blob: 873c0a78e27e105dde560783d283c464f91b4f9f [file] [log] [blame]
<!DOCTYPE html>
<html>
<head>
<% my $plain_title = $title; $plain_title=~s/<[^>]+>//g; %>
<title><%= $plain_title %>:<%= $word %> · IDS word vector analysis</title>
<link rel="stylesheet" href="//code.jquery.com/ui/1.12.1/themes/base/jquery-ui.css">
<link href="https://fonts.googleapis.com/css?family=Lato|Roboto+Condensed" rel="stylesheet">
<script src="https://code.jquery.com/jquery-latest.min.js"></script>
<script src = "https://cdn.datatables.net/1.13.10/js/jquery.dataTables.min.js"></script>
<script src = "https://cdn.datatables.net/fixedcolumns/3.2.5/js/dataTables.fixedColumns.min.js"></script>
<script src = "https://cdn.datatables.net/plug-ins/1.13.10/sorting/scientific.js"></script>
<script src='https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-MML-AM_CHTML'></script>
<script src="https://cdn.datatables.net/buttons/2.3.6/js/dataTables.buttons.min.js"></script>
<script src="https://cdn.datatables.net/buttons/2.3.6/js/buttons.print.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jszip/3.1.3/jszip.min.js"></script>
<script src="https://cdn.datatables.net/buttons/2.3.6/js/buttons.html5.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/ical.js/1.5.0/ical.js"
integrity="sha512-UxWd2RMDGpYwYuDeU2Fs+nd51gw4ZLQY0D9wWZ3NuanNSk6QQmWCZ6C+rvI0lJ/b/nZtBQ8RVESA9DN9r65dUg=="
crossorigin="anonymous" referrerpolicy="no-referrer"></script>
<script
src="https://cdnjs.cloudflare.com/ajax/libs/moment.js/2.29.4/moment-with-locales.min.js"
integrity="sha512-42PE0rd+wZ2hNXftlM78BSehIGzezNeQuzihiBCvUEB3CVxHvsShF86wBWwQORNxNINlBPuq7rG4WWhNiTVHFg=="
crossorigin="anonymous" referrerpolicy="no-referrer"></script>
<link rel="stylesheet" href="https://cdn.datatables.net/1.13.10/css/jquery.dataTables.min.css">
<link rel="stylesheet" href="/derekovecs/css/derekovecs.css">
<script
src="https://code.jquery.com/ui/1.12.1/jquery-ui.min.js"
integrity="sha256-VazP97ZCwtekAsvgPBSUwPFKdrwD3unUfSGVYrahUqU="
crossorigin="anonymous"></script>
<script>
MathJax.Hub.Config({
config: ["MMLorHTML.js"],
jax: ["input/TeX","input/MathML","output/HTML-CSS","output/NativeMML", "output/PreviewHTML"],
extensions: ["tex2jax.js","mml2jax.js","MathMenu.js","MathZoom.js", "fast-preview.js", "AssistiveMML.js", "a11y/accessibility-menu.js"],
TeX: {
extensions: ["AMSmath.js","AMSsymbols.js","noErrors.js","noUndefined.js"]
}
});
var urlParams = new URLSearchParams(window.location.search);
var currentWords = urlParams.get("word");
var CIIsearchWords = (currentWords && (currentWords.includes(" ") || currentWords.includes("|")) ? '('+currentWords.replace(/[ |]+/g, " oder ")+')' : currentWords);
var collocatorTable = null;
var plainTitle ="<%= $plain_title %>"
var korapPath="/";
if (plainTitle.match(/-en/)) {
korapPath="/instance/english";
}
var korapVC="";
if (plainTitle.match(/WUDD/i)) {
korapVC="&collection=corpusSigle+%3D+%2FW%5BDU%5DD17%2F";
korapPath="/instance/test";
}
$(document).ready(function() {
insertCalendarEvents(document.getElementById('downtimes'), '/derekovecs/getDowntimeCalendar' );
$('#firstable').hide();
//Set up a callback to hear back when MathJax is done rendering the equations
// it finds
$('#ccd').load(
'@Url.Action("ActionResultMethod","ControllerName",{controller parameters})',
function () {
MathJax.Hub.Queue(
["Typeset",MathJax.Hub,"ccd"],
function () {
$("#mi_tt").attr("title",$("#pmi_ttt").html());
$("#lfmd_tt").attr("title",$("#lfmd_ttt").html());
$("#md_tt").attr("title",$("#md_ttt").html());
$("#npmi_tt").attr("title",$("#npmi_ttt").html());
$("#ll_tt").attr("title",$("#ll_ttt").html());
$("#logdice_tt").attr("title",$("#logdice_ttt").html());
$("#logdiceaf_tt").attr("title",$("#logdiceaf_ttt").html());
}
);
});
//set things up so that we can shove raw html into what is shown in the tooltip;
// in this case, we will have already put into the title attribute the html that
// contains the MathJax rendered equations (via what we do in the callback).
