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An efficient approach for interactive Sequential pattern recognition

pattern recognition 2017年 64卷 295-304页

作者： Calvo-Zaragoza, Jorge Oncina, Jose Univ Alicante Dept Lenguajes & Sistemas Informat Carretera San Vicente del Raspeig S-N Alicante 03690 Spain

interactive pattern recognition (IPR) is an emergent framework in which the user is involved actively in the recognition process by giving feedback to the system when an error is detected. Although this framework is expected to reduce the number of errors to correct, it may increase the time required to complete the task since the machine needs to recompute its proposal after each interaction. Therefore, a fast computation is required to make the interactive system profitable and user-friendly. This work presents an efficient approach to deal with IPR tasks when data has a sequential nature. Our approach includes some computation at the very beginning, of the task but it then achieves a linear complexity after user corrections. We also show how these tasks can be effectively carried out if the solution space is defined with a Regular Language. This fact has indeed proven to'e the most relevant factor to improve the efficiency of the approach. Several experiments are carried out in which our proposal is faced against a classical search. Results show a reduction in time in all experiments considered, solving efficiently some complex IPR tasks thanks to our proposals.

关键词： interactive pattern recognition Sequential pattern recognition Human-computer interaction Word graphs Efficient search

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Enhancing medical evidence discovery through interactive pattern recognition and Process Mining

Enhancing medical evidence discovery through Interactive Pat...

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Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges (GMEPE/PAHCE)

作者： Traver, V. Martinez-Romero, A. Bayo, J. L. Sala, P. Carvalho, P. Henriques, J. Ruano, M. G. Bianchi, A. Fernandez-Llatas, C. Univ Politecn Valencia SABIEN ITACA E-46022 Valencia Spain Univ Coimbra Ctr Informat & Sistemas P-3000 Coimbra Portugal Politecn Milan Dept Elect Informat & Bioengn Milan Italy

ISBN: (纸本)9781509024865

Surrounded by heterogeneous clinical data, medical staff needs to take easily the right decisions at the point of care in real time supported by medical evidence. Up to few years ago, evidence was not available at the point of care, making use of doctor's experience or heavy books. Nowadays, the challenge is to have such decision support systems available at any time, any place and any device. interactive pattern recognition is a good approach to infer knowledge based on previous existing datasets whereas process mining is the tool to handle such knowledge in a very pragmatic way, helping medical staff to visualize the whole healthcare case.

关键词： interactive pattern recognition process mining medical evidence

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Enhancing medical evidence discovery through interactive pattern recognition and Process Mining

Enhancing medical evidence discovery through Interactive Pat...

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Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges Conference

作者： V. Traver A. Martinez- Romero J.L. Bayo P. Sala P. Carvalho J. Henriques M. G. Ruano A. Bianchi C. Fernández- Llatas SABIEN-ITACA - Universitat Politècnica de Valencia Spain Centro de Informática e Sistemas da Universidade de Coimbra Portugal Dep. of Electronics Information and Bioengineering Politecnico di Milano Italy

ISBN: (纸本)9781509024872

关键词： interactive pattern recognition process mining medical evidence

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Root-Cause Analysis with interactive Decision Trees 24

Root-Cause Analysis with Interactive Decision Trees

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24th International Conference Information Visualisation (IV)

作者： Detzner, Alexander Rueckschloss, Ramona Eigner, Martin BMW Grp Munich Germany TU Kaiseralautern Kaiserslautern Germany

ISBN: (纸本)9781728191348

When manufacturing products fail, root-cause analysis is essential to improve the affected products and processes. However, finding the relevant influences among numerous possible factors can be a challenge. Computer-aided methods for anomaly detection and pattern recognition can significantly speed up this process to provide great benefits in quality management applications. We introduce a method for root-cause analysis employing interactive decision trees. Improving upon an existing concept, we developed a software prototype that utilizes a lean yet powerful representation of relationships and influences. Several interactive options allow quality data analysts to integrate their expert domain knowledge into the pattern recognition process and quickly identify anomalies among the product attributes of defective vehicles.

关键词： decision tree interactive pattern recognition root-cause analysis quality management visual analytics

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interactive Layout Detection 8th

Interactive Layout Detection

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8th Iberian Conference on pattern recognition and Image Analysis (IbPRIA)

作者： Quiros, Lorenzo Martinez-Hinarejos, Carlos-D. Toselli, Alejandro H. Vidal, Enrique Univ Politecn Valencia Pattern Recognit & Human Language Technol Res Ctr Camino Vera S-N E-46022 Valencia Spain

ISBN: (纸本)9783319588384;9783319588377

The amounts of ancient documents transcribed by means of Handwritten Text recognition (HTR) technology have been rising dramatically over the last years. Consequently, the development and enhancement of HTR methods and algorithms have become an important issue in the field, with significant contributions in performance for documents with segmented layout. However, Layout Analysis remains a bottleneck in the development and generalization of HTR technology. In this work a new interactive-Probabilistic method to obtain document layout is presented. This new method incorporates the user feedback in the Layout Analysis process, in order to provide not just a very accurate layout, but an interactive framework in which user feedback is used to help the system to fix any error.

