Truth is a Lie: 7 Myths about Human Annotation @CogComputing Forum 2014Lora Aroyo
Big data is having a disruptive impact across the sciences.
Human annotation of semantic interpretation tasks is a critical
part of big data semantics, but it is based on an antiquated
ideal of a single correct truth that needs to be similarly
disrupted.We expose seven myths about human annotation,
most of which derive from that antiquated ideal of truth,
and dispell these myths with examples from our research.We
propose a new theory of truth, Crowd Truth, that is based
on the intuition that human interpretation is subjective, and
that measuring annotations on the same objects of interpretation (in our examples, sentences) across a crowd will provide a useful representation of their subjectivity and the range of reasonable interpretations.
Crowds & Niches Teaching Machines to Diagnose: NLeSC Kick off eHumanities pr...Lora Aroyo
This presentation was given at the NL eSchience Center during the "De Geest Uit De Fles" event for the kick off of eHumanities project in 2014:
http://esciencecenter.nl/agenda/703-26-may-de-geest-uit-de-fles/
Good News is No News? Effects of Positive Stories about African Americans on ...Miglena Sternadori
This study used a 2 (session) x 2 (trial type) experimental design to explore whether positively valenced news stories about African Americans affect the malleability of implicit attitudes.
Truth is a Lie: 7 Myths about Human Annotation @CogComputing Forum 2014Lora Aroyo
Big data is having a disruptive impact across the sciences.
Human annotation of semantic interpretation tasks is a critical
part of big data semantics, but it is based on an antiquated
ideal of a single correct truth that needs to be similarly
disrupted.We expose seven myths about human annotation,
most of which derive from that antiquated ideal of truth,
and dispell these myths with examples from our research.We
propose a new theory of truth, Crowd Truth, that is based
on the intuition that human interpretation is subjective, and
that measuring annotations on the same objects of interpretation (in our examples, sentences) across a crowd will provide a useful representation of their subjectivity and the range of reasonable interpretations.
Crowds & Niches Teaching Machines to Diagnose: NLeSC Kick off eHumanities pr...Lora Aroyo
This presentation was given at the NL eSchience Center during the "De Geest Uit De Fles" event for the kick off of eHumanities project in 2014:
http://esciencecenter.nl/agenda/703-26-may-de-geest-uit-de-fles/
Good News is No News? Effects of Positive Stories about African Americans on ...Miglena Sternadori
This study used a 2 (session) x 2 (trial type) experimental design to explore whether positively valenced news stories about African Americans affect the malleability of implicit attitudes.
Truth is a Lie: Rules & Semantics from Crowd Perspectives (RR'2015 Keynote)Lora Aroyo
http://crowdtruth.org
Processing real-world data with the crowd leaves one thing absolutely clear - there is no single notion of truth, but rather a spectrum that has to account for context, opinions, perspectives and shades of grey. CrowdTruth is a new framework for processing of human semantics drawn more from the notion of consensus then from set theory.
Visualization of Disagreement-based Quality Metrics of Crowdsourcing DataCrowdTruth
Crowdsourcing represents a significant source of data which needs to be analyzed and interpreted. These tasks influence the quality of the output as well as the efficiency of the process. Visualization proved to be an effective way of dealing with large amount of data. In this paper we propose a visualization analytic model in the context of the CrowdTruth framework and CrowdTruth metrics for optimizing the crowdsourcing process and improving its data quality. The requirements for the dynamic, scalable and interactive visualizations were extracted through literature and interviews with users of the framework.
Utilizing Social Health Websites for Cognitive Computing and Clinical Decisio...CrowdTruth
Crowdsourced annotations data offers cognitive computing systems insights in lay semantics. This is especially important in health care, where medical terminology is often not aligned with patients `lay' language. However, the general crowd often has limited medical knowledge. Therefore this research investigated the opportunities of social health websites for obtaining ground truth annotations data for cognitive computing systems including clinical decision support systems. By identifying these websites and analyzing their data, it offers a starting point for the future utilization of user-generated health content for cognitive systems. However, the opportunities of social health data are currently limited by various legal regulations. Therefore this paper also dwells on the legal aspects of implementing social health data for cognitive computing systems.