$(function () {
$(document).tooltip({
content: function () {
return $(this).prop('title');
}
});
});
$("input").bind("keydown", function(event) {
// track enter key
var keycode = (event.keyCode ? event.keyCode : (event.which ? event.which : event.charCode));
if (keycode == 13) { // keycode for enter key
// force the 'Enter Key' to implicitly click the Update button
document.getElementById('SEARCH').click();
return false;
} else {
return true;
}});
var collocatorTable_activated = false;
$( "#tabs" ).on( "tabsactivate", function( event, ui ) {
if (localStorage) localStorage['tab'] = ui.newTab.index();
if(ui.newTab.index() == 3 && !collocatorTable_activated) {
classicCollocatorTable.columns.adjust();
collocatorTable.columns.adjust();
collocatorTable_activated = true;
}
});
$(function(){
$("#SEARCH").click(function() {
window.open($(location).attr('pathname')+'?'+$('form').serialize(), "_self");
});
});
function changeCharColor(txt, heat, word) {
var newText = "";
for (var i=0, l=txt.length; i<l; i++) {
newText += (i == 5 ? txt.charAt(i) : "<a href=\"<%= $korap_url %>" + korapPath + '/?ql=cosmas2&q=' +
CIIsearchWords + ' /' + (i > 5? '%2B' : '-') + 'w' +
Math.abs(i-5) + ':' + Math.abs(i-5) + ',s0 ' + word + korapVC +
'" target="korap"><span style="background-color:' +
getHeatColor(heat[i]/maxHeat)+'">'+txt.charAt(i)+'</span></a>');
}
return newText;
}
function getHeatColor(value) {
var hue=((1-value)*120).toString(10);
return ["hsl(",hue,",90%,70%)"].join("");
}
function bitvec2window(n, heat, word) {
var str = n.toString(2).padStart(10, "0")
.replace(/^([0-9]{5})/, '$1x')
.replace(/0/g, '·')
.replace(/1/g, '+');
return changeCharColor(str, heat, word);
}
% use Mojo::ByteStream 'b';
var paraResults = <%= b(Mojo::JSON::to_json($lists)) %>;
var urlprefix = new URLSearchParams(window.location.search);
if (paraResults.length > 0 && paraResults[0] != null) {
var nvecs = [],
nwords = [],
nranks = [],
nmarked = [];
for(var i = 0; i < paraResults.length; i++) {
nwords = nwords.concat(paraResults[i].map(function(a){return a.word;}));
nvecs = nvecs.concat(paraResults[i].map(function(a){return a.vector;}));
nranks = nranks.concat(paraResults[i].map(function(a){return a.rank;}));
nmarked = nmarked.concat(paraResults[i].map(function(a){return a.marked;}));
}
showMap({target: " "+urlParams.get('word')+" ", mergedEnd: <%= $mergedEnd %>, words: nwords, vecs: nvecs, ranks: nranks, marked: nmarked} );
var t = $('#firsttable').DataTable({
data: [].concat.apply([], paraResults),
"sScrollY": "780px",
"bScrollCollapse": true,
"bPaginate": false,
"bJQueryUI": true,
"dom": '<"top">rt<"bottom"flpB><"clear">',
buttons: [
{ extend: 'copyHtml5', text: '<i class="fa fa-files-o"></i>', titleAttr: 'Copy' },
{ extend: 'csvHtml5', text: '<i class="fa fa-file-text-o"></i>', titleAttr: 'CSV', filename: currentWords+'_para_neighbours' },
{ extend: 'excelHtml5', text: '<i class="fa fa-file-excel-o"></i>', titleAttr: 'Excel', filename: currentWords+'_para_neighbours', exportOptions: { columns: ':visible' } ,
}
],
"initComplete":function(settings, json) {
$('td.paradigmator a').on('mousedown', function(e) {
return paradigmatorClick(e, paraResults[0][0].word, this.childNodes["0"].textContent);
});
},
"columns": [
{ "data": "rank", type: "allnumeric" },
{ "data": "dist", render: function ( data, type, row ) {return data.toFixed(3) }},
{ "data": "word", class: "paradigmator", render: function ( data, type, row ) {
urlprefix.set("word", data); return '<a class="' + getMergedClass(row.rank) + '" href="?' + urlprefix + '">' + data + '</a>'
}}
],
"columnDefs": [
{ className: "dt-right", "targets": [0,1] },
{ "searchable": false,
"orderable": false,
"targets": 0
},
{ "orderSequence": [ "desc" ], "targets": [ 1 ] },
{ "orderSequence": [ "asc", "desc" ], "targets": [ 2 ] },
],
