This presentation is not mine so all credits go to Zubair Junjunia. I am sharing as this as it covers the whole content of paper 6 - Alternative to practical for CIE IGCSE Biology
but can be useful for paper 5 or other boards.
This presentation is not mine so all credits go to Zubair Junjunia. I am sharing as this as it covers the whole content of paper 6 - Alternative to practical for CIE IGCSE Biology
but can be useful for paper 5 or other boards.
Russian Standard Vodka - Advertising Research, Proposal, Media Plan, Sample C...Jaddan Bruhn
Advertising proposal, including research, promotional strategy, media plan, sample creative and evaluation metrics for Russian Standard Vodka 300ml ready to drink (premixed) product.
Towards Culturally Aware AI Systems - TSDH SymposiumMarieke van Erp
Towards Culturally Aware AI Systems
Presented 23 June 2021
Slide credits: Cultural AI team members Andrei Nesterov, Laura Hollink, Ryan Brate, Valentin Vogelmann + input and inspiration from all Cultural AI Colleagues
Biases in data can be both explicit and implicit. Explicitly, ‘The Dutch Seventeenth Century’ and ‘The Dutch Golden Age’ are pseudo-synonymous and refer to a particular era of Dutch history. Implicitly, the ‘Golden Age’ moniker is contested due to the fact that the geopolitical and economic expansion came with great costs, such as the slave trade. A simple two-word phrase can carry strong contestations, and entire research fields, such as post-colonial studies, are devoted to them. However, these sometimes subtle (and sometimes not so subtle) differences in voice are as yet not often represented well in AI systems.
In this talk, I will discuss how the Cultural AI Lab is working towards creating AI systems that are implicitly or explicitly aware of the subtle and subjective complexity of human culture. I will highlight the different research strands and activities that look at AI from different angles as well as how we engage with our user communities to create synergies between the technology and the daily practice of cultural heritage professionals.
The Human in Digital Humanities
Online Symposium, Tilburg School of Humanities & Digital Sciences
Tilburg University
https://www.digitalhumanitiestilburg.com/
Marieke van Erp & Victor de Boer (2021, June). A Polyvocal and Contextualised Semantic Web. In European Semantic Web Conference (pp. 506-512). Springer, Cham.
Presented on 8 June, 2021
Computationally Tracing Concepts Through Time and SpaceMarieke van Erp
Slides for HNR2020 Keynote presentation
Abstract:
Digitised sources are a treasure trove for scholars, but accessing the information contained in them is far from trivial. Due to scale, traditional methods are insufficient to analyse the big data coming from these sources. Hence, computational methods look to be the solution. Indeed, computational methods can be utilised to identify and model concepts in large digital datasets, however the nature of these datasets as well as that of humanities research questions requires caution. In particular, the ramifications of time and location on understanding concepts cannot be underestimated.
In this talk, Marieke will present ongoing work on computationally tracing concepts through time and across geography using language and semantic web technology. The work illustrates that seemingly simple concepts (e.g. sugar) prove to be much more complex than expected. We discuss the importance of semantics in helping not only to deal with this complexity but reify it so that it can be interrogated both computationally and via expert analysis.
Slides 5, 8, 11, 12, 15, 16, 17, 18, 19, 20 are based the presentation Tabea Tietz gave for the paper "Challenges of Knowledge Graph Evolution from an NLP Perspective" in the WHiSe Workshop @ ESWC 2020 (2 June 2020).
http://hnr2020.historicalnetworkresearch.org/
The Hitchhiker's Guide to the Future of Digital HumanitiesMarieke van Erp
Slides of my DHOxSS closing lecture
Oxford, 26 July 2019
Abstract
In the constellation of research fields, new configurations are continuously reshaping our ideas of what a field should be. This is particularly the case in the young field of digital humanities which, as David M. Berry noted, started with a focus on improving access to digital repositories and then moved to expanding the limits of archives to include born-digital materials as research objects. Both moves greatly impacted our research practice. However, I argue that we have only started scratching the surface of what digital methods can mean for humanities research.