Kick-off meeting on February 24th 2017 for the Linkflows project, a collaboration between the Web & Media Sciences Group, Computer Science Department, Vrije Universiteit Amsterdam, IOS Press and Netherlands Institute for Sound and Vision.
DIVE INTO THE EVENT-BASED
BROWSING OF LINKED HISTORICAL MEDIA
VICTOR DE BOER, JOHAN OOMEN, OANA INEL, LORA AROYO, ELCO VAN STAVEREN, WERNER HELMICH AND DENNIS DE BEURS
Many scholars have pointed out that the classical way of publishing scientific articles is ill-suited to deal with the rapid growth of both, volume and complexity, of scientific contributions. To overcome these problems, next generation scientific publishing has to respond to the increasing importance of datasets and software, and needs to provide methods to automatically organize and aggregate reported scientific findings. Perhaps the most important shortcoming of the current publication system is that scientific papers do not come with formal semantics that could be processed, aggregated, and interpreted in an automated fashion.
Semantic publishing is a general approach to tackle this problem using the concepts and tools of the Semantic Web and related fields.
Stitch by Stitch: Annotating Fashion at the RijksmuseumLora Aroyo
https://www.rijksmuseum.nl/en/stitch-by-stitch
http://annotate.accurator.nl/
Fashion can be found everywhere in museums. Fashion heritage collected over centuries: costumes, accessories, paintings, prints and photographs. But while some clothes and accessories are easily found and identified, others are obscure and require a trained eye to describe. What are we looking at? What kind of sleeve is this? Which materials and techniques have been used? More specific descriptions of the images facilitate better use of digital collections and enable users to wander through them in detail.
Rating Evaluation Methods through Correlation MTE 2014 Workshop May 2014Welocalize
Welocalize presentation by Lena Marg. Machine translation research focused on the results from a major data gathering exercise we carried out in 2014 by the Welocalize Language Tools team.
We correlated results from automatic scoring (in this case referencing BLEU), human scoring of raw MT output on a 1-5 Likert scale, as well as productivity test deltas from 2013 data. The total test set comprising 22 locales, five different MT systems and various source content types. In line with findings from other speakers and recent publications, we found that while automatic scores such as BLEU serve as great trend indicators for overall MT system performance, they don’t tell us much about how useful the given MT output is for post-editors. Human scoring, on the other hand, correlated with productivity gains seen in post-editing and error classification proves a better indicator on usability. This confirmed the validity of our evaluation approach, comprising productivity data and human evaluation.
For additional information, visit http://www.welocalize.com/wemt/why-wemt/
Explaining correlation, assumptions,coefficients of correlation, coefficient of determination, variate, partial correlation, assumption, order and hypothesis of partial correlation with example, checking significance and graphical representation of partial correlation.
Truth is a Lie: Rules & Semantics from Crowd Perspectives (RR'2015 Keynote)Lora Aroyo
http://crowdtruth.org
Processing real-world data with the crowd leaves one thing absolutely clear - there is no single notion of truth, but rather a spectrum that has to account for context, opinions, perspectives and shades of grey. CrowdTruth is a new framework for processing of human semantics drawn more from the notion of consensus then from set theory.
Visualization of Disagreement-based Quality Metrics of Crowdsourcing DataCrowdTruth
Crowdsourcing represents a significant source of data which needs to be analyzed and interpreted. These tasks influence the quality of the output as well as the efficiency of the process. Visualization proved to be an effective way of dealing with large amount of data. In this paper we propose a visualization analytic model in the context of the CrowdTruth framework and CrowdTruth metrics for optimizing the crowdsourcing process and improving its data quality. The requirements for the dynamic, scalable and interactive visualizations were extracted through literature and interviews with users of the framework.
Utilizing Social Health Websites for Cognitive Computing and Clinical Decisio...CrowdTruth
Crowdsourced annotations data offers cognitive computing systems insights in lay semantics. This is especially important in health care, where medical terminology is often not aligned with patients `lay' language. However, the general crowd often has limited medical knowledge. Therefore this research investigated the opportunities of social health websites for obtaining ground truth annotations data for cognitive computing systems including clinical decision support systems. By identifying these websites and analyzing their data, it offers a starting point for the future utilization of user-generated health content for cognitive systems. However, the opportunities of social health data are currently limited by various legal regulations. Therefore this paper also dwells on the legal aspects of implementing social health data for cognitive computing systems.