"oLanguage": {
"sSearch": "Filter: "
},
"order": [[ 1, 'desc' ]],
} );
t.on( 'order.dt search.dt', function () {
t.column(0, {order:'applied'}).nodes().each( function (cell, i) {
cell.innerHTML = i+1;
} );
} ).draw();
$( "#first" ).clone().prependTo( "#tabs-2" );
}
var collocatorData = <%= b(Mojo::JSON::to_json($collocators)) %>;
var maxHeat; // = Math.max.apply(Math,collocatorData.map(function(o){return o.cprob;}))
if(typeof data !== 'undefined' && data.mergedEnd > 0) {
vocabDistanceTable = makeVocabDistanceTable("#vocabdistt", baseURL);
}
if (collocatorData != null) {
maxHeat = Math.max.apply(Math,collocatorData.map(function(o){return Math.max.apply(Math,o.heat);}))
collocatorTable = $('#secondtable').DataTable({
data: collocatorData,
"sScrollY": "780px",
"bScrollCollapse": true,
"bPaginate": false,
"bJQueryUI": true,
"dom": '<"top">rt<"bottom"flpB><"clear">',
buttons: [
{ extend: 'copyHtml5', text: '<i class="fa fa-files-o"></i>', titleAttr: 'Copy' },
{ extend: 'csvHtml5', text: '<i class="fa fa-file-text-o"></i>', titleAttr: 'CSV', filename: currentWords+'_syn_neighbours' },
{ extend: 'excelHtml5', text: '<i class="fa fa-file-excel-o"></i>', titleAttr: 'Excel', filename: currentWords+'_syn_neighbours', exportOptions: { columns: ':visible' } ,
}
],
"columns": [
{ "data": "rank", type: "allnumeric" },
{ "data": "pos", width: "7%", sClass: "dt-center mono compact", render: function ( data, type, row ) {return bitvec2window(data, row.heat, row.word) }},
{ "data": "max", render: function ( data, type, row ) {return data.toFixed(3) }},
{ "data": "average", render: function ( data, type, row ) {return data.toFixed(3) }},
{ "data": "prob", type: "scientific", render: function ( data, type, row ) {return data.toExponential(3) } },
{ "data": "cprob", type: "scientific", render: function ( data, type, row ) {return data.toExponential(3) } },
{ "data": "overall", type: "scientific", render: function ( data, type, row ) {return data.toExponential(3) } },
{ "data": "word", sClass: "collocator" },
{ "data": "rank", type: "allnumeric" }
],
"columnDefs": [
{ className: "dt-right", "targets": [0,2,3,4,5,6] },
{ className: "dt-center", "targets": [ 1] },
{ "searchable": false,
"orderable": false,
"targets": [0, 8]
},
{ "type": "scientific", targets: [2,3,4,5,6] },
{ "orderSequence": [ "desc" ], "targets": [ 2, 3, 4, 5, 6 ] },
{ "orderSequence": [ "asc", "desc" ], "targets": [ 1, 7 ] },
{ "targets": [8], "visible": false }
],
"oLanguage": {
"sSearch": "Filter: "
},
"order": [[ 4, 'desc' ]],
} );
$.ajaxSetup({
type: 'POST',
timeout: 30000,
error: function(xhr) {
$('#display_error')
.html('Error: ' + xhr.status + ' ' + xhr.statusText);
}
});
if($('#sprofiles').length) {
similarProfileTable = $('#sprofiles').DataTable({
ajax: {
method: "GET",
url: '/derekovecs/getSimilarProfiles',
dataType: 'json',
dataSrc: "",
timeout: 30000,
data: { w: paraResults[0][0].rank }
},
"initComplete":function(settings, json){
$('td.paradigmator a').on('mousedown', function(e) {
if (e.which === 2) {
e.preventDefault();
queryKorAPalternatives(paraResults[0][0].word, this.childNodes["0"].textContent);
return false;
}
});
},
"sScrollY": "780px",
"bScrollCollapse": true,
"bPaginate": false,
"bJQueryUI": true,
"dom": '<"top">rt<"bottom"flp><"clear">',
"columns": [
{ "data": "v", render: function ( data, type, row ) {return data.toFixed(3) }},
{ "data": "w", sClass: "paradigmator", render: function ( data, type, row ) {urlprefix.set("word", data); return '<a href="?' + urlprefix + '">' + data + '</a>' } }
],
"columnDefs": [
{ className: "dt-right", "targets": [0] },
],
"oLanguage": {
"sSearch": "Filter: "
},
"order": [[ 0, 'desc' ]],
});
}
// var filterQuot = /(^quot?=[A-Z])|(quot$)/g;
var filterQuot = /^quot/;
var ccResult;
var baseURL = window.location.pathname.replace(/[/]$/, '')
