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Meta methods for model sharing in personal information systems

Stefan Siersdorfer, Sergej Sizov
2008 ACM Transactions on Information Systems  
This article introduces a methodology for automatically organizing document collections into thematic categories for Personal Information Management (PIM) through collaborative sharing of machine learning  ...  We introduce a formal probabilistic model for the resulting ensemble based meta methods and explain how it can be used for constructing estimators and for goal-oriented tuning.  ...  Acknowledgements This work has been partially supported by the European project WeKnowIt ("Emerging, Collective Intelligence for Personal, Organizational and Social Use", FP7-215453) and the EU-funded  ... 
doi:10.1145/1402256.1402261 fatcat:zljpegbfk5hg5cjfnu7u3xm5e4

A user meta-model for context-aware recommender systems

Jon Imanol Durán, Juhani Laitakari, Daniel Pakkala, Juho Perälä
2010 Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems - HetRec '10  
This new user profile meta-model has been designed with a view of using it in conjunction with content and service recommender systems.  ...  User profiles are increasingly used for sharing standard information about users among context-aware agents. User profiles allow agents to offer users personalized content and services.  ...  We validate the usefulness of the user meta-model as an input model for recommendation systems within a case study that also makes use of the CAM Meta-model.  ... 
doi:10.1145/1869446.1869456 fatcat:dxxbq3tky5gk5erkol43b74dru

Meta Matrix Factorization for Federated Rating Predictions

Yujie Lin, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Dongxiao Yu, Jun Ma, Maarten de Rijke, Xiuzhen Cheng
2020 Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval  
CCS CONCEPTS • Information systems → Recommender systems.  ...  Our goal in this paper is to design a novel federated learning framework for rating prediction (RP) for mobile environments that operates on par with state-of-the-art fully centralized RP methods.  ...  ACKNOWLEDGMENTS We thank our anonymous reviewers for their helpful comments.  ... 
doi:10.1145/3397271.3401081 dblp:conf/sigir/LinRCRY0RC20 fatcat:y2udty4x4fgffagg67lb46ro3q

Meta Matrix Factorization for Federated Rating Predictions [article]

Yujie Lin, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Dongxiao Yu, Jun Ma, Maarten de Rijke, Xiuzhen Cheng
2021 arXiv   pre-print
Then, we employ a meta recommender module to generate private item embeddings and a RP model based on the collaborative vector in the server.  ...  Our goal in this paper is to design a novel federated learning framework for rating prediction (RP) for mobile environments.  ...  ACKNOWLEDGMENTS We thank our anonymous reviewers for their helpful comments.  ... 
arXiv:1910.10086v3 fatcat:57reiggicvbm3e57psvs3lupg4

Information Organizing and Sharing Technique for Task Performance and Training Support [chapter]

Hiroyuki Kojima, Takaaki Yamada, Yoshihiro Mizuno, Toshiyuki Yuasa
1999 IFIP Advances in Information and Communication Technology  
For the distributed task itiformation available on the internet or on intranet in the product design field, we propose information organizing and sharing method as a means of getting timely and exact knowledge  ...  for a task peiformance.  ...  For distributed design task information, we proposed a method for design task performance support using the information organizing and sharing system.  ... 
doi:10.1007/978-0-387-35393-7_18 fatcat:w2x35gioundahi5tk42ncckcqy

Federating Neuroscience Databases [chapter]

Wen-Hsiang Kevin Liao, Dennis McLeod
2001 Computing the Brain  
Other component databases that are interested in using the information can import the information using one of the sharing methods provided by that component database.  ...  In this paradigm, a component database of a federation decides the portion of its database to be exported and offers the methods to others on how the information can be shared.  ...  Sharing Contracts Available Data Recommended Sharing Methods Exporter -Knows best the characteristics of data and system -Recommends sharing methods that are most suitable for importers and can be  ... 
doi:10.1016/b978-012059781-9/50016-x fatcat:74jhgnez4jedvn342zrjqmdome

Improving Web Search Using Contextual Retrieval

Dilip K. Limbu, Andrew M. Connor, Russel Pears, Stephen G. MacDonell
2009 2009 Sixth International Conference on Information Technology: New Generations  
Contextual retrieval is a critical technique for today's search engines in terms of facilitating queries and returning relevant information.  ...  In this paper, results related to one are presented that support the claim that users can find information more readily using the contextual search system.  ...  User profile modeling. Several Web IR systems have explored various user modeling approaches to improve the personalization of a users' Web search experience.  ... 
doi:10.1109/itng.2009.133 dblp:conf/itng/LimbuCPM09 fatcat:gaumdzclp5b7topwknbmzxphga

Deep Meta-learning in Recommendation Systems: A Survey [article]

