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A utility-theoretic ranking method for semi-automated text classification
2012
Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12
In Semi-Automated Text Classification (SATC) an automatic classifierΦ labels a set of unlabelled documents D, following which a human annotator inspects (and corrects when appropriate) the labels attributed ...
We develop a new utility-theoretic ranking method based on the notion of inspection gain, defined as the improvement in classification effectiveness that would derive by inspecting and correcting a given ...
We call this scenario semi-automated text classification (SATC). ...
doi:10.1145/2348283.2348411
dblp:conf/sigir/BerardiES12
fatcat:6g2slzcggzczdf2huu2hr3lcv4
Utility-Theoretic Ranking for Semiautomated Text Classification
2015
ACM Transactions on Knowledge Discovery from Data
Semi-Automated Text Classification (SATC) may be defined as the task of ranking a set D of automatically labelled textual documents in such a way that, if a human annotator validates (i.e., inspects and ...
We develop new utility-theoretic ranking methods based on the notion of validation gain, defined as the improvement in classification effectiveness that would derive by validating a given automatically ...
ACKNOWLEDGMENTS We would like to thank David Lewis and Diego Marcheggiani for many interesting discussions on the topics of this article. ...
doi:10.1145/2742548
fatcat:banga6436jdh5pfohgpleliztq
Semi-Automated Text Classification for Sensitivity Identification
2015
Proceedings of the 24th ACM International on Conference on Information and Knowledge Management - CIKM '15
We look at sensitivity identification in terms of semi-automated text classification (SATC), the task of ranking automatically classified documents so as to optimize the cost-effectiveness of human post-checking ...
., for personal or organizational privacy reasons. ...
Hence, in this paper, our application of the utility-theoretic approach for semi-automated text classification to the recalloriented task of sensitivity identification, brings two contributions: (i) it ...
doi:10.1145/2806416.2806597
dblp:conf/cikm/BerardiEMO015
fatcat:sdeeh5jatrckrk35aq33jgifka
Content-specific network analysis of peer-to-peer communication in an online community for smoking cessation
2017
AMIA Annual Symposium Proceedings
In this paper, we present a methodology for high-throughput semantic and network analysis of large social media datasets, combining semi-automated text categorization with social network analytics. ...
Implications for socio-behavioral health and wellness platforms are also discussed. ...
SVD implementation we used for LSA. ...
pmid:28269890
pmcid:PMC5333292
fatcat:6zraiatuavenfngq64otipkcya
Unsupervised Key-phrase Extraction and Clustering for Classification Scheme in Scientific Publications
[article]
2021
arXiv
pre-print
Several methods have been explored for automating parts of Systematic Mapping (SM) and Systematic Review (SR) methodologies. ...
Finally Semantic key-phrase clustering at term-level can group similar terms together that can be suitable for classification scheme. ...
Recent text-mining algorithms and NLP techniques can become particularly useful for automating (parts of) this manual work within the systematic mapping studies procedure. ...
arXiv:2101.09990v2
fatcat:n6vnkvwxlbc4bogzx5ootfyyya
Active Learning Strategies for Technology Assisted Sensitivity Review
[chapter]
2018
Lecture Notes in Computer Science
Therefore, there is a need for new technology assisted review protocols to integrate automatic sensitivity classification into the sensitivity review process. ...
In this work, we present a thorough evaluation of active learning strategies for sensitivity review. ...
In that work, the authors evaluated the effectiveness of a utilitytheoretic [10] semi-automated text classification (SATC) approach, for sensitivity classification. The approach of Berardi et al. ...
doi:10.1007/978-3-319-76941-7_33
fatcat:kroy3sx4czef5g5fuo7k45q6vq
Data-Driven Requirements Elicitation: A Systematic Literature Review
2021
SN Computer Science
The outcomes of automated requirements elicitation often result in mere identification and classification of requirements-related information or identification of features, without eliciting requirements ...
The results reveal that the existing automated requirements elicitation primarily focuses on utilizing human-sourced data, especially online reviews, as requirements sources, and supervised machine learning ...
