts infer chance from visualized network, because it is difficult that to solve problem like to guess the  ...  Research(A) and (C), 25240049, 25420448.  ... 
doi:10.7763/ijke.2015.v1.14 fatcat:w3bisxypefe4rovydvvrzrkvbm

Knowledge discovery computing for management

Hector John T. Manaligod, Michael Joseph S. Diño, Sunmoon Jo, Roy C. Park
2020 Journal of Special Topics in Information Technology and Management  
Yonghua Ji and Prof. Vijay Mookerjee, the Editor-in-Chief of Information Technology and Management for support and great efforts throughout the publication.  ...  In the circumstance where knowledge is changed and is expanded, it is necessary to develop Knowledge Discovery Computing in order to detect knowledge changes and expansions accordingly.  ...  learning to generate inferred knowledge which can be used to obtain large-high-quality information and expand knowledge.  ... 
doi:10.1007/s10799-020-00315-3 fatcat:g2fxepxdkna45mdiqaf5yptie4

Knowledge Discovery in Tweets for the Prevention of Inference Attacks

D. Sai Eswari, Afreen Rafiq, R. Deepthi
2017 Indian Journal of Science and Technology  
Objectives: The objective of our proposed study is to eliminate the inference attacks through knowledge discovery process without compromising the accuracy of the systems.  ...  A supervised learning model that prevents the inference attacks using hit analytics and metadata knowledge derivation systems.  ...  Prevention of Inference Attacks using Knowledge Discovery Process This section depicts the workflow of proposed methodology using real time dataset, Twitter using an enhanced public hit analytics and metadata  ... 
doi:10.17485/ijst/2017/v10i34/114132 fatcat:wyhv5ffx5bck5mrgehuw3xsyoa

Knowledge discovery from sensor data (SensorKDD)

Olufemi A. Omitaomu, Ranga Raju Vatsavai, Auroop R. Ganguly, Nitesh V. Chawla, Joao Gama, Mohamed Medhat Gaber
2010 SIGKDD Explorations  
Extracting knowledge and emerging patterns from sensor data is a nontrivial task. The challenges for the knowledge discovery community are expected to be immense.  ...  In addition, emerging societal problems require knowledge discovery solutions that are designed to investigate anomalies, changes, extremes and nonlinear processes, and departures from the normal.  ...  , and Dr.  ... 
doi:10.1145/1809400.1809417 fatcat:jrtrixjfzzgo3bdlelcyldihom

Knowledge discovery from sensor data (SensorKDD)

Ranga Raju Vatsavai, Olufemi A. Omitaomu, Joao Gama, Nitesh V. Chawla, Mohamed Medhat Gaber, Auroop R. Ganguly
2008 SIGKDD Explorations  
Extracting knowledge and emerging patterns from sensor data is a nontrivial task. The challenges for the knowledge discovery community are expected to be immense.  ...  In addition, emerging societal problems require knowledge discovery solutions that are designed to investigate anomalies, changes, extremes and nonlinear processes, and departures from the normal.  ...  , and Dr.  ... 
doi:10.1145/1540276.1540297 fatcat:72jirtrxibbrpmpfcwrivmedjm

DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions [article]

Amit Sharma, Vasilis Syrgkanis, Cheng Zhang, Emre Kıcıman
2021 arXiv   pre-print
of the graph, and developing validation tests that can better detect errors, both for average and conditional treatment effects.  ...  Our experience with DoWhy highlights a number of open questions for future research: developing new ways beyond causal graphs to express assumptions, the role of causal discovery in learning relevant parts  ...  However, the fields of causal discovery and inference have evolved separately and many challenges remain for causal discovery to be useful in the downstream effect inference task.  ... 
arXiv:2108.13518v1 fatcat:zlsqcpmfmnflvdt5djxddok6ee

A Survey on Truth Discovery [article]

Yaliang Li, Jing Gao, Chuishi Meng, Qi Li, Lu Su, Bo Zhao, Wei Fan, Jiawei Han
2015 arXiv   pre-print
In this survey, we focus on providing a comprehensive overview of truth discovery methods, and summarizing them from different aspects.  ...  Several truth discovery methods have been proposed for various scenarios, and they have been successfully applied in diverse application domains.  ...  and infer true information.  ... 
arXiv:1505.02463v2 fatcat:sqvfxldfqjbtlexi5gqaldtgqq

Research Challenges in Ubiquitous Knowledge Discovery [chapter]

