Corrected bibtex paste

getcomputo-pub.fsx

@@ -76,7 +76,7 @@ type RepoError =
 
 let redirectStringRe = Regex(@"URL='(.*)'")
 
-let getAbstract (page: string) =
+let getBibTeX (page: string) =
 
     let htmlFirst = HtmlDocument.Load(page)
 
@@ -100,16 +100,29 @@ let getAbstract (page: string) =
     try
         html.CssSelect(".bibtex").Head.InnerText()
         |> DirtyParser.bibTeXFromString
-        |> _.Head.Properties["abstract"]
+        |> _.Head
         |> Result.Ok
     with e ->
-        printfn "Error getting abstract from %s: %s" page e.Message
+        printfn "Error getting BibTeX from %s: %s" page e.Message
         Result.Error e.Message
 
+let getAbstract (entry: BibTeXEntry) = entry.Properties["abstract"]
+
+let getBibTeXFromDict (d: Dictionary<obj, obj>) =
+    d["repoObj"] :?> Repository
+    |> _.Homepage
+    |> getBibTeX
+    |> function
+        | Ok a -> DrBiber.DirtyParser.bibTeXToString [ a ]
+        | Error e ->
+            printfn "Error getting BibTeX from %s: %s" (d["repoObj"] :?> Repository).Name e
+            ""
+
 let getAbstractFromDict (d: Dictionary<obj, obj>) =
     d["repoObj"] :?> Repository
     |> _.Homepage
-    |> getAbstract
+    |> getBibTeX
+    |> Result.map (fun bibTeX -> getAbstract bibTeX)
     |> function
         | Ok a -> a
         | Error e ->
@@ -159,6 +172,7 @@ let extractCitation (d: Dictionary<obj, obj>) =
        description = d |> getSomeString "description"
        abstract' = d |> getAbstractFromDict
        repo = d |> getSomeString "repo"
+       bibtex = d |> getBibTeXFromDict
        pdf = d |> getAnotherThing "citation" |> getSomeString "pdf-url"
        url = d |> getAnotherThing "citation" |> getSomeString "url"
        draft = d |> getSomeString "draft" |}

site/mock-papers.yml

@@ -20,6 +20,39 @@
         t-SNE are significantly better than those produced by other
         techniques on almost all of the data sets.
   authors: Laurens van der Maaten and Geoffrey Hinton
+  bibtex: >+
+    @article{van_der_maaten2008,
+    	author = {van der Maaten, Laurens and Hinton, Geoffrey},
+    	publisher = {Société Française de Statistique},
+    	title = {Visualizing {Data} Using {t-SNE:} A Practical Computo Example
+        (Mock)},
+    	journal = {Computo},
+    	date = {2008-08-11},
+    	url = {https://computo.sfds.asso.fr/published-paper-tsne},
+    	issn = {2824-7795},
+    	langid = {en},
+    	abstract = {We present a new technique called “t-SNE” that visualizes
+        high-dimensional data by giving each datapoint a location in a two
+        or three-dimensional map. The technique is a variation of Stochastic
+        Neighbor Embedding {[}@hinton:stochastic{]} that is much easier to
+        optimize, and produces significantly better visualizations by
+        reducing the tendency to crowd points together in the center of the
+        map. t-SNE is better than existing techniques at creating a single
+        map that reveals structure at many different scales. This is
+        particularly important for high-dimensional data that lie on several
+        different, but related, low-dimensional manifolds, such as images of
+        objects from multiple classes seen from multiple viewpoints. For
+        visualizing the structure of very large data sets, we show how t-SNE
+        can use random walks on neighborhood graphs to allow the implicit
+        structure of all the data to influence the way in which a subset of
+        the data is displayed. We illustrate the performance of t-SNE on a
+        wide variety of data sets and compare it with many other
+        non-parametric visualization techniques, including Sammon mapping,
+        Isomap, and Locally Linear Embedding. The visualization produced by
+        t-SNE are significantly better than those produced by other
+        techniques on almost all of the data sets.}
+    }
+
   date: 2008-08-11
   description: >
     This page is a reworking of the original t-SNE article using the Computo template. It aims to help authors submitting to the journal by using some advanced formatting features. We warmly thank the authors of t-SNE and the editor of JMLR for allowing us to use their work to illustrate the Computo spirit.
@@ -29,7 +62,7 @@
   pdf: ''
   repo: published-paper-tsne
   title: Visualizing Data using t-SNE (mock contributon)
-  url: https://computo.sfds.asso.fr/published-paper-tsne
+  url: https://computo-journal.org/published-paper-tsne
   year: 2008
 - abstract': >-
     We present a new technique called “t-SNE” that visualizes
@@ -53,6 +86,39 @@
         t-SNE are significantly better than those produced by other
         techniques on almost all of the data sets.
   authors: Laurens van der Maaten and Geoffrey Hinton
+  bibtex: >+
+    @article{van_der_maaten2008,
+    	author = {van der Maaten, Laurens and Hinton, Geoffrey},
+    	publisher = {French Statistical Society},
+    	title = {Visualizing {Data} Using {t-SNE:} A Practical {Computo}
+        Example (Mock)},
+    	journal = {Computo},
+    	date = {2008-08-11},
+    	url = {https://computo-journal.org/published-paper-tsne-R},
+    	issn = {2824-7795},
+    	langid = {en},
+    	abstract = {We present a new technique called “t-SNE” that visualizes
+        high-dimensional data by giving each datapoint a location in a two
+        or three-dimensional map. The technique is a variation of Stochastic
+        Neighbor Embeddi{[}@hinton:stochastic{]} that is much easier to
+        optimize, and produces significantly better visualizations by
+        reducing the tendency to crowd points together in the center of the
+        map. t-SNE is better than existing techniques at creating a single
+        map that reveals structure at many different scales. This is
+        particularly important for high-dimensional data that lie on several
+        different, but related, low-dimensional manifolds, such as images of
+        objects from multiple classes seen from multiple viewpoints. For
+        visualizing the structure of very large data sets, we show how t-SNE
+        can use random walks on neighborhood graphs to allow the implicit
+        structure of all the data to influence the way in which a subset of
+        the data is displayed. We illustrate the performance of t-SNE on a
+        wide variety of data sets and compare it with many other
+        non-parametric visualization techniques, including Sammon mapping,
+        Isomap, and Locally Linear Embedding. The visualization produced by
+        t-SNE are significantly better than those produced by other
+        techniques on almost all of the data sets.}
+    }
+
   date: 2008-08-11
   description: >
     This page is a reworking of the original t-SNE article using the Computo template. It aims to help authors submitting to the journal by using some advanced formatting features. We warmly thank the authors of t-SNE and the editor of JMLR for allowing us to use their work to illustrate the Computo spirit.
@@ -62,5 +128,5 @@
   pdf: ''
   repo: published-paper-tsne-R
   title: Visualizing Data using t-SNE (mock contributon)
-  url: https://computo.sfds.asso.fr/published-paper-tsne-R
+  url: https://computo-journal.org/published-paper-tsne-R
   year: 2008