classicCollocatorTable = makeClassicCollocatorTable('#classicoloctable', baseURL, paraResults[0][0].rank)
$('#show-details').change(function (e) {
var columns = classicCollocatorTable.columns(".detail");
if(this.checked) {
columns.visible(true);
$("#ccd").css('width', 'auto');
} else {
columns.visible(false);
$("#ccd").css('width', '680px');
}
classicCollocatorTable.columns.adjust().draw();
} );
$("td.collocator").click(function(){
queryKorAPCII(this.textContent + " /w1:5,s0 " + CIIsearchWords);
});
collocatorTable.on( 'order.dt search.dt', function () {
collocatorTable.column(0, {order:'applied'}).nodes().each( function (cell, i) {
cell.innerHTML = i+1;
} );
}).draw();
}
if (localStorage && !window.location.hash) { // let's not crash if some user has IE7
var index = parseInt(localStorage['tab']||'0');
$("#tabs").tabs({ active: index });
}
$("#tabs").css("visibility", "visible"); // now we can show the tabs
});
$(function(){
$("#dropdownoptions").dialog({
title: "<%= loc 'Options' %>",
autoOpen: false,
modal: false,
draggable: false,
height: "auto",
width: "auto",
resizable: false,
buttons: {
"<%= loc 'Cancel'%>": function() {
$( this ).dialog( "close" );
},
"<%= loc 'Apply' %>": function() {
window.open($(location).attr('pathname')+'?'+$('form').serialize(), "_self");
}
}
});
});
$(function(){
$("#showoptions").click(function(){
$("#dropdownoptions").dialog("open");
var target = $(this);
$("#dropdownoptions").dialog("widget").position({
my: 'left bottom',
at: 'left bottom',
of: target
});
});
});
$( function() {
$( "#no_iterations" ).spinner({
spin: function( event, ui ) {
if ( ui.value < 1000 ) {
$( this ).spinner( "value", 1000 );
return false;
} else if ( ui.value > 10000 ) {
$( this ).spinner( "value", 10000 );
return false;
}
}
});
} );
$( function() {
$( "#neighbours" ).spinner({
spin: function( event, ui ) {
if ( ui.value < 0 ) {
$( this ).spinner( "value", 0 );
return false;
} else if ( ui.value > 200 ) {
$( this ).spinner( "value", 200 );
return false;
}
}
});
} );
$( function() {
$( "#cutoff" ).spinner({
spin: function( event, ui ) {
if ( ui.value < 100000 ) {
$( this ).spinner( "value", 100000 );
return false;
} else if ( ui.value > 2000000 ) {
$( this ).spinner( "value", 2000000 );
return false;
}
}
});
} );
$( function() {
$( "#tabs" ).tabs().addClass('tabs-min');
} );
$( function() {
$( ".controlgroup-vertical" ).controlgroup({
"direction": "vertical"
});
} );
$(function() {
$( document ).tooltip({
content: function() {
return $(this).attr('title');
}}
)
});
$(function () {
$(document).tooltip({
content: function () {
return $(this).prop('title');
},
show: null,
close: function (event, ui) {
ui.tooltip.hover(
function () {
$(this).stop(true).fadeTo(400, 1);
},
function () {
$(this).fadeOut("400", function () {
$(this).remove();
})
});
}
});
});
</script>
<script src="//d3js.org/d3.v3.min.js" charset="utf-8"></script>
<script src="/derekovecs/js/calendar-events.js"></script>
<script src="/derekovecs/js/tsne.js"></script>
<script src="/derekovecs/js/som.js"></script>
<script src="/derekovecs/js/labeler.js"></script>
<script src="/derekovecs/js/derekovecs.js"></script>
<script>
var opt = {epsilon: <%= $epsilon %>, perplexity: <%= $perplexity %>},
mapWidth = 800, // width map
mapHeight = 800,
jitterRadius = 7;
var T = new tsnejs.tSNE(opt); // create a tSNE instance
var Y;
var data;
var labeler;
function applyJitter() {
svg.selectAll('.tsnet')
.data(labels)
.transition()
.duration(50)
.attr("transform", function(d, i) {
T.Y[i][0] = (d.x - mapWidth/2 - tx)/ss/20;
T.Y[i][1] = (d.y - mapHeight/2 - ty)/ss/20;
return "translate(" +
(d.x) + "," +
(d.y) + ")";
});
}
function updateEmbedding() {
var Y = T.getSolution();
svg.selectAll('.tsnet')
.data(data.words)
.attr("transform", function(d, i) {
return "translate(" +