Kick-off meeting on February 24th 2017 for the Linkflows project, a collaboration between the Web & Media Sciences Group, Computer Science Department, Vrije Universiteit Amsterdam, IOS Press and Netherlands Institute for Sound and Vision.
DIVE INTO THE EVENT-BASED
BROWSING OF LINKED HISTORICAL MEDIA
VICTOR DE BOER, JOHAN OOMEN, OANA INEL, LORA AROYO, ELCO VAN STAVEREN, WERNER HELMICH AND DENNIS DE BEURS
Many scholars have pointed out that the classical way of publishing scientific articles is ill-suited to deal with the rapid growth of both, volume and complexity, of scientific contributions. To overcome these problems, next generation scientific publishing has to respond to the increasing importance of datasets and software, and needs to provide methods to automatically organize and aggregate reported scientific findings. Perhaps the most important shortcoming of the current publication system is that scientific papers do not come with formal semantics that could be processed, aggregated, and interpreted in an automated fashion.
Semantic publishing is a general approach to tackle this problem using the concepts and tools of the Semantic Web and related fields.
Stitch by Stitch: Annotating Fashion at the RijksmuseumLora Aroyo
https://www.rijksmuseum.nl/en/stitch-by-stitch
http://annotate.accurator.nl/
Fashion can be found everywhere in museums. Fashion heritage collected over centuries: costumes, accessories, paintings, prints and photographs. But while some clothes and accessories are easily found and identified, others are obscure and require a trained eye to describe. What are we looking at? What kind of sleeve is this? Which materials and techniques have been used? More specific descriptions of the images facilitate better use of digital collections and enable users to wander through them in detail.
Rating Evaluation Methods through Correlation MTE 2014 Workshop May 2014Welocalize
Welocalize presentation by Lena Marg. Machine translation research focused on the results from a major data gathering exercise we carried out in 2014 by the Welocalize Language Tools team.
We correlated results from automatic scoring (in this case referencing BLEU), human scoring of raw MT output on a 1-5 Likert scale, as well as productivity test deltas from 2013 data. The total test set comprising 22 locales, five different MT systems and various source content types. In line with findings from other speakers and recent publications, we found that while automatic scores such as BLEU serve as great trend indicators for overall MT system performance, they don’t tell us much about how useful the given MT output is for post-editors. Human scoring, on the other hand, correlated with productivity gains seen in post-editing and error classification proves a better indicator on usability. This confirmed the validity of our evaluation approach, comprising productivity data and human evaluation.
For additional information, visit http://www.welocalize.com/wemt/why-wemt/
Explaining correlation, assumptions,coefficients of correlation, coefficient of determination, variate, partial correlation, assumption, order and hypothesis of partial correlation with example, checking significance and graphical representation of partial correlation.
Sentence level sentiment polarity calculation for customer reviews by conside...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
this activity is designed for you to explore the continuum of an a.docxhowardh5
this activity is designed for you to explore the continuum of an addictive behavior of your choice.
Addictive behavior appears in stages. The earliest stage is non-use, which finally leads up to out-of-control dependence. The stages in between are important to identify, as it is much easier to correct an early-stage issue as opposed to a late-stage problem.
After reviewing the module readings and tasks, use the module notes as a reference and alcohol or substance abuse addiction as an example to identify the various levels of addiction.
You may choose to develop a time line identifying the stages or develop a written essay (no more than 500 words in Word format) to describe the escalation of addictive behaviors.
You are to include at least two references from academic sources that you have researched on this topic in the Excelsior College Library and use appropriate citations in American Psychological Association (APA) style.
You cannot just do a Google search for the topic! Academic sources are required. You may use Google Scholar or other libraries.
Chapter 13
Qualitative Data Analysis
1
Process of Qualitative Data Analysis
Preparing the Qualitative Data
Transform the data into readable text
Check for and resolve transcription errors
Manage the data
Organize by attribute coding
Two Separate Processes
5
Coding: Involves labeling and breaking down the data to find:
Patterns
Themes
Interpretation: Giving meaning to the identified patterns and themes
Coding
Starts with identifying the unit of analysis
Coding categories may reflect realms of meaning or different activities.
