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--- project:diplomatic_documents_and_swiss_newspapers_in_1914 [2015/02/28 15:12] – [Diplomatic Documents and Swiss Newspapers in 1914] giovanni
+++ project:diplomatic_documents_and_swiss_newspapers_in_1914 [2015/03/01 15:46] (current) – [Team] giovanni
@@ Line 12: / Line 12: @@
   * [[https://www.dropbox.com/s/pyuuuv2ms7ushua/data.zip?dl=0|Data.zip (CC BY 4.0)]] (DropBox)
   * [[https://github.com/aoloe/glamhack-dodis-gdl-jdg|github]]
 ===== Documentation =====
-In this project, we want to connect newspaper articles from Journal de Genève (a Genevan daily newspaper) and a sample of the Diplomatic Documents in Switzerland database (Dodis). The goal is to conduct requests in the Dodis descriptive metadata to look for what appears in a given interval of time in the press by comparing occurrences from both data sets. Thus, we should be able to examine if and how the written press reflected what was happening at the diplomatic level. The time interval for this project is the summer of 1914.
+In this project, we want to connect newspaper articles from Journal de Genève (a Genevan daily newspaper) and the Gazette de Lausanne to a sample of the Diplomatic Documents in Switzerland database (Dodis). The goal is to conduct requests in the Dodis descriptive metadata to look for what appears in a given interval of time in the press by comparing occurrences from both data sets. Thus, we should be able to examine if and how the written press reflected what was happening at the diplomatic level. The time interval for this project is the summer of 1914.
-In this context, at first we cleaned the data, for example by removing noise caused by short strings of characters and stopwords. The cleansing is a huge work, the pre-processing step of journal indexing. We compared small sizes vectors of words, and paired words in the index with their occurrences. Semantic groups were thus recomposed (thesaurus).
+In this context, at first we cleaned the data, for example by removing noise caused by short strings of characters and stopwords. The cleansing is a necessary step to reduce noise in the corpus. We then compared prepared tfidf vectors of words and LSI topics and represented each article in the corpus as such. Finally, we indexed the whole corpus of Le Temps to prepare it for similarity queries. THe last step was to build an interface to search the corpus by entering a text (e.g., a Dodis summary).
+Difficulties were not only technical. For example, the data are massive: we started doing this work on fifteen days, then on three months. Moreover, some Dodis documents were classified (i.e. non public) at the time, therefore some of the decisions don't appear in the newspapers articles. We also used the [[http://textometrie.ens-lyon.fr/?lang=en|TXM software]], a platform for lexicometry and text statistical analysis, to explore both text corpora (the DODIS metadata and the newspapers) and to detect frequencies of significant words and their presence in both corpora.
+===== Dodis Map =====
+{{:project:project:dodis_map.png?400|}}
+  * [[http://t.preus.se/dodis-map/#/|demo]]
+  * [[https://github.com/tpreusse/dodis-map/tree/master|github]]
-Difficulties were not only technical. For example, the data are massive : we started doing this work on fifteen days, then on three months. Moreover, some documents were classified at the time, therefore some of the decisions don't appear in the newspapers articles.
 ===== Team =====
@@ Line 28: / Line 36: @@
   * [[http://t.preus.se/|Thomas Preusse]]
   * [[http://ideale.ch/|Ale Rimoldi]]
-  * [[user:yrochat|Yannick Rochat]]
+  * [[http://people.epfl.ch/yannick.rochat?lang=fr|Yannick Rochat]]
-{{:project:20150228_115443.jpg?300|}}
-===== Links =====
-  * Blog or forum posts ...
+{{tag> glam}}
-  * Tools you used ...
-{{tag>status:concept needs:dev needs:design needs:data needs:expert}}