Inria Saclay, batiment Alan Turing	Data Science for Document Analysis and Understanding Part 2 INRIA (French Institute for Research in Computer Science and Automation) (Institut national de recherche en informatique et en automatique) Saclay, France July 15 - July 26, 2019	Cit�é internationale universitaire de Paris (CIUP)

---

Summary

This is the second part of the summer school that takes over from Part 1 in La Rochelle. We aim to teach the fundamental concepts and important developments in data science and natural language processing. The target audience are students having completed advanced classwork in mathematics, statistics, or computer science.

---

Organizing Institution

Inria, the French National Institute for computer science and applied mathematics, promotes scientific excellence for technology transfer and society. Graduates from the world's top universities, Inria's 2,600 employees rise to the challenges of digital sciences. Research at Inria is organised in �³project teams�´ which bring together researchers with complementary skills to focus on specific scientific projects. With this open, agile model, Inria is able to explore original approaches with its partners in industry and academia and provide an efficient response to the multidisciplinary and application challenges of the digital transformation. The source of many innovations that add value and create jobs, Inria transfers expertise and research results to companies (startups, SMEs and major groups) in fields as diverse as healthcare, transport, energy, communications, security and privacy protection, smart cities and the factory of the future.

---

Lecturers

Zoltan Szabo(CMAP Ecole Polytechnique, France)

Balazs Pinter (E�ötv�ös Lor�ánd University, Hungary)

Jing-Rebecca Li (INRIA-Saclay, CMAP Ecole Polytechnique, France)

Raphaële Miljkovitch (Laboratoire Paragraphe Université Paris 8, France)

---

Current schedule

Download current schedule here

Important information

Download important information here

---

Scientific program

Week 1

Data Science (Linear algebra, optimization, applications, kernels, classification, kernel PCA/CCA, dependency measures/distances, hypothesis testing, acceleration schemes.)

Natural Language Processing (NLP) (Foundations of NLP: corpora, tokenization, stemming, term vector representations, POS tagging, parsing, language models, stopwords, text classification and clustering, dialogue systems. Deep learning in NLP: recurrent neural networks, LSTM, word vector representations, end-to-end dialogue systems.)

Week 2

Professional advising (CV, motivation letter, PhD scholarship application)

Presentation on graduate studies in France

A list of links to Master's and PhD programs

Download and install

Python:Anaconda scientific package

Download class material.

Python Jupyter Notebooks

Practical Project: Text processing for psychological interviews of attachment.

AMMI-Project (the Attachment Multiple Model Interview, transcripts in French)

The folder "Transcripts_scores" contains the transcripts and their scores.


There are two studies (I labelled them "AMMI-ASSI" and "AMMI-Lausanne").
For one study, the scores are in an Excel file, in the other study, the scores are in separate .docx files

In the Excel file, the headings corresponds to the scores in the .docx files in the following way.
ID = the transcript number,CATASSSI = ?, SEXE = (1 = female, 2 = male), AGET3 = ?;
ASSSECM = Security (Mother), ASSINHM = Inhibition (Mother), ASSHYPM = Hyperactivation (Mother);
ASSSECP = Security (Father), ASSINHP = Inhibition (Father), ASSHYPP = Hyperactivation (Father);
ASSSECDC = Security (Romantic Partner), ASSINHDC = Inhibition (Romantic Partner), ASSHYPDC = Hyperactivation(Romantic Partner);
AMMIDM = Disorganization (Mother), AMMIDP = Disorganization (Father), AMMIDC = Disorganization (Romantic Partner);


The folder "Transcripts_original" contains the original .doc and .docx formatted files of the two studies.
The folder "Transcripts_text" are the files converted to text format.


The gender of the interviewee is on the top of each interview (in .doc and .docx format).
"Homme" or "H" means male, "Femme" or "F" means female.

The age of the interviewee is on the top of some of the interviews (the ones whose file name starts with "AMMI").
The age is number followed by "ans". For, example, "H 63 ans" means "male, 63 years old".


A simple Jupyter notebook file "Process_transcripts_clean" to get you started.

The folder "AAI-Project-English" has some of the old files from last year's project where all the transcripts are in English. This is given just for reference.

TO DO.

A. Save all the interviews into a data structure that contains the transcripts, the gender of the interviewee, the age of the interviewee (the age is available only for one study, not the other study), and the scores of the transcripts. The scores are for each relationship (Mother, Father, and Romantic Partner). Each relationship has 4 numerical scores: Sécurité, Inhibition, Hyperactivation, and Désorganisation, each ranging between 0 and 10.

B. The transcripts consist of alternating interviewer questions and interviewee answers. Call each interviewee answer an "utterance". Label by hand several transcripts in the following way. In each transcript,

Label each interviewer question as 1) a general question, 2) a question about Mother, 3) a question about Father, 4) a question about Romantic Partner;
Label each interviewee "utterance" as either 1) a general statement, or about 2) Mother, 3) Father, 4) Romantic Partner.
That makes 8 labels.


C. Include the labels of the interviewer questions and the interviewee "utterances" you did in B) into the data structure of all the transcripts you did in A).

---

Cultural program


Saturday July 20, 2019

Guided visit of Paris (lunch and dinner included)

July 22 - 25, 2019

French language and culture classes

---

Lodging

The students will be lodged at Cit�e internationale universitaire de Paris

17, bd Jourdan, 75014 Paris.

The house is called Fondation Deutsch de la Meurthe

---

Practical details

Location of classes:

Inria-Saclay (Building Alan Turing).

Massy-Palaiseay station is the closest station : take RER line B towards Saint-Rémy-lès-Chevreuse, getting off at Massy-Palaiseau. Walk to the front of the train and take the stairs. On the top of the stairs, walk a few steps on your left and go down the stairs on your right. Walk straight forward to the bus stop (bus 91.06, the last one). Take the bus 91.06, and get off at the "Polytechnique Laboratoire" station.

RER B schedule
Bus 91.06 schedule (summer)

Lunches will be provided.

---

Transportation

Pass Navigo (5 zones transportation card for Paris and surrounding regions) will be provided for each student

---

Included	Meeting at Paris train station. Lodging in Paris. Lunches Monday - Friday. Guided visits in Paris on July 20, 2019. 5 zones transportation card for Paris and surrounding regions. Scientific program. French language and culture classes.
Not included	Dinners (the students can use the common kitchens to cook in the lodging). Lunch on the weekends. Transportation away from lodging at the end of the program.

---

Jing-Rebecca Li

Last modified: Tue Jul 24 07:01:01 GMT 2018