Coding categories can be theoretically-based or inductively created emerging from the data.
Use of Analytical Memos
7
Analytical memos help researchers w/ process of breaking down the data
Personal reflections on the research experience, methodological issues, or patterns in the data
Comes in 3 varieties:
Code notes
Operational notes
Theoretical notes
Data Displays
Taxonomy: system of ordered classification
Data matrix: individuals or other units represent columns and coding categories represent rows
Typologies: representation of findings based on the interrelationship between two or more ideas, concepts, or variables
Flow charts: diagrams that display processes
Taxonomy of Survival Strategies
Data Matrix: Homeless Individuals by Dimensions
Drawing and Evaluating Conclusions
Conclusions may result in:
Rich descriptions
Identification of themes
Inferences about patterns and concepts
Theoretical propositions
Evaluation of the data can occur by:
Comparing notes among observers
Using multiple sources of data
Examining exceptions to the data patterns
Member checking
Variations in Qualitative Data Analysis: Grounded Theory
Objective is to develop theory from data
Emphasizes people’s actions and voices as the main sources of d.
The most integral part of our work is to extract Aspects from User Feedback and associate Sentiment and Opinion terms to them. The dataset we have at our disposal to work upon, is a set of feedback documents for various departments in a Hospital in XML format which have comments represented in tags. It contains about 65000 responses to a survey taken in a Hospital. Every response or comment is treated as a sentence or a set of them. We perform a sentence level aspect and sentiment extraction and we attempt to understand and mine User Feedback data to gather aspects from it. Further to it, we extract the sentiment mentions and evaluate them contextually for sentiment and associate those sentiment mentions with the corresponding aspects. To start with, we perform a clean up on the User Feedback data, followed by aspect extraction and sentiment polarity calculation, with the help of POS tagging and SentiWordNet filters respectively. The obtained sentiments are further classified according to a set of Linguistic rules and the scores are normalized to nullify any noise that might be present. We lay emphasis on using a rule based approach; rules being Linguistic rules that correspond to the positioning of various parts-of-speech words in a sentence.
Cost and Quality Analysis 1Unsatisfactory0.002Less th.docxvanesaburnand
Cost and Quality Analysis
1
Unsatisfactory
0.00%
2
Less than Satisfactory
80.00%
3
Satisfactory
88.00%
4
Good
92.00%
5
Excellent
100.00%
75.0 %Content
10.0 %Describe the relationship between health care cost and quality.
Does not describe the relationship between health care cost and quality.
Describes issues related to health care cost and health care quality, but does not discuss the relationship between the two.
Describes the relationship between health care cost and quality, but is insufficiently developed.
Adequately describes the relationship between health care cost and quality. There are few inconsistencies. Few examples given.
Fully describes the relationship between health care cost and quality with no inconsistencies. Clear examples given.
20.0 %Differentiate the roles and major activities between one public and one private agency in addressing cost and quality in healthcare.
Does not discuss the roles and major activities of public or private agencies in addressing cost and quality in health care.
Discusses either the roles or the major activities of one public and one private agency in cost and quality in health care, but not both.
Discusses, but does not differentiate the roles and major activities of one public and one private agency in addressing cost and quality in health care.
Differentiates the roles and major activities between one public and one private agency in addressing cost and quality in health care, but is insufficiently developed. Minimal use of examples, supporting details, or references.
Clearly and systematically differentiates the roles and major activities between one public and one private agency in addressing cost and quality in health care utilizing references, examples, and supporting details.
20.0 %Analyze current and projected initiatives to improve quality while simultaneously controlling costs. Describe any unintended consequences.
Does not discuss current and projected initiatives to improve quality while simultaneously controlling costs. Does not describe any unintended consequences.
Discusses either current or projected initiatives to improve quality while simultaneously controlling costs, but not both. Does not describe unintended consequences.
Discusses current and projected initiatives to improve quality while simultaneously controlling costs. Does not describe any unintended consequences.
Partially analyzes current and projected initiatives to improve quality while simultaneously controlling costs. Minimally describes unintended consequences.