In particular, as our methods and collaborations with other fields have matured, we can now start imagining new types of research questions that go beyond the sum of their ‘digital’ and ‘humanities’ parts -- to fundamentally change the nature of the humanities questions that we can ask. For such a reshaping to occur, we need to deepen the connection to our academic neighbours and keep looking beyond our own research community in order to ask these new questions. In my talk, I will present how multi-disciplinary collaborations between historians, linguists, and computer scientists can bring about new insights that may form the first steps to this future.
Why language technology can’t handle Game of Thrones (yet)Marieke van Erp
Natural language processing (NLP) tools are commonly used in many day-to-day applications such as Siri and Google, but the effectiveness of these technologies is not thoroughly understood. I will present joint work with colleagues from the Vrij Universiteit Amsterdam in which we perform a thorough evaluation of four different name recognition tools on 40 popular novels (including A Game of Thrones). I will highlight why literary texts are so difficult for NLP tools as well as solutions for improving their performance.
Finding common ground between text, maps, and tables for quantitative and qua...Marieke van Erp
Invited talk given at 8th AIUCD Conference 2019 – ‘Pedagogy, teaching, and research in the age of Digital Humanities’
http://aiucd2019.uniud.it/
24 January 2019, Udine, Italy
Slicing and Dicing a Newspaper Corpus for Historical Ecology ResearchMarieke van Erp
Presented at EKAW 2018
Historical newspapers are a novel source of information for historical ecologists to study the interactions between humans and animals through time and space. Newspaper archives are particularly interesting to analyse because of their breadth and depth. However, the size and the occasional noisiness of such archives also brings difficulties, as manual analysis is impossible. In this paper, we present experiments and results on automatic query expansion and categorisation for the perception of animal species between 1800 and 1940. For query expansion and to the manual annotation process, we used lexicons. For the categorisation we trained a Support Vector Machine model. Our results indicate that we can distinguish newspaper articles that are about animal species from those that are not with an F 1 of 0.92 and the subcategorisation of the different types of newspapers on animals up to 0.84 F 1 .
Lessons Learnt from the Named Entity rEcognition and Linking (NEEL) Challenge...Marieke van Erp
Giuseppe Rizzo, Biana Pereira, Andra Varga, Marieke van Erp, Amparo Elizabeth Cano Basave
Presented on Wednesday 10 October at the 17th International Semantic Web Conference (ISWC 2018)
Paper: http://www.semantic-web-journal.net/content/lessons-learnt-named-entity-recognition-and-linking-neel-challenge-series
Conference: http://iswc2018.semanticweb.org/
Russian Standard Vodka - Advertising Research, Proposal, Media Plan, Sample C...Jaddan Bruhn
Advertising proposal, including research, promotional strategy, media plan, sample creative and evaluation metrics for Russian Standard Vodka 300ml ready to drink (premixed) product.
Towards Culturally Aware AI Systems - TSDH SymposiumMarieke van Erp
Towards Culturally Aware AI Systems
Presented 23 June 2021
Slide credits: Cultural AI team members Andrei Nesterov, Laura Hollink, Ryan Brate, Valentin Vogelmann + input and inspiration from all Cultural AI Colleagues
Biases in data can be both explicit and implicit. Explicitly, ‘The Dutch Seventeenth Century’ and ‘The Dutch Golden Age’ are pseudo-synonymous and refer to a particular era of Dutch history. Implicitly, the ‘Golden Age’ moniker is contested due to the fact that the geopolitical and economic expansion came with great costs, such as the slave trade. A simple two-word phrase can carry strong contestations, and entire research fields, such as post-colonial studies, are devoted to them. However, these sometimes subtle (and sometimes not so subtle) differences in voice are as yet not often represented well in AI systems.
In this talk, I will discuss how the Cultural AI Lab is working towards creating AI systems that are implicitly or explicitly aware of the subtle and subjective complexity of human culture. I will highlight the different research strands and activities that look at AI from different angles as well as how we engage with our user communities to create synergies between the technology and the daily practice of cultural heritage professionals.
The Human in Digital Humanities
Online Symposium, Tilburg School of Humanities & Digital Sciences
Tilburg University
https://www.digitalhumanitiestilburg.com/
Marieke van Erp & Victor de Boer (2021, June). A Polyvocal and Contextualised Semantic Web. In European Semantic Web Conference (pp. 506-512). Springer, Cham.