((Y[i][0]*20*ss + tx) + mapWidth/2) + "," +
((Y[i][1]*20*ss + ty) + mapHeight/2) + ")"; });
}
var svg;
var labels = [];
var anchor_array = [];
var text;
function getMergedClass(i) {
if(typeof data !== 'undefined' && i > data.mergedEnd) {
return " merged"
} else {
return "";
}
}
function getRankTooltip(i) {
if(data.mergedEnd) {
if(data.ranks[i] < data.mergedEnd) {
return "rank: "+i +" "+"freq. rank: "+(data.ranks[i]).toString().replace(/\B(?=(\d{3})+(?!\d))/g, ",");
} else {
return "rank: "+i +" "+"freq. rank: "+(data.ranks[i]-data.mergedEnd).toString().replace(/\B(?=(\d{3})+(?!\d))/g, ",") + " (merged vocab)";
}
} else {
return "rank: "+i +" "+"freq. rank: "+data.ranks[i].toString().replace(/\B(?=(\d{3})+(?!\d))/g, ",");
}
}
function drawEmbedding() {
var urlprefix = new URLSearchParams(window.location.search);
urlprefix.delete("word");
urlprefix.append("word","");
$("#embed").empty();
var div = d3.select("#embed");
// get min and max in each column of Y
var Y = T.Y;
svg = div.append("svg") // svg is global
.attr("width", mapWidth)
.attr("height", mapHeight);
var g = svg.selectAll(".b")
.data(data.words)
.enter().append("g")
.attr("class", "tsnet");
g.append("a")
.attr("xlink:href", function(word) {
return "?"+urlprefix+word; })
.attr("class", function(d, i) {
var res="";
if(data.marked[i]) {
res="marked ";
}
if(data.target.indexOf(" "+d+" ") >= 0) {
res += "target";
}
if(data.mergedEnd && data.ranks[i] >= data.mergedEnd) {
return res+" merged";
} else {
return res;
}
})
.attr("title", function(d, i) {
return getRankTooltip(i);
})
.append("text")
.attr("text-anchor", "top")
.attr("font-size", 12)
.text(function(d) { return d; });
g.append("svg:title")
.text(function(d, i) {
return getRankTooltip(i);
});
var zoomListener = d3.behavior.zoom()
.scaleExtent([0.1, 10])
.center([0,0])
.on("zoom", zoomHandler);
zoomListener(svg);
}
var tx=0, ty=0;
var ss=1;
var iter_id=-1;
function zoomHandler() {
tx = d3.event.translate[0];
ty = d3.event.translate[1];
ss = d3.event.scale;
updateEmbedding();
}
var stepnum = 0;
function stopStep() {
clearInterval(iter_id);
text = svg.selectAll("text");
// jitter function needs different data and co-ordinate representation
labels = d3.range(data.words.length).map(function(i) {
var x = (T.Y[i][0]*20*ss + tx) + mapWidth/2;
var y = (T.Y[i][1]*20*ss + ty) + mapHeight/2;
anchor_array.push({x: x, y: y, r: jitterRadius});
return {
x: x,
y: y,
name: data.words[i]
};
});
// get the actual label bounding boxes for the jitter function
var index = 0;
text.each(function() {
labels[index].width = this.getBBox().width;
labels[index].height = this.getBBox().height;
index += 1;
});
// setTimeout(updateEmbedding, 1);
// setTimeout(
labeler = d3.labeler()
.label(labels)
.anchor(anchor_array)
.width(mapWidth)
.height(mapHeight)
.update(applyJitter);
// .start(1000);
iter_id = setInterval(jitterStep, 1);
}
var jitter_i=0;
function jitterStep() {
if(jitter_i++ > 100) {
clearInterval(iter_id);
} else {
labeler.start2(10);
applyJitter();
}
}
var last_cost=1000;
function step() {
var i = T.iter;
if(i > <%= $no_iterations %>) {
stopStep();
} else {
var cost = Math.round(T.step() * 100000) / 100000; // do a few steps
$("#cost").html("tsne iteration " + i + ", cost: " + cost.toFixed(5));
if(i % 250 == 0 && cost >= last_cost) {
stopStep();
} else {
last_cost = cost;
updateEmbedding();
}
}
}
function showMap(j) {
data=j;
T.iter=0;
iter_id = -1;
last_cost=1000;
T.initDataRaw(data.vecs); // init embedding
drawEmbedding(); // draw initial embedding
if(iter_id >= 0) {
clearInterval(iter_id);
}
//T.debugGrad();
iter_id = setInterval(step, 1);
if(true) { // (<%= $show_som %>) {
makeSOM(j, <%= $no_iterations %>);
}
}
var queryword;
function showCollocatorSOM() {
var baseURL = window.location.pathname.replace(/[/]$/, '')
if (collocatorTable) {
