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45th IEEE Conference on Decision and Control 2006, CDC

作者： Pang, Chee Khiang Lewis, Frank L. Ge, Sam Shuzhi Guo, Xiao Chen, Ben M. Lee, Tong Heng IEEE Central Research Laboratory Research and Development Group Hitachi Ltd. 2880 Kozu Odawara Kanagawa 256-8510 Japan A STAR Data Storage Institute Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Advanced Controls and Sensors Group Automation and Robotics Research Institute University of Texas Arlington United States

ISBN: (纸本)1424401712

In this paper, the SPT (Singular Perturbation Theory) is applied to decompose the VCM's (Voice Coil Motor) and induced PZT active suspension's dynamics into fast and slow subsystems, respectively. The control system is decomposed into fast and slow time scale for controller designs, and control effectiveness is increased to tackle more DOFs (Degrees-Of-Freedom) via inner loop vibration suppression with measured high frequency VCM's and PZT active suspension's dynamics from the piezoelectric elements in the suspension. Experimental results on a commercial HDD with LDV (Laser Doppler Vibrometer) show effective suppression of the VCM and PZT active suspension's flexible resonant modes as well as an improvement of 39.9% in 3σ PES (Position Error Signal) during track following when compared to conventional notch-based servos. © 2006 IEEE.

关键词： Hard disk storage

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SocialWeb Communities Executive Summary of the Dagstuhl Seminar

SocialWeb Communities Executive Summary of the Dagstuhl Semi...

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Social Web Communities 2008

作者： Alani, Harith Staab, Steffen Stumme, Gerd Address Harith Research Group ISWeb - Information Systems and Semantic Web University of Koblenz-Landau Univ.str. 1 Koblenz56016 Germany Knowledge & Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 Kassel34121 Germany

Blogs, Wikis, and Social Bookmark Tools have rapidly emerged on the Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing so without requiring any specific skills. At the moment, there exists no foundational research for these systems, and they provide only very simple structures for organising knowledge. Individual users create their own structures, but these can currently not be exploited for knowledge sharing. The objective of the seminar was to provide theoretical foundations for upcoming Web 2.0 applications and to investigate further applications that go beyond bookmark- and file-sharing. The main research question can be summarized as follows: How will current and emerging resource sharing systems support users to leverage more knowledge and power from the information they share on Web 2.0 applications? research areas like Semantic Web, Machine Learning, Information Retrieval, Information Extraction, Social Network Analysis, Natural Language Processing, Library and Information Sciences, and Hypermedia Systems have been working for a while on these questions. In the workshop, researchers from these areas came together to assess the state of the art and to set up a road map describing the next steps towards the next generation of social software. © 2008 Dagstuhl Seminar Proceedings. All rights reserved.

关键词： Natural language processing systems

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Analysis of Social Media and Ubiquitous data 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Martin Atzmueller Andreas Hotho Markus Strohmaier Alvin Chin

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A comparison of content-based tag recommendations in folksonomy systems

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Lecture Notes in computer Science

作者： Illig, Jens Hotho, Andreas Jäschke, Robert Stumme, Gerd Knowledge and Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 34121 Kassel Germany Research Center L3S Appelstraße 9a 30167 Hannover Germany

ISBN: (纸本)9783642221392

Recommendation algorithms and multi-class classifiers can support users of social bookmarking systems in assigning tags to their bookmarks. Content based recommenders are the usual approach for facing the cold start problem, i.e., when a bookmark is uploaded for the first time and no information from other users can be exploited. In this paper, we evaluate several recommendation algorithms in a cold-start scenario on a large real-world dataset. © 2011 Springer-Verlag.

关键词： computers

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Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach

arXiv

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arXiv 2021年

作者： Alomrani, Mohammad Ali Moravej, Reza Khalil, Elias B. Department of Electrical & Computer Engineering University of Toronto Canada Department of Mechanical & Industrial Engineering SCALE AI Research in Data-Driven Algorithms for Modern Supply Chains University of Toronto Canada

The challenge in the widely applicable online matching problem lies in making irrevocable assignments while there is uncertainty about future inputs. Most theoretically-grounded policies are myopic or greedy in nature. In real-world applications where the matching process is repeated on a regular basis, the underlying data distribution can be leveraged for better decision-making. We present an end-to-end Reinforcement Learning framework for deriving better matching policies based on trial-and-error on historical data. We devise a set of neural network architectures, design feature representations, and empirically evaluate them across two online matching problems: Edge-Weighted Online Bipartite Matching and Online Submodular Bipartite Matching. We show that most of the learning approaches perform consistently better than classical baseline algorithms on four synthetic and real-world datasets. On average, our proposed models improve the matching quality by 3-10% on a variety of synthetic and real-world datasets. Our code is publicly available at https://***/lyeskhalil/CORL. © 2021, CC BY.