Comprehensively analyzes current and projected initiatives to improve quality while simultaneously controlling costs. Fully describes unintended consequences. Clear examples given.
20.0 %Synthesize implications for staff nurses and advanced practice nurses, including evidence-based practice, relative to cost and quality.
Does not address any implications for staff nurses and advanced practice nurses, or evidence-based practice, relative to cost and q.
EVALUATION OF SEMANTIC ANSWER SIMILARITY METRICSkevig
There are several issues with the existing general machine translation or natural language generation
evaluation metrics, and question-answering (QA) systems are indifferent in that context. To build robust
QA systems, we need the ability to have equivalently robust evaluation systems to verify whether model
predictions to questions are similar to ground-truth annotations. The ability to compare similarity based
on semantics as opposed to pure string overlap is important to compare models fairly and to indicate more
realistic acceptance criteria in real-life applications. We build upon the first to our knowledge paper that
uses transformer-based model metrics to assess semantic answer similarity and achieve higher correlations
to human judgement in the case of no lexical overlap. We propose cross-encoder augmented bi-encoder and
BERTScore models for semantic answer similarity, trained on a new dataset consisting of name pairs of
US-American public figures. As far as we are concerned, we provide the first dataset of co-referent name
string pairs along with their similarities, which can be used for training
Similar to (Presentation Chris) Crowdsourcing & Semantic Web: Dagstuhl 2014 (20)
The Rijksmuseum Collection as Linked DataLora Aroyo
Presentation at ISWC2018: http://iswc2018.semanticweb.org/sessions/the-rijksmuseum-collection-as-linked-data/ of our paper published originally in the Semantic Web Journal: http://www.semantic-web-journal.net/content/rijksmuseum-collection-linked-data-2
Many museums are currently providing online access to their collections. The state of the art research in the last decade shows that it is beneficial for institutions to provide their datasets as Linked Data in order to achieve easy cross-referencing, interlinking and integration. In this paper, we present the Rijksmuseum linked dataset (accessible at http://datahub.io/dataset/rijksmuseum), along with collection and vocabulary statistics, as well as lessons learned from the process of converting the collection to Linked Data. The version of March 2016 contains over 350,000 objects, including detailed descriptions and high-quality images released under a public domain license.
FAIRview: Responsible Video Summarization @NYCML'18Lora Aroyo
Presentation at the NYC Media Lab (NYCML2018). There is a growing demand for news videos online, with more consumers preferring to watch the news than read or listen to it. On the publisher side, there is a growing effort to use video summarization technology in order to create easy-to-consume previews (trailers) for different types of broadcast programs. How can we measure the quality of video summaries and their potential to misinform? This workshop will inform participants about automatic video summarization algorithms and how to produce more “representative” video summaries. The research presented is from the FAIRview project and is supported by the Digital News Innovation Fund (DNI Fund), which is part of the Google News Initiative.
DH Benelux 2017 Panel: A Pragmatic Approach to Understanding and Utilising Ev...Lora Aroyo
Lora Aroyo, Chiel van den Akker, Marnix van Berchum, Lodewijk
Petram, Gerard Kuys, Tommaso Caselli, Jacco van Ossenbruggen, Victor de Boer, Sabrina Sauer, Berber Hagedoorn
Crowdsourcing ambiguity aware ground truth - collective intelligence 2017Lora Aroyo
The process of gathering ground truth data through human annotation is a major bottleneck in the use of information extraction methods. Crowdsourcing-based approaches are gaining popularity in the attempt to solve the issues related to the volume of data and lack of annotators. Typically these practices use inter-annotator agreement as a measure of quality. However, this assumption often creates issues in practice. Previous experiments we performed found that inter-annotator disagreement is usually never captured, either because the number of annotators is too small to capture the full diversity of opinion, or because the crowd data is aggregated with metrics that enforce consensus, such as majority vote. These practices create artificial data that is neither general nor reflects the ambiguity inherent in the data.
To address these issues, we proposed the method for crowdsourcing ground truth by harnessing inter-annotator disagreement. We present an alternative approach for crowdsourcing ground truth data that, instead of enforcing an agreement between annotators, captures the ambiguity inherent in semantic annotation through the use of disagreement-aware metrics for aggregating crowdsourcing responses. Based on this principle, we have implemented the CrowdTruth framework for machine-human computation, that first introduced the disagreement-aware metrics and built a pipeline to process crowdsourcing data with these metrics.