var ctableData = collocatorTable.rows().data();
var nwords = [],
nranks = [];
for (var i=0; i < ctableData.length && i < 100; i++) {
nranks.push(ctableData[i].rank);
nwords.push(ctableData[i].word);
}
$.post(baseURL+'/getVecsByRanks',
JSON.stringify(nranks),
function(data, status){
showMap({target: " "+urlParams.get('word')+" ", mergedEnd: <%= $mergedEnd %>, words: nwords, vecs: data, ranks: nranks, marked: Array(100).fill(false)} );
}, 'json');
}
}
function onload() {
queryword = document.getElementById('word');
}
function queryKorAP() {
window.open("<%= $korap_url %>" + korapPath + '?q='+queryword.value+korapVC, 'KorAP');
}
function queryKorAPCII(query) {
window.open("<%= $korap_url %>" +korapPath + '?ql=cosmas2&q='+query+korapVC, 'KorAP');
}
</script>
</head>
<body onload="onload()"> <div style="display:none;" id="pmi_ttt">Pointwise mutual information: $$\text{MI}=\text{MI}=\log_2\frac{p(w_1,w_2)}{p(w_1) p(w_2)}$$<p class="citation">Church, K. W. and Hanks, P. (1990): Word association norms, mutual information, and lexicography. Comput. Linguist. 16, 1 (March 1990), 22-29.</p></div>
<div style="display:none;" id="md_ttt">Pointwise mutual information squared [1], also called mutual dependency [2]: $$\text{MI}^2=\text{MD}=\log_2\frac{p^2(w_1,w_2)}{p(w_1) p(w_2)}$$<p class="citation">[1] Daille, B. (1994): <a href="http://www.bdaille.com/index.php?option=com_docman&task=doc_download&gid=8&Itemid=">Approche mixte pour l’extraction automatique de terminologie: statistiques lexicales et filtres linguistiques</a>. PhD thesis, Université Paris 7.</p><p class="citation">[2] Thanopoulos, A., Fakotakis, N., Kokkinakis, G. (2002): <a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.11.8101&rep=rep1&type=pdf">Comparative evaluation of collocation extraction metrics</a>. In: Proc. of LREC 2002: 620–625.</p></div>
<div style="display:none;" id="lfmd_ttt">Pointwise mutual information cubed [1], also called log-frequency biased mutual dependency [2]: $$\text{MI}^3=\text{LFMD}=\log_2\frac{p^3(w_1,w_2)}{p(w_1) p(w_2)}$$<p class="citation">[1] Daille, B. (1994): <a href="http://www.bdaille.com/index.php?option=com_docman&task=doc_download&gid=8&Itemid=">Approche mixte pour l’extraction automatique de terminologie: statistiques lexicales et filtres linguistiques</a>. PhD thesis, Université Paris 7.</p><p class="citation">[2] Thanopoulos, A., Fakotakis, N., Kokkinakis, G. (2002): <a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.11.8101&rep=rep1&type=pdf">Comparative evaluation of collocation extraction metrics</a>. In: Proc. of LREC 2002: 620–625.</p></div>
<div style="display:none;" id="npmi_ttt">Normalized pointwise mutual information: $$\frac{\log_2\frac{p(w_1,w_2)}{p(w_1)p(w_2)}}{-\log_2(p(w_1,w_2))}$$<p class="citation">Bouma, Gerlof (2009): <a href="https://svn.spraakdata.gu.se/repos/gerlof/pub/www/Docs/npmi-pfd.pdf">Normalized (pointwise) mutual information in collocation extraction</a>. In Proceedings of GSCL.</p></div>
<div style="display:none;" id="ll_ttt">Log-likelihood: $$2\sum_{ij}O_{ij}\log\frac{O_{ij}}{E_{ij}}$$<p class="citation">Dunning, T. (1993): Accurate methods for the statistics of surprise and coincidence. Comput. Linguist. 19, 1 (March 1993), 61-74.</p>
<p class="citation">Evert, Stefan (2004): <a href="http://purl.org/stefan.evert/PUB/Evert2004phd.pdf">The Statistics of Word Cooccurrences: Word Pairs and Collocations.</a> PhD dissertation, IMS, University of Stuttgart. Published in 2005, URN urn:nbn:de:bsz:93-opus-23714.</p></div>
<div style="display:none;" id="logdice_ttt">Log-Dice: $$14 + \log_2 \frac{2f_{1,2}}{f_1 + f_2}$$<p class="citation">Rychlý, Pavel (2008): <a href="http://www.fi.muni.cz/usr/sojka/download/raslan2008/13.pdf">A lexicographer-friendly association score.</a> In Proceedings of Recent Advances in Slavonic Natural Language Processing, RASLAN, 6–9, 2008</p></div>
