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The Nature of Novelty Detection [article]

Le Zhao, Min Zhang, Shaoping Ma
2005 arXiv   pre-print
Aiming at a better accuracy for detecting redundancy, this paper reveals the nature of the novelty detection task currently overlooked by the Novelty community - Novelty as a combination of the partial  ...  We propose new evaluation measures for Novelty according to the nature of the task, as well as possible directions for future study.  ...  Section 3 is the heart of the paper, in which the nature of the novelty detection task is provided as a combination of the PO-CO relations.  ... 
arXiv:cs/0510054v1 fatcat:mpisloeygjfyjeddjrf6xoljb4

The nature of novelty detection

Le Zhao, Min Zhang, Shaoping Ma
2006 Information retrieval (Boston)  
In the task, sentences appearing later in the list with no new meanings are eliminated. For the task of novelty detection, the contributions of this paper are three-fold.  ...  First, conceptually, this paper reveals the computational nature of the task currently overlooked by the Novelty community − Novelty as a combination of partial overlap (PO) and complete overlap (CO) relations  ...  Nevertheless, novelty detection remains a difficult task which is demanded by the complexities and arbitrariness of natural language.  ... 
doi:10.1007/s10791-006-9000-x fatcat:zl6jjx2n3jd3tg2gkptd2ilgkq

Semantic Novelty Detection in Natural Language Descriptions

Nianzu Ma, Alexander Politowicz, Sahisnu Mazumder, Jiahua Chen, Bing Liu, Eric Robertson, Scott Grigsby
2021 Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing   unpublished
Given a set of natural language descriptions of normal scenes, we want to identify descriptions of novel scenes. We are not aware of any existing work that solves the problem.  ...  This paper proposes to study a fine-grained semantic novelty detection task, which can be illustrated with the following example.  ...  The problem of semantic novelty detection is defined as follows.  ... 
doi:10.18653/v1/2021.emnlp-main.66 fatcat:s6khxdp2ubd2rblp4bzpnqgb5q

Novelty detection

Ian Soboroff, Donna Harman
2005 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05   unpublished
In the TREC novelty track, the task was to highlight sentences containing relevant and new information in a short, topical document stream.  ...  A challenge for search systems is to detect not only when an item is relevant to the user's information need, but also when it contains something new which the user has not seen before.  ...  Introduction The problem of novelty detection has long been a significant one for retrieval systems.  ... 
doi:10.3115/1220575.1220589 fatcat:nyu2eznk5jghbfwpyd4uhpbjqq

Context and learning in novelty detection

Barry Schiffman, Kathleen R. McKeown
2005 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05   unpublished
We demonstrate the value of using context in a new-information detection system that achieved the highest precision scores at the Text Retrieval Conference's Novelty Track in 2004.  ...  In order to determine whether information within a sentence has been seen in material read previously, our system integrates information about the context of the sentence with novel words and named entities  ...  Novelty Track Much of the work in new-information detection has been done for the TREC Novelty Track.  ... 
doi:10.3115/1220575.1220665 fatcat:h6x4snvpa5blvkh5xore77c5cm

Graph-based text representation for novelty detection

Michael Gamon
2006 Proceedings of TextGraphs: the First Workshop on Graph Based Methods for Natural Language Processing on the First Workshop on Graph Based Methods for Natural Language Processing - TextGraphs '06   unpublished
We discuss several feature sets for novelty detection at the sentence level, using the data and procedure established in task 2 of the TREC 2004 novelty track.  ...  These feature sets allow us to increase the accuracy of an initial novelty classifier which is based on a bagof-word representation and KL divergence.  ...  Novelty detection as classification For the purpose of this paper we view novelty detection as a supervised classification task.  ... 
doi:10.3115/1654758.1654762 fatcat:6emwxmqs6bdttmygn6rv2rhfie

Exploring the Implications of Artificial Intelligence in Various Aspects of Scholarly Peer Review

Tirthankar Ghosal
2019 Bulletin of IEEE Technical Committee on Digital Libraries  
We identify three potential factors: Novelty, Scope and Quality which are central to the theme of scholarly communication process and seek to investigate various techniques encompassing Natural Language  ...  We are sure that there more issues to address, many scope of improvements which would eventually lead us one step closer to this ambitious vision: to cut through the clutter of bad literature and accelerate  ...  ACKNOWLEDGMENTS The author is supported by Visvesvaraya PhD fellowship, Ministry of Electronics and Information Technology (MeitY), Government of India (GoI).  ... 
dblp:journals/tcdl/Ghosal19 fatcat:6we7jpytqndtlcjbc5ky5my5kq

Applying Convolutional Neural Networks to Detect Natural Gas Leaks in Wellhead Images