Presented on 8 June, 2021
Computationally Tracing Concepts Through Time and SpaceMarieke van Erp
Slides for HNR2020 Keynote presentation
Abstract:
Digitised sources are a treasure trove for scholars, but accessing the information contained in them is far from trivial. Due to scale, traditional methods are insufficient to analyse the big data coming from these sources. Hence, computational methods look to be the solution. Indeed, computational methods can be utilised to identify and model concepts in large digital datasets, however the nature of these datasets as well as that of humanities research questions requires caution. In particular, the ramifications of time and location on understanding concepts cannot be underestimated.
In this talk, Marieke will present ongoing work on computationally tracing concepts through time and across geography using language and semantic web technology. The work illustrates that seemingly simple concepts (e.g. sugar) prove to be much more complex than expected. We discuss the importance of semantics in helping not only to deal with this complexity but reify it so that it can be interrogated both computationally and via expert analysis.
Slides 5, 8, 11, 12, 15, 16, 17, 18, 19, 20 are based the presentation Tabea Tietz gave for the paper "Challenges of Knowledge Graph Evolution from an NLP Perspective" in the WHiSe Workshop @ ESWC 2020 (2 June 2020).
http://hnr2020.historicalnetworkresearch.org/
The Hitchhiker's Guide to the Future of Digital HumanitiesMarieke van Erp
Slides of my DHOxSS closing lecture
Oxford, 26 July 2019
Abstract
In the constellation of research fields, new configurations are continuously reshaping our ideas of what a field should be. This is particularly the case in the young field of digital humanities which, as David M. Berry noted, started with a focus on improving access to digital repositories and then moved to expanding the limits of archives to include born-digital materials as research objects. Both moves greatly impacted our research practice. However, I argue that we have only started scratching the surface of what digital methods can mean for humanities research.
In particular, as our methods and collaborations with other fields have matured, we can now start imagining new types of research questions that go beyond the sum of their ‘digital’ and ‘humanities’ parts -- to fundamentally change the nature of the humanities questions that we can ask. For such a reshaping to occur, we need to deepen the connection to our academic neighbours and keep looking beyond our own research community in order to ask these new questions. In my talk, I will present how multi-disciplinary collaborations between historians, linguists, and computer scientists can bring about new insights that may form the first steps to this future.
Why language technology can’t handle Game of Thrones (yet)Marieke van Erp
Natural language processing (NLP) tools are commonly used in many day-to-day applications such as Siri and Google, but the effectiveness of these technologies is not thoroughly understood. I will present joint work with colleagues from the Vrij Universiteit Amsterdam in which we perform a thorough evaluation of four different name recognition tools on 40 popular novels (including A Game of Thrones). I will highlight why literary texts are so difficult for NLP tools as well as solutions for improving their performance.
Finding common ground between text, maps, and tables for quantitative and qua...Marieke van Erp
Invited talk given at 8th AIUCD Conference 2019 – ‘Pedagogy, teaching, and research in the age of Digital Humanities’
http://aiucd2019.uniud.it/
24 January 2019, Udine, Italy
Slicing and Dicing a Newspaper Corpus for Historical Ecology ResearchMarieke van Erp
Presented at EKAW 2018
Historical newspapers are a novel source of information for historical ecologists to study the interactions between humans and animals through time and space. Newspaper archives are particularly interesting to analyse because of their breadth and depth. However, the size and the occasional noisiness of such archives also brings difficulties, as manual analysis is impossible. In this paper, we present experiments and results on automatic query expansion and categorisation for the perception of animal species between 1800 and 1940. For query expansion and to the manual annotation process, we used lexicons. For the categorisation we trained a Support Vector Machine model. Our results indicate that we can distinguish newspaper articles that are about animal species from those that are not with an F 1 of 0.92 and the subcategorisation of the different types of newspapers on animals up to 0.84 F 1 .