关键词： Reinforcement learning

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Semi-automatic staging area for high-quality structured data extraction from scientific literature

arXiv

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arXiv 2023年

作者： Foppiano, Luca Mato, Tomoya Terashima, Kensei Suarez, Pedro Ortiz Tou, Taku Sakai, Chikako Wang, Wei-Sheng Amagasa, Toshiyuki Takano, Yoshihiko Ishii, Masashi Materials Modelling Group Data-driven Materials Research Field Centre for Basic Research on Materials NIMS Japan Knowledge and Data Engineering Centre for Computational Sciences University of Tsukuba Japan Frontier Superconducting Materials Group MANA NIMS Tsukuba Japan DFKI GmbH Germany

We propose a semi-automatic staging area for efficiently building an accurate database of experimental physical properties of superconductors from literature, called SuperCon2, to enrich the existing manually-built superconductor database SuperCon. Here we report our curation interface (SuperCon2 Interface) and a workflow managing the state transitions of each examined record, to validate the dataset of superconductors from PDF documents collected using Grobid-superconductors in a previous work [1]. This curation workflow allows both automatic and manual operations, the former contains "anomaly detection" that scans new data identifying outliers, and a "training data collector" mechanism that collects training data examples based on manual corrections. Such training data collection policy is effective in improving the machine-learning models with a reduced number of examples. For manual operations, the interface (SuperCon2 interface) is developed to increase efficiency during manual correction by providing a smart interface and an enhanced PDF document viewer. We show that our interface significantly improves the curation quality by boosting precision and recall as compared with the traditional "manual correction". Our semi-automatic approach would provide a solution for achieving a reliable database with text-data mining of scientific documents. © 2023, CC BY.

关键词： database systems

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Emergent semantics in BibSonomy

Emergent semantics in BibSonomy

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36th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Informatik fur Menschen, INFORMATIK 2006

作者： Hotho, Andreas Jäschke, Robert Schmitz, Christoph Stumme, Gerd Knowledge and Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 D-34121 Kassel Germany Research Center L3S Expo Plaza 1 D-30539 Hannover Germany

ISBN: (纸本)9783885791881

关键词： Semantics

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Information retrieval in folksonomies: Search and ranking

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3rd European Semantic Web Conference, ESWC 2006

作者： Hotho, Andreas Jäschke, Robert Schmilz, Christoph Stumme, Gerd Knowledge and Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 D-34121 Kassel Germany Research Center L3S Expo Plaza 1 D-30539 Hannover Germany

ISBN: (纸本)3540345442

Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Information retrieval systems

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Web service recommendation based on event ontology 4

Web service recommendation based on event ontology

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2021 4th International Symposium on Big data and Applied Statistics, ISBDAS 2021

作者： Lv, Hang Pan, Junjun Wu, Jinliang Ren, Haiyang College of Computer Engineering and Science Shanghai University Shanghai200444 China Pudong New Area Big Data Center Shanghai200135 China The 54th Research Institute of China Electronics Technology Group Corporation Beijing100036 China

Web service recommendation is an important means to help users quickly discover and select services. Service recommendation combined with situational information is one of the development trends of Web services in the future. This paper proposes a Web service recommendation method based on event ontology, which abstracts Web service requirements into service event classes, according to the historical service records of the target users, Web service recommendations combined with service event ontology and content similarity calculation are recommended, and event class elements and hierarchical models in service event ontology are used as reference, calculate the service similarity and generate the fusion recommendation result according to the weight;Then, based on the current situation status of the user, the user's current situation is located to a node on the event ontology situation model, the predictive recommendation of services is based on the semantic relationship between event classes in the event scenario model. Finally, the service with the highest similarity among the two parts of service recommendation is recommended to users. The experimental results show that this method can better improve the accuracy and diversity of service recommendation. © Published under licence by IOP Publishing Ltd.

关键词： Web services

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Prediction of Wastewater Pre-Precipitation Variables Using Self-Organizing Networks

Prediction of Wastewater Pre-Precipitation Variables Using S...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： P. Isaias S. Nilsson A. Stathaki R.E. King Data and Knowledge Engineering Group Computer Research Institute Athens Athens Greece Environmental Research Institute IVL Stockholm Sweden Electrical Engineering and Computer Science University of Patras Greece

This paper describes the derivation and design of an array of self-organizing networks trained by inductive learning for one step ahead prediction of the outputs of the pre-precipitation stage of a wastewater treatmen... 详细信息

关键词： Self-organizing networks Wastewater treatment Mathematical model Neural networks Effluents Predictive models Predictive control Machine learning Chemicals Instruments

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