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A Self-adaptive Classifier for Efficient Text-stream Processing
2014
International Conference on Computational Linguistics
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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]
2016
Encyclopedia of Machine Learning and Data Mining
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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
2008
IEEE transactions on fuzzy systems
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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
2010
Journal of Computers
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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]
2014
arXiv
pre-print
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(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
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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
2021
Concurrency and Computation
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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]
2021
arXiv
pre-print
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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]
2022
arXiv
pre-print
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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
2020
International Journal of Environmental Research and Public Health
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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
2016
Computers & security
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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]
2006
Lecture Notes in Computer Science
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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
2019
TELKOMNIKA (Telecommunication Computing Electronics and Control)
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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
2016
Indian Journal of Science and Technology
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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
2014
2014 International Wireless Communications and Mobile Computing Conference (IWCMC)
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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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