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A Self-adaptive Classifier for Efficient Text-stream Processing

Naoki Yoshinaga, Masaru Kitsuregawa
2014 International Conference on Computational Linguistics  
A self-adaptive classifier for efficient text-stream processing is proposed.  ...  The proposed classifier adaptively speeds up its classification while processing a given text stream for various NLP tasks.  ...  Conclusion Aiming to efficiently process a real-world text stream (such as a Twitter stream) in real-time, a selfadaptive classifier that becomes faster for a given text stream is proposed.  ... 
dblp:conf/coling/0001K14 fatcat:22ftxbjpfncabc66dvieqrnk4u

Opinion Stream Mining [chapter]

Myra Spiliopoulou, Eirini Ntoutsi, Max Zimmermann
2016 Encyclopedia of Machine Learning and Data Mining  
Opinion stream mining aims at learning and adaptation of a polarity model over a stream of opinionated documents, i.e., documents associated with a polarity.  ...  In this chapter, we overview methods for polarity learning in a stream environment focusing especially on how these methods deal with the challenges imposed by the stream nature of the data, namely the  ...  ., in "instancebased" processing, the classifier is adapted after seeing each new instance. In "chunkbased" processing, the classifier adapts after each chunk.  ... 
doi:10.1007/978-1-4899-7502-7_905-1 fatcat:d2fgtvgjzbhz7pkmt44amrfpmy

Guest Editorial Evolving Fuzzy Systems–-Preface to the Special Section

Plamen Angelov, Dimitar Filev, Nikola Kasabov
2008 IEEE transactions on fuzzy systems  
EFS are addressing nonstationary processes by computationally efficient algorithms for real-time applications.  ...  The paper "Evolving Fuzzy-Rule-Based Classifiers from Data Streams" by Plamen Angelov and Xiaowei Zhou, introduces a new approach to classification of streaming data by the use of EFSs.  ... 
doi:10.1109/tfuzz.2008.2006743 fatcat:573uxoc72zhojjgog5jx4eaoam

Anomaly Network Intrusion Detection Based on Improved Self Adaptive Bayesian Algorithm

Dewan Md. Farid, Mohammad Zahidur Rahman
2010 Journal of Computers  
Furthermore, a successful intrusion serves as a motivation factor for aspiring black-hat hackers to launch their own intrusion campaigns.  ...  To process the huge network traffic data we require powerful machines that are often too expensive.  ...  Our streaming classifier can classify an average of 434 packets per minute. The detection rate of our streaming job is 90%.  ... 
doi:10.4304/jcp.5.1.23-31 fatcat:tiz3fj5gmnguhfotfpiwg3nefa

Self-Learning Camera: Autonomous Adaptation of Object Detectors to Unlabeled Video Streams [article]

Adrien Gaidon, Gloria Zen, Jose A. Rodriguez-Serrano (Xerox Research Center Europe, France)
2014 arXiv   pre-print
(i) detectors continuously updating themselves to efficiently adapt to streaming data sources (contrary to transductive algorithms), (ii) without any labeled data strongly related to the target data stream  ...  To that end, we propose an unsupervised, on-line, and self-tuning learning algorithm to optimize a multi-task learning convex objective.  ...  These approaches can only be applied in stationary transductive settings, and do not allow for efficient model adaptation along a particular video stream.  ... 
arXiv:1406.4296v2 fatcat:6u37mzyfxbbf5ibviam3mrysbe

Text Classification Techniques: A Literature Review

2018 Interdisciplinary Journal of Information, Knowledge, and Management  
The role of streaming data processing is still rarely explored when it comes to text classification.  ...  It supports state-of-the-art decision making, for example, predicting an event before it actually occurs, classifying a transaction as 'Fraudulent' etc.  ...  Self-training along with semisupervised classifier is recommended for multi-label hierarchical classification. It has also proven a better way to achieve automatic label attribution.  ... 
doi:10.28945/4066 fatcat:6dio5bpajjf77lkrs7xdtciveu

Self‐adaptation on parallel stream processing: A systematic review

Adriano Vogel, Dalvan Griebler, Marco Danelutto, Luiz Gustavo Fernandes
2021 Concurrency and Computation  
In this work, we aim at providing a literature review regarding self-adaptation applied to the parallel stream processing domain.  ...  We present a comprehensive revision using a systematic literature review method. Moreover, we propose a taxonomy to categorize and classify the existing self-adaptive approaches.  ...  for self-adaptive executions in parallel stream processing. • A unified taxonomy for categorization and validation of self-adaptation in parallel stream processing. • A catalog defining self-adaptation  ... 
doi:10.1002/cpe.6759 fatcat:4qa2hlnhijbjbhmf73de5qa2re

Survey: Transformer based Video-Language Pre-training [article]