site/publications.ejs

@@ -10,6 +10,7 @@ for (const item of items) {
   let doiurl = item.url === "" ? "https://doi.org/" + item.doi : item.url;
   let bibtitle = item.title.replace(/'/g, "\\'");
   let bibauthors = item.authors.replace(/'/g, "\\'");
+  let bibtex = item.bibtex.replace(/'/g, "\\'").replace(/\"/g, '"').replace(/\r?\n/g, "\\n");
   if (item.year !== currentYear) {
     if (currentYear !== null) { %>
 </div> <!-- End previous year section -->
@@ -52,7 +53,7 @@ for (const item of items) {
                   <a href="<%= item.pdf %>" class="btn btn-outline-secondary btn-sm" target="_blank" style="padding:0.2em 0.6em;">PDF</a>
                   <% } %> -->
                   <a href="https://github.com/computorg/<%- item.repo %>" class="btn btn-outline-secondary btn-sm" target="_blank" style="padding:0.2em 0.6em;">Sources (Git)</a>
-                  <button type="button" class="btn btn-outline-secondary btn-sm" onclick="generateBibTex('<%- bibtitle %>', '<%- bibauthors %>', '<%= item.year %>', '<%= doiurl %>')" style="padding:0.2em 0.6em;"><span style="font-variant: small-caps; font-family: 'Times New Roman', Times, serif;">Bib<span style="vertical-align: -0.2em;">T</span><span style="vertical-align: 0em;">E</span>X</span></button>
+                  <button type="button" class="btn btn-outline-secondary btn-sm" onclick="generateBibTex('<%= bibtex %>')" style="padding:0.2em 0.6em;"><span style="font-variant: small-caps; font-family: 'Times New Roman', Times, serif;">Bib<span style="vertical-align: -0.2em;">T</span><span style="vertical-align: 0em;">E</span>X</span></button>
                 </div>
               </div>
             </div>
@@ -124,19 +125,7 @@ for (const item of items) {
     $('#abstractContent').text(abstract);
   });
 
-  function generateBibTex(title, authors, year, url) {
-    // Generate a simple BibTeX key from the first author's last name and year
-    var firstAuthor = authors.split(' and ')[0].split(' ').pop().toLowerCase();
-    var bibKey = firstAuthor + year;
-
-    var bibTeX = '@article{' + bibKey + ',\n' +
-      '  title={' + title + '},\n' +
-      '  author={' + authors + '},\n' +
-      '  journal={Computo},\n' +
-      '  year={' + year + '},\n' +
-      '  url={' + url + '}\n' +
-      '}';
-
+  function generateBibTex(bibTeX) {
     // Create a temporary textarea to copy the BibTeX to clipboard
     var textArea = document.createElement('textarea');
     textArea.value = bibTeX;