Lessons Learnt from the Named Entity rEcognition and Linking (NEEL) Challenge...Marieke van Erp
Giuseppe Rizzo, Biana Pereira, Andra Varga, Marieke van Erp, Amparo Elizabeth Cano Basave
Presented on Wednesday 10 October at the 17th International Semantic Web Conference (ISWC 2018)
Paper: http://www.semantic-web-journal.net/content/lessons-learnt-named-entity-recognition-and-linking-neel-challenge-series
Conference: http://iswc2018.semanticweb.org/
Entity Typing Using Distributional Semantics and DBpedia Marieke van Erp
Presentation given at NLP&DBpedia workshop on 18 October 2016. The presentation accompanies the work described in: https://nlpdbpedia2016.files.wordpress.com/2016/09/nlpdbpedia2016_paper_9.pdf
The domain as unifier, how focusing on social history can bring technical fie...Marieke van Erp
Invited talk given at the final CEDAR symposium about the interaction between (social) history, language technology, and semantic web.
https://socialhistory.org/en/events/final-cedar-mini-symposium
Evaluating entity linking an analysis of current benchmark datasets and a ro...Marieke van Erp
Marieke van Erp, Pablo Mendes, Heiko Paulheim, Filip Ilievski, Julien Plu, Giuseppe Rizzo and Joerg Waitelonis
Presented at LREC 2016:
http://www.lrec-conf.org/proceedings/lrec2016/pdf/926_Paper.pdf
Finding Stories in 1,784,532 Events: Scaling up computational models of narr...Marieke van Erp
Slides of the NewsReader Computational Models of Narrative Presentation "Finding Stories in 1,784,532 Events: Scaling Up Computational Models of Narrative - Marieke van Erp, Antske Fokkens, and Piek Vossen"
Workshop page: http://narrative.csail.mit.edu/cmn14/
Project page: http://www.newsreader-project.eu
2. OVERVIEW
Research Proposal
Finding your topic
Defining your research question
Writing it up
Research Poster: Communicating your idea visually
Peer Review: Providing positive feedback
Lightning Talk: Condense your idea
Logistics
Friday, November 30, 12
4. FINDING YOUR TOPIC
Which topics in the course did you like?
Which problem should be solved?
Think out of the box, what have you seen in the
literature in other lectures that may be of use here?
Sleep on it.
Am I still excited about it? OK, go to step 2
Friday, November 30, 12
8. DEFINING YOUR RQ
Dig into the literature, has my problem been
researched before?
If so, what techniques have been used to deal with
it?
Is my proposed solution novel and viable?
No literature? Ask yourself if the problem you want
to investigate is relevant.
Friday, November 30, 12
9. WRITING IT UP
Make sure the proposal is self-contained, i.e., any
peer reviewer should understand your main problem
and proposed solution by just reading your
document
Use examples, or figures to explain your proposal
Don’t forget any parts (literature etc.)
Friday, November 30, 12
11. VISUALISING YOUR IDEA
A picture says more than a thousand words
Come up with a catchy example
Don’t paste text from your proposal into your poster!
Friday, November 30, 12
12. Knowledge & Media Conference 2011
December 12th VU University Amsterdam
Juicing the LOD Cloud with WordNet
Use WordNet to Though at first glance it may seem as if there
are many connections between data sources
Use a validation metric
suggest new links in the LOD Cloud, a more detailed look will
show that most data sources are connected
to determine the
in the LOD Cloud to only one or two other data sources. This
also follows from the LOD Cloud statistics. relevance of new links
More than 50% of the data sources in the
LOD Cloud link to no more than two other
sources, and more than 66% of them link to
no more than three other sources.
Derive identifying terms
Use WordNet as a semantic and relational
from existing RDF Triples
knowledge base to analyze the subjects,
predicates and objects of existing triples in
▼
the LOD Cloud and propose new links
between data items based on the linguistic Match these terms
The number of data sets that link to 1, 2, 3, 4, 5, 6 to 10 or
more than 10 other data sets
relations defined in WordNet. Nouns, verbs,
adjectives and adverbs are grouped into sets
against synsets in
of cognitive synonyms called synsets, each
expressing a distinct concept. Synsets are
WordNet
interlinked by means of conceptual-semantic
and lexical relations.