关键词： Layout analysis Page segmentation interactive pattern recognition Conditional Random Field Handwritten Text recognition

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Improving on-line handwritten recognition in interactive machine translation

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pattern recognition 2014年第3期47卷 1217-1228页

作者： Alabau, Vicent Sanchis, Alberto Casacuberta, Francisco Univ Politecn Valencia Inst Tecnol Informat Valencia 46022 Spain

On-line handwriting text recognition (HTR) could be used as a more natural way of interaction in many interactive applications. However, current HTR technology is far from developing error-free systems and, consequently, its use in many applications is limited. Despite this, there are many scenarios, as in the correction of the errors of fully-automatic systems using HTR in a post-editing step, in which the information from the specific task allows to constrain the search and therefore to improve the HTR accuracy. For example, in machine translation (MT), the on-line HTR system can also be used to correct translation errors. The HTR can take advantage of information from the translation problem such as the source sentence that is translated, the portion of the translated sentence that has been supervised by the human, or the translation error to be amended. Empirical experimentation suggests that this is a valuable information to improve the robustness of the on-line HTR system achieving remarkable results. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： interactive pattern recognition On-line handwritten text recognition interactive machine translation Human interaction

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Multimodal interactive Parsing

Multimodal Interactive Parsing

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6th Iberian Conference on pattern recognition and Image Analysis (IbPRIA)

作者： Benedi, Jose-Miguel Sanchez, Joan-Andreu Leiva, Luis A. Sanchez-Saez, Ricardo Maca, Mauricio Univ Politecn Valencia Inst Tecnol Informat Valencia Spain Univ Cauca Dept Math Popayan Colombia

ISBN: (纸本)9783642386282

Probabilistic parsing is a fundamental problem in Computational Linguistics, whose goal is obtaining a syntactic structure associated to a sentence according to a probabilistic grammatical model. Recently, an interactive framework for probabilistic parsing has been introduced, in which the user and the system cooperate to generate error-free parse trees. In an early prototype developed according to this interactive parsing technology, user feedback was provided by means of mouse actions and keyboard strokes. Here we augment the interaction style with support for (non-deterministic) natural handwritten recognition, and provide confidence measures as a visual aid to ease the correction process. Handwriting input seems to be a modality specially suitable for parsing, since the vocabulary size involved in the recognition of syntactic labels is fairly limited and thus intuitively errors should be small. However, errors may increase as handwriting quality (i.e., calligraphy) degrades. To solve this problem, we introduce a late fusion approach that leverages both on-line and off-line information, corresponding to pen strokes and contextual information from the parse trees. We demonstrate that late fusion can effectively help to disambiguate user intention and improve system accuracy.

关键词： syntactic parsing interactive pattern recognition multimodal interaction late fusion

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On the optimal decision rule for sequential interactive structured prediction

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pattern recognition LETTERS 2012年第16期33卷 2226-2231页

作者： Alabau, Vicent Sanchis, Alberto Casacuberta, Francisco Univ Politecn Valencia Dept Sistemes Informat & Comp Inst Tecnol Informat Valencia 46022 Spain

interactive structured prediction (ISP) is an emerging framework for structured prediction (SP) where the user and the system collaborate to produce a high quality output. Typically, search algorithms applied to ISP problems have been based on the algorithms for fully-automatic SP systems. However, the decision rule applied should not be considered as optimal since the goal in ISP is to reduce human effort instead of output errors. In this work, we present some insight into the theory of the sequential ISP search problem. First, it is formulated as a decision theory problem from which a general analytical formulation of the optimal decision rule is derived. Then, it is compared with the standard formulation to establish under what conditions the standard algorithm should perform similarly to the optimal decision rule. Finally, a general and practical implementation is given and evaluated against three classical ISP problems: interactive machine translation, interactive handwritten text recognition, and interactive speech recognition. (c) 2012 Elsevier B.V. All rights reserved.

关键词： interactive pattern recognition Minimum Bayes risk Human interaction Machine translation Handwritten text recognition Automatic speech recognition

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interactive Structured Output Prediction: Application to Chromosome Classification

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5th Iberian Conference on pattern recognition and Image Analysis (IbPRIA)

作者： Oncina, Jose Vidal, Enrique Univ Alicante Dept Lenguajes & Sistemas Informat Alicante Spain Univ Politecn Valencia Inst Informat Technol Valencia Spain

ISBN: (纸本)9783642212567;9783642212574

interactive pattern recognition concepts and techniques are applied to problems with structured output;i.e., problems in which the result is not just a simple class label, but a suitable structure of labels. For illustration purposes (a simplification of) the problem of Human Karyotyping is considered. Results show that a) taking into account label dependencies in a karyogram significantly reduces the classical (non-interactive) chromosome label prediction error rate and b) they are further improved when interactive processing is adopted.

关键词： interactive pattern recognition machine learning structured output prediction chromosome classification karyotype recognition

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Active learning for interactive multimedia retrieval

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PROCEEDINGS OF THE IEEE 2008年第4期96卷 648-667页

作者： Huang, Thomas S. Dagli, Charlie K. Rajaram, Shyamsundar Chang, Edward Y. Mandel, Michael I. Poliner, Graham E. Ellis, Daniel P. W. Univ Illinois Beckman Inst Adv Sci & Technol Urbana IL 61801 USA Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA Columbia Univ Dept Elect & Comp Engn New York NY 10027 USA

AS the first decade of the 21st century comes to a close, growth in multimedia delivery infrastructure and public demand for applications built on this backbone are converging like never before. The push towards reaching truly interactive multimedia technologies becomes stronger as our media consumption paradigms continue to change. in this paper, we will profile a technology leading the way in this revolution: active learning. Active learning is a strategy that helps alleviate challenges inherent in multimedia information retrieval through user interaction. We will show how active learning is ideally suited for the multimedia information retrieval problem by giving an overview of the paradigm and component technologies used with special attention given to the application scenarios in which these technologies are useful. Finally, we give insight into the future of this growing field and how it fits into the larger context of multimedia information retrieval.

关键词： active learning content-based information retrieval human-computer interaction image/video search interactive pattern recognition relevance feedback user-centered design

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