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A model of exploratory search for evaluating its systems & applications

Emilie Palagi, Alain Giboin, Fabien Gandon, Raphaël Troncy
2018 Proceedings of the 30th Conference on l'Interaction Homme-Machine - IHM '18  
Aiming to elaborate evaluation methods based on an appropriate model of exploratory search, we propose in this paper a model of the exploratory search process compliant with the acknowledged exploratory  ...  Current evaluation methods of exploratory search systems are still incomplete as they are not fully based on a suitable model of the exploratory search process: as such they cannot be used to determine  ...  Acknowledgment This work was partly funded by the French Government (National Research Agency, ANR) through the "Investments for the Future" Program reference #ANR-11-LABX-0031-01.  ... 
doi:10.1145/3286689.3286716 dblp:conf/ihm/PalagiGGT18 fatcat:ozifhahmdbdpfchu4mjidwpjmi

Greed Is Good: Rapid Hyperparameter Optimization and Model Selection Using Greedy k-Fold Cross Validation

Daniel S. Soper
2021 Electronics  
Evaluating each candidate model commonly relies on k-fold cross validation, wherein the data are randomly subdivided into k folds, with each fold being iteratively used as a validation set for a model  ...  The greedy early stopping method is shown to outperform a competing, state-of-the-art early stopping method both in terms of search time and the quality of the ML models selected by the algorithm.  ...  model search process.  ... 
doi:10.3390/electronics10161973 fatcat:2eufnxczhbczdhtcjsfdpc6kpi

Autotune

Patrick Koch, Oleg Golovidov, Steven Gardner, Brett Wujek, Joshua Griffin, Yan Xu
2018 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '18  
Given the inherent expense of training numerous candidate models, we demonstrate the effectiveness of Autotune's search methods and the efficient distributed and parallel paradigms for training and tuning  ...  The hyperparameters usually drive both the efficiency of the model training process and the resulting model quality. For hyperparameter tuning, machine learning algorithms are complex black-boxes.  ...  The Bayesian search method beats the default search method for the first 150 evaluations, after which its rate of improvement slows.  ... 
doi:10.1145/3219819.3219837 dblp:conf/kdd/KochGGWGX18 fatcat:m5bpqabztjbxpdqdv32qg46boi

A Survey of Definitions and Models of Exploratory Search

Emilie Palagi, Fabien Gandon, Alain Giboin, Raphaël Troncy
2017 Proceedings of the 2017 ACM Workshop on Exploratory Search and Interactive Data Analytics - ESIDA '17  
The complexity of the task and the difficulty of defining this activity are reflected in the limits of existing evaluation methods for exploratory search systems.  ...  In order to improve them, we intend to design an evaluation method based on a user-centered model of exploratory search.  ...  ACKNOWLEDGMENT This work was partly funded by the French Government (National Research Agency, ANR) through the "Investments for the Future" Program reference #ANR-11-LABX-0031-01.  ... 
doi:10.1145/3038462.3038465 dblp:conf/iui/PalagiGGT17 fatcat:s7o7duuqfjglnbw3lob2srjbaa

An Extensible Platform for Process Model Search and Evaluation

Christian Ress, Matthias Kunze
2013 International Conference on Business Process Management  
We present a platform that integrates a number of process model search techniques and provides a uniform interface for query formulation and search result presentation, as well as a framework to evaluate  ...  a particular search technique.  ...  The presentation layer includes a simplistic, web-based process model editor, that allows formulating queries as regular process models, as this is typical for similarity search and has been proposed for  ... 
dblp:conf/bpm/RessK13 fatcat:dnlmkykifzbqhf465iwze7asku

Rain or shine? Forecasting search process performance in exploratory search tasks

Chirag Shah, Chathra Hendahewa, Roberto González-Ibáñez
2015 Journal of the Association for Information Science and Technology  
In effect, the work reported here provides a framework for evaluating search processes during exploratory search tasks and predicting search performance.  ...  We propose a machine-learning-based method to dynamically evaluate and predict search performance several time-steps ahead at each given time point of the search process during an exploratory search task  ...  Next, our method for running experiments, which included features to extract data from user actions during a search process, is given in the Evaluation Method section (addressing RQ1).  ... 
doi:10.1002/asi.23484 fatcat:mtd244xxnzblteakt67lve357u

Scout: An Experienced Guide to Find the Best Cloud Configuration [article]

Chin-Jung Hsu, Vivek Nair, Tim Menzies, Vincent W. Freeh
2018 arXiv   pre-print
Based on this work, we conclude that (i) low-level performance information is necessary for finding the right cloud configuration in an effective, efficient and reliable way, and (ii) a search method can  ...  Such hints enable SCOUT to navigate through the search space more efficiently---only spotlight region will be searched. We evaluate SCOUT with 107 workloads on Apache Hadoop and Spark.  ...  At the start of the search process for a workload (w), none of the cloud configurations are evaluated.  ... 
arXiv:1803.01296v1 fatcat:iw44p3gqtjf2zf7z25cujhyjx4

A Framework for Model Search Across Multiple Machine Learning Implementations [article]

