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1Using source code metrics
https://ieeexplore.ieee.org/abstract/document/9825846/
8 months ago by @scch
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1Finally Remember Precision and Recall | by Jakub Rysavy | Towards Data Science
Can't remember what is precision and recall (sensitivity)? Why accuracy is not enough? Read the explanation with an example with a confusion matrix.
a year ago by @ghagerer
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1Perplexity in Language Models. Evaluating language models using the… | by Chiara Campagnola | Towards Data Science
Perplexity is a useful metric to evaluate models in Natural Language Processing (NLP). This article will cover the two ways in which it is normally defined and the intuitions behind them. A language…
a year ago by @ghagerer
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llms
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1Chatbot Analytics: 9 Key Metrics You Must Track in 2023
The ultimate guide to chatbot analytics. Find out what bot metrics and KPIs you should measure and discover easy ways to optimize your chatbot performance.
a year ago by @ghagerer
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Chatgpt
evaluation
kpis
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Chatgptevaluationkpismetrics
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1Social Media Metrics as Indicators of Repository Impact from Making Institutional Repositories Work on JSTOR
Kim Holmberg, Stefanie Haustein, Daniel Beucke, Social Media Metrics as Indicators of Repository Impact, Making Institutional Repositories Work, pp. 235-248
a year ago by @antonioanic
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1What Improves Developer Productivity at Google? Code Quality. – Google Research
https://research.google/pubs/pub51783/
a year ago by @brightbyte
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study
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1Software Engineering at Google
https://abseil.io/resources/swe-book/html/ch07.html
a year ago by @brightbyte
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productivity
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1Measuring Engineering Productivity - by Abi Noda
https://newsletter.abinoda.com/p/engineering-productivity
a year ago by @brightbyte
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1Three-Bucket Framework for Engineering Metrics
https://newsletter.abinoda.com/p/choosing-engineering-metrics
a year ago by @brightbyte
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1jors2014_CJ - POST-PEER-REVIEW-PUBLISHERS.PDF
https://pure.manchester.ac.uk/ws/portalfiles/portal/24263271/POST-PEER-REVIEW-PUBLISHERS.PDF
a year ago by @brightbyte
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1Performance evaluation of proactive, reactive, and hybrid routing protocols for small, medium, and large mobile ad hoc networks
M. Gatete. BOHR Journal of Computational Intelligence and Communication Network, 2 (1): 5-10 (2024)
11 days ago by @bjcicnjournal
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evaluation
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3Automatic Evaluation of Attribution by Large Language Models
X. Yue, B. Wang, Z. Chen, K. Zhang, Y. Su, and H. Sun. (2023)
a month ago by @ghagerer
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attribution
fact-checking
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attributionfact-checkinghallucinationsllmsmetrics
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2Rethinking FID: Towards a Better Evaluation Metric for Image Generation
S. Jayasumana, S. Ramalingam, A. Veit, D. Glasner, A. Chakrabarti, and S. Kumar. (2024)
a month ago by @svanderbleek
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imggen
metrics
imggenmetrics
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2Prediction of user listening contexts for music playlists
J. Choi, A. Khlif, and E. Epure. Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), page 23--27. Online, Association for Computational Linguistics, (2020)
2 months ago by @sop2-ffzg
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Multimodal
Semantic
language
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Prediction
Data
aggregation
learning
analysis
Natural
Feature
from:kamber
Machine
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metrics
UserMultimodalSemanticlanguageEvaluationPredictionDataaggregationlearninganalysisNaturalFeaturefrom:kamberMachinePlaylistactivitiescurationcontextpredictionmetrics
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1Introduction altmetrics: What, why and where?
H. Piwowar. (2013)
3 months ago by @laura.lackovic
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citation_count
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1Can citation metrics predict the true impact of scientific papers?
R. Aroeira, and M. Castanho. (2020)
3 months ago by @nikastanicic
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2Prediction of user listening contexts for music playlists
J. Choi, A. Khlif, and E. Epure. Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), page 23--27. Online, Association for Computational Linguistics, (2020)
3 months ago by @kamber
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Data
Evaluation
Feature
Machine
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Playlist
Prediction
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activities
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prediction
DataEvaluationFeatureMachineMultimodalNaturalPlaylistPredictionSemanticUseractivitiesaggregationanalysiscontextcurationlanguagelearningmetricsprediction
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2Metrics and Trends in Assessing the Scientific Impact
G. Tsatsaronis. (2020)
3 months ago by @lucija_cirjak
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2Introduction to the Special Issue on Perspectives on Recommender Systems Evaluation
C. Bauer, A. Said, and E. Zangerle. ACM Trans. Recomm. Syst., 2 (1): 1–5 (Mar 7, 2024)
3 months ago by @bauerc
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evaluation
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literature
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myown
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evaluationintroductionliteraturemetricsmyownperspectivesrecsysreproducibilitysurvey
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1Assessment of Listed Cement Companies in India with Reference to Specific Valuation Parameters
B. Japee. INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 7 (2): 1104-1108 (April 2023)
11 months ago by @ijtsrd
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Analysis
Cement
Companies,
Corporate
Metrics
Valuation
Valuation,
AnalysisCementCompanies,CorporateMetricsValuationValuation,
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1Altmetrics – a complement to conventional metrics
M. Remedios. (2015)
a year ago by @antonioanic
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conventional
metrics
altmetricsconventionalmetrics
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1Green Chemistry for a Sustainable Future
D. Khirwar. INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 6 (5): 1402-1412 (August 2022)
2 years ago by @ijtsrd
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Greenest
chemistry
economy
global
manufacturing
metrics
recycling
sustainable
waste
Greenestchemistryeconomyglobalmanufacturingmetricsrecyclingsustainablewaste
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1Advanced Service Data Provisioning for Real-Time Management of Ongoing Cellular Communication Networks
M. Belkin, L. Zhukov, A. Sigov, and M. Vasil’ev. International Journal of Computer Networks & Communications (IJCNC), 14 (03): 107-119 (May 2022)
2 years ago by @laimbee
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5G
OILVCSEL
QoS
RoF-based
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and
beyond
bimodal
metrics
monitoring
network
radio
real-time
5GOILVCSELQoSRoF-basedaccessandbeyondbimodalmetricsmonitoringnetworkradioreal-time
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2How do the existing fairness metrics and unfairness mitigation algorithms contribute to ethical learning analytics?
O. Deho, C. Zhan, J. Li, J. Liu, L. Liu, and T. Le. British Journal of Educational Technology, (April 2022)
2 years ago by @ereidt
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ethics
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algorithmsethicsfairnesslearninganalyticsmachinelearningmetricsmitigation
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6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity
M. Leznik, J. Grohmann, N. Kliche, A. Bauer, D. Seybold, S. Eismann, S. Kounev, and J. Domaschka. Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering, page 89–96. New York, NY, USA, Association for Computing Machinery, (2022)
2 years ago by @joh.grohmann
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myown
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6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity
M. Leznik, J. Grohmann, N. Kliche, A. Bauer, D. Seybold, S. Eismann, S. Kounev, and J. Domaschka. Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering, page 89–96. New York, NY, USA, Association for Computing Machinery, (2022)
2 years ago by @samuel.kounev
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myown
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6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity
M. Leznik, J. Grohmann, N. Kliche, A. Bauer, D. Seybold, S. Eismann, S. Kounev, and J. Domaschka. Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering, page 89–96. New York, NY, USA, Association for Computing Machinery, (2022)
2 years ago by @simon.eismann
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myown
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6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity
M. Leznik, J. Grohmann, N. Kliche, A. Bauer, D. Seybold, S. Eismann, S. Kounev, and J. Domaschka. Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering, page 89–96. New York, NY, USA, Association for Computing Machinery, (2022)
2 years ago by @se-group
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1Bibliometric Services as a Research Support Services in Academic and Research Libraries
J. Stojanovski, and B. Macan. (2012.)
2 years ago by @anjaz
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AcademicLibraries
BibliometricServices
bibliometrics
indicators
libraries
metrics
AcademicLibrariesBibliometricServicesbibliometricsindicatorslibrariesmetrics
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6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity
M. Leznik, J. Grohmann, N. Kliche, A. Bauer, D. Seybold, S. Eismann, S. Kounev, and J. Domaschka. Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering, page 89–96. New York, NY, USA, Association for Computing Machinery, (2022)
2 years ago by @andre.bauer
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BibSonomy