Chunyang Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Jiadi Yu, Feilong Tang
2022 arXiv   pre-print
Deep neural network based recommendation systems have achieved great success as information filtering techniques in recent years.  ...  for meta-learning based recommendation methods.  ...  META-LEANRING METHODS FOR RECOMMENDATION SYSTEMS In this section, we look in more detail at meta-learning based recommendation methods in the literature.  ... 
arXiv:2206.04415v1 fatcat:w5rax6bjy5efjfmxunvf4j6kly

Learning to Recommend via Meta Parameter Partition [article]

Liang Zhao, Yang Wang, Daxiang Dong, Hao Tian
2019 arXiv   pre-print
In this paper we propose to solve an important problem in recommendation -- user cold start, based on meta leaning method.  ...  In contrast, we divide model parameters into fixed and adaptive parts and develop a two-stage meta learning algorithm to learn them separately.  ...  In contrast, personalized recommendation system has a model for each user, which is trained with each user's own data.  ... 
arXiv:1912.04108v1 fatcat:msk7xhsmbrebliak6vp3lwrzyy

Applying the Business Process and Practice Alignment Meta-model: Daily Practices and Process Modelling

Paula Ventura Martins, Marielba Zacarias
2017 Business Systems Research  
This lack of information implies that further research in BP meta-models is needed to reflect the evolution/change in BP.  ...  Background: Business Process Modelling (BPM) is one of the most important phases of information system design.  ...  Interactions among actors are both supported and constrained by information systems and tools, shared vocabularies and meanings, interaction patterns and rules.  ... 
doi:10.1515/bsrj-2017-0001 fatcat:sl3jjmuiyvcl3iu2wnawxvf2yi

Meta-ontology for automated information integration of parts libraries

Joonmyun Cho, Soonhung Han, Hyun Kim
2006 Computer-Aided Design  
Modeling ontologies of real mold and die parts libraries is taken as an example task to show how to use the meta-concepts.  ...  In this paper, we propose meta-concepts with which the ontology developers describe the domain concepts of parts libraries.  ...  We applied the method for knowledge systematization to modeling the ontologies of real mold and die parts libraries, and demonstrated the usefulness of the method in automated integration of parts libraries  ... 
doi:10.1016/j.cad.2006.03.002 fatcat:hanfufprhzenni2wwrfp7giksu

MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation [article]

Manqing Dong and Feng Yuan and Lina Yao and Xiwei Xu and Liming Zhu
2020 arXiv   pre-print
However, most meta-learning based recommendation approaches adopt model-agnostic meta-learning for parameter initialization, where the global sharing parameter may lead the model into local optima for  ...  And we adopt a meta-optimization approach for optimizing the proposed method. We test the model on two widely used recommendation datasets and consider four cold-start situations.  ...  Most of the current meta-learning based recommender systems [5, 15, 34] adopt optimization-based algorithms such as model-agnostic meta-learning (MAML) [11] , for their promising performance in learning  ... 
arXiv:2007.03183v1 fatcat:cg7gn5an6rcsvfjel3arno2mim


2007 International Journal of Information Technology and Decision Making  
Meta-synthesis system approach (MSA) is oriented to complexities in those problems.  ...  to expose problem structure by collaborative activities for qualitative meta-synthesis.  ...  shares similar meaning as ba in the SECI model.  ... 
doi:10.1142/s0219622007002630 fatcat:nzfpajjipzehlafjzogle4pkta

Improving Patient Outcomes Through Untethered Patient-Centered Health Records

Mohammed Abdulkareem Alyami, Majed Almotairi, Alberto R. Yataco, Yeong-Tae Song
2018 Advances in Science, Technology and Engineering Systems  
to such scenarios, we propose an untethered patient health record system that manages personal health data by utilizing meta-data that enables easy retrieval of clinical data.  ...  Well-managed personal cloud space could outlive the lifetime of personal health records system (PHRS) since the discontinuity of the service does not affect the data stored in the cloud space.  ...  Our proposed system, MCRS, provides a method to collect and organize heterogeneous personal health data using DC meta-data.  ... 
doi:10.25046/aj030219 fatcat:e44y6wt7ovdsnpwwzn5lg4eewq

Scientific and Technological Resource Sharing Model Based on Few-Shot Relational Learning

Yangshengyan LIU, Fu GU, Yangjian JI, Yijie WU, Jianfeng GUO, Xinjian GU, Jin ZHANG
2021 IEICE transactions on information and systems  
Resource sharing is to ensure required resources available for their demanders.  ...  Here we propose a novel method to share scientific and technological resources by storing resources as nodes and correlations as links to form a complex network.  ...  Contrarily tacit resource sharing [35] , such as informal networks among human resources, has its relevant factor that is hard to identify and requires the model for employees to foster informal networks  ... 
doi:10.1587/transinf.2020bdp0021 fatcat:caoeiwdfmjawfb6din5zurhao4
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