<div style="display:none;" id="logdiceaf_ttt">Log-Dice using "auto-focus", i.e. the window that yields the highest score.</div>
<div id="ids_logo">
<a href="http://www.ids-mannheim.de/" target="_blank"><img src="/derekovecs/img/IDS-neu_farbig.svg" alt="Leibniz-Institut für Deutsche Sprache"/></a>
</div>
<div id="header">
<div id="pagetitle">
<h1>DeReKoVecs</h1>
<h2><%== $title %></h2>
</div>
<div id="options" class="widget">
<form id="queryform">
<input id="word" type="text" name="word" placeholder="<%= loc 'words_to_be_searched' %>" value="<%= $word %>"
title="<%= loc 'search_description' %>"/>
<input id="SEARCH" type="button" value="<%= loc 'SEARCH' %>">
<input type="button" id="showoptions" name="showoptions" value="<%= loc 'Options' %>" />
</form>
<div id="dropdownoptions" style="display: none">
<form id="optionsform">
<div class="controlgroup-vertical">
<label for="cutoff">cut-off</label>
<input id="cutoff" type="text" name="cutoff" size="10" value="<%= $cutoff %>" title="Only consider the most frequent x word forms.">
<label for="dedupe">dedupe</label>
<input id="dedupe" type="checkbox" name="dedupe" value="1" <%= ($dedupe ? "checked" : "") %> title="radically filter out any near-duplicates">
% if($mergedEnd > 0) {
<label for="sbf">backw.</label>
<input id="sbf" type="checkbox" name="sbf" value="1" <%= ($searchBaseVocabFirst ? "checked" : "") %> title="If checkecked base vocabulary will be searched first. Otherwise merged vocabulray will be searched first.">
% }
<label for="neighbours">max. neighbours:</label>
<input id="neighbours" size="4" name="n" value="<%= $no_nbs %>">
<label for="no_iterations">max. iterations</label>
<input id="no_iterations" name="N" size="4" value="<%= $no_iterations %>">
<!-- <label for="dosom">SOM</label>
<input id="dosom" type="checkbox" name="som" value="1" <%= ($show_som ? "checked" : "") %>> -->
% if($collocators) {
<label for="sortby">window/sort</label>
<select id="sortby" name="sort">
<option value="0" <%= ($sort!=1 && $sort!=2? "selected":"") %>>auto focus</option>
<!-- <option value="1" <%= ($sort==1? "selected":"") %>>any single position</option>
<option value="2" <%= ($sort==2? "selected":"") %>>whole window</option> -->
</select>
% }
<input type="button" value="→ KorAP" onclick="queryKorAP();" title="query word with KorAP"/>
<input id="show-details" type="checkbox" name="show-details" value="1" >
<label for="show-details">
Show details
</label>
</div>
</form>
</div>
</div>
</div>
<div id="topwrapper">
<div style="visibility: hidden;" id="tabs">
<ul>
% if (defined $word && $word ne '') {
% if($mergedEnd && $distantWords) {
<li><a href="#tabs-0" title="Cos offsets of the words furthest away from their position in the reference corpus."">Offsets</a></li>
% }
<li><a href="#tabs-1"><%= loc 'paradigmatic_tsne' %></a></li>
<li><a href="#tabs-2"><%= loc 'paradigmatic_som' %></a></li>
<li><a href="#tabs-3"><%= loc 'syntagmatic' %></a></li>
% }
<li><a href="#tabs-4">Info</a></li>
</ul>
% if($mergedEnd && $distantWords) {
<div id="tabs-0" style="display: flex; padding: 5px; flex-flow: row wrap;">
<div id="vocabdist" style="width: 230px; margin-bottom: 15px;">
<table class="display compact nowrap" id="vocabdistt">
<thead>
<tr>
<th align="right">#</th><th id="cosD" align="right">D<sub>cos</sub></th><th align="left">word</th>
</tr>
</thead>
<tbody>
<tr>
<td align="right">
</td>
<td align="right">
</td>
<td></td>
</tr>
</tbody>
</table>
</div>
</div>
% }
<div id="tabs-1" style="display: flex; padding: 5px; flex-flow: row wrap;">
% if($lists && (@$lists) > 0 && (@$lists)[0]) {
<div id="wrapper">
<div id="first" style="width: 230px; margin-bottom: 15px;">
<table class="display compact nowrap" id="firsttable">
<thead>
<tr>