Semi-automation refers to having a human-in-the-loop for automating requirements elicitation, thus requirements are directed by human interactions. ...
doi:10.1007/s42979-020-00416-4
fatcat:g4g7nb4mwbhuhgmmfxi5vir5ly
KDD2008 workshop report DMMT'08
2008
SIGKDD Explorations
matrix computations • Feature selection and extraction • Graph-based learning (classification, semi-supervised learning and unsupervised learning) • Matrix factorization for classification Application ...
and Sparsification • Sparse PCA and SVD • Randomized algorithms for matrix computation • Web search and ranking algorithms • Tensor analysis, 2DSVD and high order SVD • GSVD for classification • Latent ...
doi:10.1145/1540276.1540293
fatcat:724tpyimyzfx7hzx2g6t3lkjrq
From Theories to Queries
2011
Journal of machine learning research
This article surveys recent work in active learning aimed at making it more practical for real-world use. ...
An active learner might iteratively select informative query instances to be labeled by an oracle, for example. ...
sentiment classification in blogs using the pooling multinomials naïve Bayes approach, and consider a similar query setting for a semi-supervised graph/kernel-based text classifier. ...
dblp:journals/jmlr/Settles11
fatcat:ezffijkj35g4bgktfm3k2z5aoi
Graph Data Augmentation for Graph Machine Learning: A Survey
[article]
2022
arXiv
pre-print
We conclude by outlining currently unsolved challenges as well as directions for future research. ...
Although several automated augmentation solutions exist for graph contrastive learning, automated augmentation methods for (semi-)supervised graph learning are still needed. ...
Mixup Several Mixup methods were also proposed for graph classification. For example, the aforementioned Graph Mixup [Wang et al., 2021b ] also works for graph classification. ...
arXiv:2202.08871v1
fatcat:gjf7mgihkfbqdg6cqscflcw6ga
An approach based on Combination of Features for automatic news retrieval
[article]
2020
arXiv
pre-print
Then, using the proposed approach, techniques of text categorization, evaluation criteria and ranking algorithms, the data were analyzed and examined. ...
Understanding this information is very important for providing the best set of information resources for users. ...
In their paper the multiword considered as an alternative index terms in vector space model for text representation with theoretical support. ...
arXiv:2004.11699v1
fatcat:vppybnsh4rdixiqz3vrdsf2iva
Network Text Analysis in Computer-Intensive Rapid Ethnography Retrieval: An Example from Political Networks of Sudan
2019
Journal of Social Structure
descriptions from texts and fusing the results from varied sources. ...
Advances in text analysis, particularly the ability to extract network based information from texts, is enabling researches to conduct detailed socio-cultural ethnographies rapidly by retrieving characteristic ...
Hence, the potential exists to use semi-automated text mining and assessment techniques to rapidly process vast quantities of text-based information. ...
doi:10.21307/joss-2019-028
fatcat:3dyucijqbvcdvpkeswkwsx26xu
Unsupervised Approaches for Textual Semantic Annotation, A Survey
2019
ACM Computing Surveys
Link to publication Creative Commons License (see https://creativecommons.org/use-remix/cc-licenses): CC BY Citation for published version (APA): ...
ACKNOWLEDGMENTS The authors thank the anonymous reviewers for their helpful comments, in addition to Cees de Laat, Paul Martin, Jayachander Surbiryala, and ZeShun Shi for useful discussions. ...
The candidate proper nouns are then categorized into the highest ranked concepts as the annotation for that piece of text. ...
doi:10.1145/3324473
fatcat:fg5ucwtloze6ljdlh4hqjkqxfe
Classification of Consumer Belief Statements From Social Media
[article]
2021
arXiv
pre-print
on text classification tasks. ...
It is not yet fully understood how this can be leveraged successfully for classification. ...
We perceive a great potential in semi-automated class abstraction, especially for large-scale content analysis. ...
arXiv:2106.15498v1
fatcat:2zctkylvsbehfdxcvzpyki2cme
Optimising human inspection work in automated verbatim coding
2014
International Journal of Market Research
However, in some of these contexts the accuracy standards imposed by the customer may be too high for today's automated verbatim coding technology; this means that human coders may need to devote some ...
) maximises the reduction in the overall error achieved for an available amount of human inspection work. † The order in which the authors are listed is purely alphabetical; each author has given an equally ...
Thanks also to Ivano Luberti for many interesting discussions, and to two anonymous reviewers for providing many stimulating comments. ...
doi:10.2501/ijmr-2014-032
fatcat:z443gs5idfhtnmd36jwvmduj5u
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