Michael May, Bettina Berendt, Antoine Cornuéjols, João Gama, Fosca Giannotti, Andreas Hotho, Donato Malerba, Ernestina Menesalvas, Katharina Morik, Rasmus Pedersen, Lorenza Saitta, Yücel Saygin (+2 others)
2008 Chapman & Hall/CRC Data Mining and Knowledge Discovery Series  
This chapter is based on the discussions in the network, and contributions from project partners are gratefully acknowledged.  ...  distributed and mobile systems and advanced knowledge discovery systems.  ...  In a typical scenario for ubiquitous knowledge discovery the learner has access to past and maybe present data from a time-varying distribution (see last section), and has to make inferences about the  ... 
doi:10.1201/9781420085877.ch7 fatcat:4mhq33nalnabhg2epkw5y3fxqu

Semantic-Based Knowledge Dissemination and Extraction in Smart Environments

M. Ruta, F. Scioscia, E. Di Sciascio, D. Rotondi, S. Piccione
2013 2013 27th International Conference on Advanced Information Networking and Applications Workshops  
Logic-based standard and non-standard inference services can be exploited in matchmaking and negotiation for service/resource discovery and on-the-fly reasoning, as well as for large-scale analyses.  ...  Features of the proposed approach are detailed and discussed w.r.t. the key requirements and research challenges of next-generation smart cities and factory automation.  ...  ACKNOWLEDGMENTS The authors acknowledge partial support of EU ECTP 2012-14 project "GAIA: Generalized Automatic exchange of port Information Area", and EU FP7 Project IoT@Work (Grant Agreement N. 257367  ... 
doi:10.1109/waina.2013.249 dblp:conf/aina/RutaSSRP13 fatcat:d43rbifwmvd2dpjvegte4dxs5e

Content-based inference of hierarchical structural grammar for recurrent TV programs using multiple sequence alignment

Bingqing Qu, Felicien Vallet, Jean Carrive, Guillaume Gravier
2014 2014 IEEE International Conference on Multimedia and Expo (ICME)  
Using a set of basic event detectors and simple filtering techniques to detect repeating elements of interest, a symbolic representation of each episode is derived based on minimal domain knowledge.  ...  These methods can discover key repeating elements, such as jingles and separators, however they cannot infer the entire structure of a program.  ...  For further discovery, based on the hierarchical method described in section 3.3, the chapters are then structured and finergrain grammars are inferred.  ... 
doi:10.1109/icme.2014.6890295 dblp:conf/icmcs/QuVCG14 fatcat:oascgn4csvh3fciyvm3eatziha

Learning Probabilistic Graphical Models for Identification of Dark Matter Signatures in Noisy Data

Christina Peters, Aaron Higuera, Shixiao Liang, Alex Oranday, Venkat Roy, Waheed Bajwa, Christopher Tunnell, Hagit Shatkay
2020 Zenodo  
The learned Probabilistic Graphical Model can be used to infer interaction positions of experimentally measured events, and thus uncover the meaningful signals in noisy detector data.  ...  As a way of embedding domain knowledge into the solution, we propose using the framework of probabilistic graphical models, which can readily incorporate physical constraints and prior knowledge.  ...  being used to infer precise and accurate positions and energies.  ... 
doi:10.5281/zenodo.5426347 fatcat:ep3nl6bal5d5zk4t7rbxmxmu7u

SemaKoDE: Hybrid System for Knowledge Discovery in Sensor-Based Smart Environments [chapter]

Stefan Negru
2012 Lecture Notes in Computer Science  
This article describes a conceptual hybrid architecture for a knowledge discovery system, able to automatically annotate, reason, classify and operate with sensor data.  ...  The adoption of semantic web technologies to enrich sensor and link data represents an adequate methodology that facilitates the processes of reasoning, classification and other types of automation.  ...  Discovery Layer. The Discovery Layer encapsulates both data mining [7] and reasoning algorithms as presented in [1, 4] , used for knowledge discovery.  ... 
doi:10.1007/978-3-642-31753-8_41 fatcat:ljqarp3qureeri74budgrrub7u

Page 655 of None Vol. 37, Issue 969 [page]

1874 None  
He maintains that all inference may be resolved into the detection of likeness. In all acts of inference, however different their apparent forms, there is involved a detection of likeness.  ...  The universal is merely a memorandum, or aid to memory, and the new knowledge consists in the unexamined case to which I am entitled to infer from the examined cases.  ... 

Detecting privacy leaks using corpus-based association rules

Richard Chow, Philippe Golle, Jessica Staddon
2008 Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08  
Detecting inferences in documents is critical for ensuring privacy when sharing information. In this paper, we propose a refined and practical model of inference detection using a reference corpus.  ...  These experiments demonstrate that our techniques are practical, and that our model of inference based on word co-occurrence is well-suited to efficient inference detection.  ...  We would also like to thank the anonymous reviewers of previous versions of this paper and Tomoyoshi Takebayashi and Toshihiro Sonoda of Fujitsu Laboratories Ltd. for many helpful comments.  ... 
doi:10.1145/1401890.1401997 dblp:conf/kdd/ChowGS08 fatcat:t7rzipw4ofalfdifn4oju476tq
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