Roberlanio De Oliveira Melo, Marly G. F. Costa, Cicero F. F. Costa Filho
2020 IEEE Access  
These previous studies used image-processing techniques associated with a novelty filter classifier to detect the presence or absence of visible cloud of hydrocarbon vapors, that is, a natural gas plume  ...  Detecting natural gas leaks is one of the most important measures in the oil industry for preventing accidents. The literature provides different techniques for detecting natural gas leaks.  ...  Therefore, to mitigate the effects of natural gas leaks on the greenhouse effect, it is mandatory to develop efficient prevention systems, such as natural gas leak detection systems.  ... 
doi:10.1109/access.2020.3031683 fatcat:bymx3hvq45cbheholk5ygq7hhu

Page 270 of Neural Computation Vol. 6, Issue 2 [page]

1994 Neural Computation  
We have developed a robust method for novelty detection, which aims to mini- mize the number of heuristically chosen thresholds in the novelty de- cision process.  ...  We show on a sample problem of medical signal processing that this method is capable of providing robust novelty de- cision boundaries and apply the technique to the detection of epileptic seizures within  ... 

Novelty Detection in Images Using Vector Quantization with Topological Learning

Yann Bernard, Nicolas Hueber, Bernard Girau
2020 2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)  
Combination of VQ and Topology Novelty detection The two above methods have different and complementary properties in their novelty detection.  ...  The challenges with this application are the high dimensionality of the data (images), the naturally high variability in the background and the requirement to precisely locate the novelty in the images  ... 
doi:10.1109/icecs49266.2020.9294957 fatcat:ugmjgxovgjf33emh5ivobuoquy

Hippocampal theta frequency and novelty

Anke Sambeth, Martijn Meeter, Arjan Blokland
2009 Hippocampus  
However, the exact nature and processes underlying hippocampal novelty detection remain elusive. One important mechanism that may underlie hippocampal novelty detection is hippocampal theta activity.  ...  Various studies indicate that the hippocampus plays an essential role in novelty detection.  ...  However, the exact nature and processes underlying hippocampal novelty detection remain elusive. One important mechanism that may underlie hippocampal novelty detection is hippocampal theta activity.  ... 
doi:10.1002/hipo.20541 pmid:19212942 fatcat:qhvv4c3hprbjfihuf3cy6snfvq

Oscillatory model of novelty detection

R. Borisyuk, M. denham, F. Hoppensteadt, Y. Kazanovich, O. Vinogradova
2001 Network  
The resonance amplification of network activity is used as a recognition principle for familiar stimuli. Application of the model to novelty detection in the hippocampus is discussed.  ...  A model of novelty detection is developed which is based on an oscillatory mechanism of memory formation and information processing.  ...  Acknowledgments The work of RB, YK, and OV was supported in part by the Russian Foundation of Basic Research (grant 99-04-49112 for RB and YK, grant 99-04-48281 for OV).  ... 
doi:10.1080/net.12.1.1.20 pmid:11254079 fatcat:jt7b5iqnonhjdjfnavx57vsau4

Novelty detection of rotating machinery using a non-parametric machine learning approach

Enrique Angola
2017 2017 IEEE International Conference on Prognostics and Health Management (ICPHM)  
The presented novelty detection technique could greatly enhance the performance of current state-of-the art condition monitoring systems, or could also be used as a stand-alone system.  ...  This anomaly detection technique can be used to monitor the health of a machine or could also be coupled with a current state of the art system to enhance its fault detection capabilities.  ...  This conclusion should be sufficient for the purposes of the novelty detection algorithm.  ... 
doi:10.1109/icphm.2017.7998304 dblp:conf/icphm/Angola17 fatcat:cdb45ejogrdqfklyobsjqa55ay

Confidence from Invariance to Image Transformations [article]

Yuval Bahat, Gregory Shakhnarovich
2018 arXiv   pre-print
In addition, we apply our technique to novelty detection scenarios, where we also demonstrate state of the art results.  ...  We develop a technique for automatically detecting the classification errors of a pre-trained visual classifier.  ...  Conclusion We have presented a new approach to error and novelty detection in visual classification, based on analysis of stability of classifier's output under a set of natural input transformations.  ... 
arXiv:1804.00657v1 fatcat:o3xdnjq4ljazjebxmq22hlilwm

Novelty Goes Deep. A Deep Neural Solution To Document Level Novelty Detection

Tirthankar Ghosal, Vignesh Edithal, Asif Ekbal, Pushpak Bhattacharyya, George Tsatsaronis, Srinivasa Satya Sameer Kumar Chivukula
2018 International Conference on Computational Linguistics  
The proposed method outperforms the existing benchmark on two document-level novelty detection datasets by a margin of ∼5% in terms of accuracy.  ...  We further demonstrate the effectiveness of our approach on a standard paraphrase detection dataset where the paraphrased passages closely resembles semantically redundant documents.  ...  We thank the anonymous reviewers for their valuable feedback and Prof. Donia Scott, University of Sussex for her advice in the Writing Mentoring Program as part of COLING 2018.  ... 
dblp:conf/coling/GhosalEEBTC18 fatcat:wiezgu3pnvdj3oraoy6ipafoaq
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