Ludan Ruan, Qin Jin
2021 arXiv   pre-print
This survey aims to give a comprehensive overview on transformer-based pre-training methods for Video-Language learning.  ...  Next, we categorize transformer models into Single-Stream and Multi-Stream structures, highlight their innovations and compare their performances.  ...  For fill-in-the-blank VideoQA, ActBERT (Zhu and Yang 2020) proposes a similar method, which adds a linear classifier upon the cross-modal feature but without the input of candidate text.  ... 
arXiv:2109.09920v1 fatcat:ixysz5k4vrbktmf6cqftttls7m

Image-text Retrieval: A Survey on Recent Research and Development [article]

Min Cao, Shiping Li, Juntao Li, Liqiang Nie, Min Zhang
2022 arXiv   pre-print
On top of this, the efficiency-focused study on the ITR system is introduced as the third perspective.  ...  This paper presents a comprehensive and up-to-date survey on the ITR approaches from four perspectives.  ...  Self-adaptive (SA).  ... 
arXiv:2203.14713v2 fatcat:acvezdy23nfobhy5vh7m4hdghq

A Big Data Platform for Real Time Analysis of Signs of Depression in Social Media

Rodrigo Martínez-Castaño, Juan C. Pichel, David E. Losada
2020 International Journal of Environmental Research and Public Health  
In this paper we propose a scalable platform for real-time processing of Social Media data.  ...  The design is modular and supports different processing elements, such as crawlers to extract relevant contents or classifiers to categorise Social Media.  ...  This stream-based approach is highly efficient and more convenient than a batch processing approach for generating alerts as soon as possible.  ... 
doi:10.3390/ijerph17134752 pmid:32630341 fatcat:rf64qw2jpjdcpbzeivfgehdclq

Enhanced template update: Application to keystroke dynamics

Paulo Henrique Pisani, Romain Giot, André C.P.L.F. de Carvalho, Ana Carolina Lorena
2016 Computers & security  
This new approach, named Enhanced Template Update, uses all collected unlabeled samples to support the adaptation process.  ...  Most of the studies in the literature only take into account samples classified as genuine to perform adaptation.  ...  Acknowledgment The authors would like to thank LaBRI/Université de Bordeaux for the financial support to the Enhanced Template Update project.  ... 
doi:10.1016/j.cose.2016.04.004 fatcat:s3mzymczfjejpgyhmkhd5cr7mq

Recognition and Classification of Figures in PDF Documents [chapter]

Mingyan Shao, Robert P. Futrelle
2006 Lecture Notes in Computer Science  
An interpreter was constructed to translate PDF content into a set of self-contained graphics and text objects (in Java), freed from the intricacies of the PDF file.  ...  ., a pair of primitive graphic objects satisfying certain geometric constraints. The third stage uses machine learning to classify figures using grapheme statistics as attributes.  ...  The process required building an interpreter that led to a sequence of self-contained Java 2D graphic objects mirroring the PDF content stream. Stage 2.  ... 
doi:10.1007/11767978_21 fatcat:lnvepqldhjfsdazy7ltoil55iy

Data stream mining techniques: a review

Eiman Alothali, Hany Alashwal, Saad Harous
2019 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
In this paper, we review real time clustering and classification mining techniques for data stream.  ...  We analyze the characteristics of data stream mining and discuss the challenges and research issues of data steam mining. Finally, we present some of the platforms for data stream mining.  ...  The online component stores the summary statistics of stream using very efficient process for storage.  ... 
doi:10.12928/telkomnika.v17i2.11752 fatcat:rls2qzcl3vhobmkpycsdwhzplu

Survey and Analysis of Recent Sentiment Analysis Schemes Relating to Social Media

Osamah Ali Mohammed Ghaleb, Anna Saro Vijendran
2016 Indian Journal of Science and Technology  
Thus this paper work provides a detailed analysis of the recent sentiment analysis schemes and throws light on new avenues for future research work in this domain.  ...  Methods/ Statistical Analysis: Extraction of the information from the web, classification and prediction of the sentiment polarity is a complex process which performed through various approaches like Part-Of-Speech  ...  Such a similarity matrix can classify unlabeled tweet sets. A well-known Self-training algorithm was introduced for a better tweet sentiment classifier.  ... 
doi:10.17485/ijst/2016/v9i41/97767 fatcat:447w5xhaunaavfxgbitggsjhqi

Self-adaptive battery and context aware mobile application development

Soumya Kanti Datta, Christian Bonnet, Navid Nikaein
2014 2014 International Wireless Communications and Mobile Computing Conference (IWCMC)  
This paper introduces a self-adaptive application development framework which proposes three profiles with various selfadaptive features for mobile applications.  ...  The self-adaption takes place in four levelshardware & software features adaption, user features adaption and additional optimization.  ...  This paper proposes a self-adaptive framework to facilitate the development of power efficient mobile applications.  ... 
doi:10.1109/iwcmc.2014.6906452 dblp:conf/iwcmc/DattaBN14 fatcat:gedr4c6zpfgvbag3zypjlyz5z4
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