In this paper, we apply the CrowdTruth methodology to collect data over a set of diverse tasks: medical relation extraction, Twitter event identification, news event extraction and sound interpretation. We prove that capturing disagreement is essential for acquiring a high-quality ground truth. We achieve this by comparing the quality of the data aggregated with CrowdTruth metrics with a majority vote, a method which enforces consensus among annotators. By applying our analysis over a set of diverse tasks we show that, even though ambiguity manifests differently depending on the task, our theory of inter-annotator disagreement as a property of ambiguity is generalizable.
My ESWC 2017 keynote: Disrupting the Semantic Comfort ZoneLora Aroyo
Ambiguity in interpreting signs is not a new idea, yet the vast majority of research in machine interpretation of signals such as speech, language, images, video, audio, etc., tend to ignore ambiguity. This is evidenced by the fact that metrics for quality of machine understanding rely on a ground truth, in which each instance (a sentence, a photo, a sound clip, etc) is assigned a discrete label, or set of labels, and the machine’s prediction for that instance is compared to the label to determine if it is correct. This determination yields the familiar precision, recall, accuracy, and f-measure metrics, but clearly presupposes that this determination can be made. CrowdTruth is a form of collective intelligence based on a vector representation that accommodates diverse interpretation perspectives and encourages human annotators to disagree with each other, in order to expose latent elements such as ambiguity and worker quality. In other words, CrowdTruth assumes that when annotators disagree on how to label an example, it is because the example is ambiguous, the worker isn’t doing the right thing, or the task itself is not clear. In previous work on CrowdTruth, the focus was on how the disagreement signals from low quality workers and from unclear tasks can be isolated. Recently, we observed that disagreement can also signal ambiguity. The basic hypothesis is that, if workers disagree on the correct label for an example, then it will be more difficult for a machine to classify that example. The elaborate data analysis to determine if the source of the disagreement is ambiguity supports our intuition that low clarity signals ambiguity, while high clarity sentences quite obviously express one or more of the target relations. In this talk I will share the experiences and lessons learned on the path to understanding diversity in human interpretation and the ways to capture it as ground truth to enable machines to deal with such diversity.
Data Science with Human in the Loop @Faculty of Science #Leiden UniversityLora Aroyo
Software systems are becoming ever more intelligent and more useful, but the way we interact with these machines too often reveals that they don’t actually understand people. Knowledge Representation and Semantic Web focus on the scientific challenges involved in providing human knowledge in machine-readable form. However, we observe that various types of human knowledge cannot yet be captured by machines, especially when dealing with wide ranges of real-world tasks and contexts. The key scientific challenge is to provide an approach to capturing human knowledge in a way that is scalable and adequate to real-world needs. Human Computation has begun to scientifically study how human intelligence at scale can be used to methodologically improve machine-based knowledge and data management. My research is focusing on understanding human computation for improving how machine-based systems can acquire, capture and harness human knowledge and thus become even more intelligent. In this talk I will show how the CrowdTruth framework (http://crowdtruth.org) facilitates data collection, processing and analytics of human computation knowledge.
Some project links:
- http://controcurator.org/
- http://crowdtruth.org/
- http://diveproject.beeldengeluid.nl/
- http://vu-amsterdam-web-media-group.github.io/linkflows/
Crowdsourcing & Nichesourcing: Enriching Cultural Heritagewith Experts & Cr...Lora Aroyo
Presentation at the "Past, Present and Future of Digital Humanities & Social Sciences in the Netherlands" event, http://www.ehumanities.nl/past-present-and-future-of-digital-humanities-social-sciences-in-the-netherlands-programme-and-abstracts-2/
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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1. How to Measure Quality
with Disagreement?
or the Three Sides of
CrowdTruth
Lora Aroyo & Chris Welty
2. CrowdTruth
Annotator disagreement is signal, not noise.