▼
Use synonymy hyponymy
WordNet contains 3 major relation types and meronymy relations
that could be utilized: Synonymy relations;
relations between words that have similar ▼
meaning, e.g. ‘forest’ is synonymous to
‘wood’. Hyponymy relations; relations Suggest links based on
between words that are sub concepts or
super concepts of each other, e.g. ‘taxi’ is a distance in the linguistic
sub concept of ‘car’, which in turn is a sub
concept of ‘vehicle’. Meronymy relations; WordNet relation and
relations that define if words are sub
concepts, e.g. ‘bumper’ is a part of ‘car’. matching percentage
▼
Use a filter for
domain specific
applications
Ben A. Student
VU University Amsterdam
Friday, November 30, 12 b.a.student@vu.nl
14. PROVIDING POSITIVE
FEEDBACK
Meant to help each other in improving the proposal
Read critically, but fairly
Provide detailed as well as high level comments to
aid the author whose work you are reviewing
Friday, November 30, 12
16. CONDENSING YOUR IDEA
Explain the core of your idea in one minute
Don’t try to summarise your entire proposal
Create a single slide to communicate your idea
Friday, November 30, 12
17. Try-on eyewear
Serious gaming for opticians
Friday, November 30, 12
18. MusicWees
by Justin van
discovery and recommendations using the Semantic Web
Problem statement Research question
• Enormous collections of music are available Can we create a system that generates personalized music
online recommendations by using Semantic Web technologies and
• To find new, possibly interseting music, currently available Linked Open Data?
users can:
We wan to:
- Read reviews
• help users discover new music that
- Listen to lots of tracks
fits personal taste
- ... or use colleborative filtering services 20+ • combine collaborative filtering data,
like: million songs
expert-based data and high-level
content based features
• provide meaningful feedback on
Text why items are suggested (Cohen
and Fan, 2000)
• intergrate with a (popular) existing
Colleborative filtering methods have service
several disadvantages:
• compares on (very few) high level Methods
metadeta properties • collect music related linked data and map it to the
• content-based properties are Music Ontology (Raimond et al., 2007)
ignored • build and evaluate recommendation methods
• prone to a popularity bias; makes • determine what information on recommendations is useful to
it unlikely for artists located in the the end-user
‘Long Tail’ to be ever recommend References
• recommendations are not Casey, M., Veltkamp, R., Goto, M., Leman, M., Rhodes, C., and Slaney, M. (2008). Content-based music information retrieval: current direc-
tions and future challenges. Proceedings of the IEEE, 96(4):668–696.
Celma, O. and Cano, P. (2008). From hits to niches?: or how popular artists can bias music recommendation and discovery. In Proceedings
transparent of the 2nd KDD Workshop on Large-Scale Recommender Systems and the Netflix Prize Competition, page 5. ACM.
Cohen, W. and Fan, W. (2000). Web-collaborative filtering: Recommending music by crawling the web. Computer Networks, 33(1):685–
The Top–737 artists accumulate 50% of total
698.
playcounts (Celma and Cano, 2008). Raimond, Y., Abdallah, S., Sandler, M., and Giasson, F. (2007). The music ontology. In Proceedings of the International Conference on Music
Information Retrieval, pages 417– 422. Citeseer.
http://en.wikipedia.org/wiki/ITunes_Store#Music, http://en.wikipedia.org/wiki/Spotify
http://dbtune.org/
Friday, November 30, 12
19. Crowdsourcing for documentation and
revitalization of endangered languages
Language embeds knowledge…
documenting
sharing
in the hands of the crowd
Friday, November 30, 12
23. LIGHTNING TALK SLIDE
Submit a PDF file with one single slide to the
dropbox, named <LASTNAME>_slide.pdf
Deadline: Friday 7 December 23:59 CET.
Make sure the slide is in landscape mode and has at
dimensions 1024x768 or greater with same
proportions
Friday, November 30, 12
24. FINAL VERSION
Process reviewers’ comments and lightning talk
comments
Explain your improvements in a response letter
Deadline: Sunday 23 December 23:59 CET
Resubmit using Easychair
Friday, November 30, 12