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1Using source code metrics

1Finally Remember Precision and Recall | by Jakub Rysavy | Towards Data Science

1Perplexity in Language Models. Evaluating language models using the… | by Chiara Campagnola | Towards Data Science

1Chatbot Analytics: 9 Key Metrics You Must Track in 2023

1Social Media Metrics as Indicators of Repository Impact from Making Institutional Repositories Work on JSTOR

1What Improves Developer Productivity at Google? Code Quality. – Google Research

1Software Engineering at Google

1Measuring Engineering Productivity - by Abi Noda

1Three-Bucket Framework for Engineering Metrics

1jors2014_CJ - POST-PEER-REVIEW-PUBLISHERS.PDF

publications (hide)467
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1Performance evaluation of proactive, reactive, and hybrid routing protocols for small, medium, and large mobile ad hoc networks

3Automatic Evaluation of Attribution by Large Language Models

2Rethinking FID: Towards a Better Evaluation Metric for Image Generation

2Prediction of user listening contexts for music playlists

1Introduction altmetrics: What, why and where?

1Can citation metrics predict the true impact of scientific papers?

2Prediction of user listening contexts for music playlists

2Metrics and Trends in Assessing the Scientific Impact

2Introduction to the Special Issue on Perspectives on Recommender Systems Evaluation

1Assessment of Listed Cement Companies in India with Reference to Specific Valuation Parameters

1Altmetrics – a complement to conventional metrics

1Green Chemistry for a Sustainable Future

1Advanced Service Data Provisioning for Real-Time Management of Ongoing Cellular Communication Networks

2How do the existing fairness metrics and unfairness mitigation algorithms contribute to ethical learning analytics?

6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity

6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity

6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity

6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity

1Bibliometric Services as a Research Support Services in Academic and Research Libraries

6Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity

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