It is indicative of the variation in human
semantic interpretation of signs
It can indicate ambiguity, vagueness,
similarity, over-generality, etc, as well as
quality
3. CrowdTruth Dependencies
worker metrics for detecting spam
à quality of sentences
à quality of the target semantics
worker quality metrics can improve significantly when the
quality of these other aspects of semantic interpretation
are considered
7. Feeling the way the CHEST expands (PALPATION), can identify areas of
the lung that are full of fluid.
?PALPATIONIs CHEST related to
diagnose location associated
with
is_a otherpart_of
0 0 02 3 0 0 0 1 0 0 44 1
Disagreement for Sentence
Clarity
Unclear relationship between the two arguments
reflected in the disagreement
8. ?CONJUNCTIVITISHYPERAEMIA related toIs
0 0 0 1 0 0 0 013 0 0 0 0 0
symptomcause
Redness (HYPERAEMIA), irritation (chemosis) and watering (epiphora)
of the eyes are symptoms common to all forms of CONJUNCTIVITIS.
Disagreement for Sentence
Clarity
Clearly expressed relation between the two
arguments reflected in the agreement
9. Sentence-Relation Score
Measures how clearly a sentence expresses a relation
0
1
1
0
0
4
3
0
0
5
1
0
Unit vector for
relation R6
Sentence
Vector
Cosine = .55
11. Worker Metrics
how much A WORKER disagrees with THE CROWD per sentence à the avg
of all cosine distances between each worker’s sentence vector & the full sentence
vector (minus that worker)
are there consistently like-minded workers à pairwise metric - avg for a
particular worker à there may be communities of thought that consistently
disagree with others, but agree within themselves
Low quality workers generally have high scores in both
avg relations per sentence à per worker the number of relations he/she
chooses per sentence averaged over all sentences he/she annotates.
High score here can help indicate low quality workers.
12. Sentence Metrics
Sentence-relation score à core CrowdTruth metric for
relation extraction à measured for each relation on each
sentence as the cosine of the unit vector for the relation
with the sentence vector
indicating that a relation is clearly or vaguely expressed,
Sentence clarity à defined for each sentence as the max
relation score for that sentence
indicating a clear or ambiguous or confusing sentence
13. Relation Metrics
Relation similarity à the causal power (pairwise conditional
probability). high similarity score indicates the relations are
confusable to workers
Relation ambiguity is defined for each relation as the max relation
similarity for the relation. If a relation is clear, then it will have a low
score.
Relation clarity à defined for each relation as the max
sentence-relation score for the relation over all sentences.
If a relation has a high clarity score, it means that
it is at least possible to express the relation clearly
Relation frequency is the number of times the relation is
annotated at least once in a sentence
16. Impact of Sentence Quality on
Worker Quality
(a) the space with no filtering of sentences or relations, a single line cannot separate the
spammers from non-spammers
(b) the space after sentence filtering, Figure (c) after relation filtering, and Figure (d)
after both sentence and relation filtering. Sentence filtering makes the classes
linearly separable, and the separation between the classes increases in the
subsequent figures.
17. Impact of Relation
Quality on Worker
Quality
(a) the space with no filtering of sentences or relations,
a single line cannot separate the spammers from non-
spammers
(c) after relation filtering
the relation filtering much more clearly
defines the space, with a large
separation between positive and
negative instances.
the pairwise improvements to the
worker scores are significant
with p < :001, which is better than the
sentence clarity improvements
18. Combining Sentence &
Relation Filtering
• first filtering out low clarity
sentences
• then filtering vague and
ambiguous relations
• worker metrics were
computed on these new
sentences and vectors
• proves to even further
separate the space, and the
pairwise improvement in
worker scores from the
baseline (unfiltered) is
significant with p < :0005.
• The improvement over
sentence filtering alone is
also significant (p < :01)
• The improvement over
relation filtering alone is only
significant with p < :05.
19. quality measures in
semantic interpretation tasks
are inter-dependent
higher accuracy can be achieved by considering the impact of
sentence quality & relation quality on worker quality measurements
significant improvement in worker quality metrics with respect
to known spammers by incorporating the quality of the individual
sentences & target relations
relationships between the different corners of the triangle of
reference, e.g.
à the impact of relation & worker quality on sentence measures,
à the impact of worker & sentence quality on relation measures