Yoshiki Takahashi, Masato Asahara, Kazuyuki Shudo
2019 arXiv   pre-print
Model searches, which explore to find an optimal ML algorithm and hyperparameter values for the target problem, play a critical role in such improvements.  ...  During a model search, data scientists typically use multiple ML implementations to construct several predictive models; however, it takes significant time and effort to employ multiple ML implementations  ...  The random search method evaluates several sets of randomly selected values from the search ranges specified for each hyperparameter.  ... 
arXiv:1908.10310v1 fatcat:3yuyqst7a5dgplb5npxjiojp5e

Stimulating R&D by Finding Frugal Patents: A Process Model and a Comparison Between Different Evaluation Methods

Lena L. Kronemeyer, Raik Draeger, Martin G. Moehrle
2021 IEEE transactions on engineering management  
For this purpose, we present a process model in four steps, and particularly analyze the evaluation step by applying different text-mining methods, namely search string refinement and topic modeling.  ...  Testing the process model in the technological field of white goods, we find that the process model as a whole as well as both evaluation methods are able to detect frugal patent candidates.  ...  Furthermore, it compares two methods that may be applied in the evaluation step of the process model, namely, search string refinement and topic modeling.  ... 
doi:10.1109/tem.2021.3058003 fatcat:6h72ghp6vbainci6oanzsdxaia

Neural Architecture Search using Covariance Matrix Adaptation Evolution Strategy [article]

Nilotpal Sinha, Kuan-Wen Chen
2021 arXiv   pre-print
We also used an architecture-fitness table (AF table) for keeping record of the already evaluated architecture, thus further reducing the search time.  ...  previous evolution-based methods while reducing the search time significantly.  ...  Furthermore, we are grateful to the National Center for High-performance Computing for computer time and facilities.  ... 
arXiv:2107.07266v1 fatcat:whe32lvl45fp5eyd7eepfrtrky

A Proposal for User-Focused Evaluation and Prediction of Information Seeking Process

Chirag Shah
2013 European Workshop on Human-Computer Interaction and Information Retrieval  
In effect, the work reported here provides a new framework for evaluating search processes and predicting search performance.  ...  Specifically, we propose a machine-learning based method to dynamically evaluate and predict search performance several time-steps ahead at each given time point of the search process during an exploratory  ...  The author is also grateful to his PhD students Chathra Hendahewa and Roberto Gonzalez-Ibanez for their valuable contributions to this work.  ... 
dblp:conf/eurohcir/Shah13 fatcat:vhohzuhliranrn67s4vh3gnqbu

Kernel Method Based Human Model for Enhancing Interactive Evolutionary Optimization

Yan Pei, Qiangfu Zhao, Yong Liu
2015 The Scientific World Journal  
From experimental evaluation results with a pseudo-IEC user, our proposed model and method can enhance IEC search significantly.  ...  The human model is established by this method for predicting potential perceptual knowledge of human. With the human model, we design an evolution control method to enhance IEC search.  ...  In our experimental evaluation, we apply a human model with an evolution control method in four GMM for enhancing IEC search.  ... 
doi:10.1155/2015/185860 pmid:25879050 pmcid:PMC4386548 fatcat:u5pehbib3bfkfbt4n4digwpiaq

A Survey on Surrogate-assisted Efficient Neural Architecture Search [article]

Shiqing Liu, Haoyu Zhang, Yaochu Jin
2022 arXiv   pre-print
Then, the methods for evaluating network candidates under the proxy metrics are systematically discussed.  ...  However, NAS is still laborious and time-consuming because a large number of performance estimations are required during the search process of NAS, and training DNNs is computationally intensive.  ...  During the optimization process, no new data can be actively generated for real evaluation, and only the predictions provided by the trained surrogate model can guide the evolutionary search.  ... 
arXiv:2206.01520v2 fatcat:4artwgoyw5fzph2m25xanowywe

Efficient methods of automatic calibration for rainfall-runoff modelling in the Floreon+ system

Matyáš Theuer, Radim Vavřík, Vít Vondrák, Štěpán Kuchař, Boris Šír, Antonio Portero
2017 Neural Network World  
search methods [17] .  ...  In order to perform the calibration repeatedly for large amount of data and provide results of calibrated model simulations for the flood warning process in a short time, the method also has to be automated  ...  Acknowledgement This article was supported by Operational Programme Education for Competitiveness and co-financed by the European Social Fund within the framework of the project New creative teams in priorities  ... 
doi:10.14311/nnw.2017.27.022 fatcat:4qf4ffm3hndvzndky6efpxgicq

A Projection Pursuit Model Optimized by Free Search: For the Regional Power Quality Evaluation

Yu Yun-jun, Tong Chao, Xue Yun-tao, Peng Sui, Li Yuan-hao, Xin Jian-bo
2015 Open Cybernetics and Systemics Journal  
A Projection Pursuit Model Optimized by Free Search is proposed for power quality comprehensive evaluation high dimensional index system.  ...  conventional evaluation methods of human subjective weighting on the result of evaluation.  ...  Aiming at this problem, this paper proposes a regional power quality evaluation model based on free search and projection pursuit model optimization.  ... 
doi:10.2174/1874110x01509011422 fatcat:ss4y6ld4zvberfclw37v2yjn2q
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