<th align="right">#</th><th align="right">S<sub>cos</sub></th><th align="left">similars by w2v</th>
</tr>
</thead>
<tbody>
<tr>
<td align="right">
</td>
<td align="right">
</td>
<td></td>
</tr>
</tbody>
</table>
</div>
% if(0 && $haveSProfiles) {
<div id="sprofilesdiv" style="width: 200px; padding-right: 10px;">
<table class="display compact nowrap" id="sprofiles">
<thead>
<tr>
<th align="right">cos</th><th align="left">similars by coll. profile</th>
</tr>
</thead>
<tbody>
<tr>
<td align="right">
</td>
<td></td>
</tr>
</tbody>
</table>
</div>
%}
<div id="second">
<div id="embed">
</div>
<div id="cost">
</div>
</div>
</div>
% } elsif($word !~ /^\s*$/) {
<div id="wrapper">
<script>
$( function() {
$( "<%== loc 'notfounddialog' %>").dialog({
autoOpen: true,
modal: true,
draggable: false,
height: "auto",
width: "auto",
resizable: false,
buttons: {
"OK": function() {
$( this ).dialog( "close" );
} /* ,
"Apply": function() {
window.open($(location).attr('pathname')+'?'+$('form').serialize(), "_self");
} */
}
});
});
</script>
<div id="not-found-dialog_de" style="display: none" title="Nicht gefunden">
<p>FEHLER: Konnte "<%= $word %>" nicht finden.</p>
<p>Wenn Sie der Meinung sind, dass es Vokabluar enthalten sein sollte, können Sie versuchen den Cut-Off-Parameter in den Optionen zu erhöhen.</p>
</div>
<div id="not-found-dialog_en" style="display: none" title="Not found">
<p>ERROR: "<%= $word %>" not found in vocabluary.</p>
<p>If you are sure you have spelled the word as intended, you can try to increase the cutoff parameter in the options menu.</p>
</div>
</div>
% }
</div>
<div id="tabs-2" style="display: flex; padding: 5px; flex-flow: row wrap;">
% if(defined $word && $word ne "") {
<div id="som2" style="width: 800;">
<div id="sominfo1"><span id="somcolor1"> </span> <span id="somword1"> </span> <span id="somcolor2"> </span> <span id="somword2"> </span> <span id="somcolor3"> </span></div>
<div id="sominfo" style="text-align: right">SOM iteration <span id="iterations">0</span></div>
</div>
% }
</div>
<div id="tabs-3" style="display: flex; padding:5px; flex-flow: row wrap;">
<div style="margin-right: 20px; margin-bottom: 10px;" id="secondt">
<table class="display compact nowrap" id="secondtable">
<thead>
<tr>
% if($collocators) {
<th>#</th>
<th align="center" title="Activation of the respective collocator in the columns around the target normalized by its maximum (red). Columns selected by the auto-focus funtion (which window of all possible column-combinations maximizes ⊥(a/c)?) are marked with +. Click on the column postions to lauch a KorAP query with target word and collocator in the respective position.">w'</th>
<th align="right" title="Maximum activation of the collocator anywhere in the output layer.">max(a)</th>
<th title="Average raw activation of the collocator in the columns selected by auto-focus." align="right">⟨a⟩</th>
<th title="Sum of activations over the selected colunns normalized by the total activation sum of the selected columns." align="right">Σa/Σw'</th>
<th title="Co-norm of the column-normalized activations over the colunns selected by the auto-focus." align="right">⊥(a/c)</th>
<th title="Sum of the activations over the whole window normalized by the total window sum (no auto-focus)." align="right">Σa/Σw</th>
<th align="left"><%= loc 'collocate_w2v' %></th>
% }
</tr>
</thead>
<tbody>
<tr>
<td align="right">
</td>
<td align="right">
</td>
<td align="right">
</td>
<td align="right">
</td>
<td align="right">
</td>
<td align="right">
</td>
</tr>
</tbody>
</table>
</div>
<div id="ccd" style="">
<table class="display compact nowrap" id="classicoloctable">
<thead>
% if($collocators) {
<tr>
<th id="ll_tt">LL</th>
<th id="mi_tt">MI</th>
<th id="md_tt">MI²</th>
<th id="lfmd_tt">MI³</th>
<th id="npmi_tt">nPMI</th>
<th id="dice_tt">dice</th>
<th id="logdice_tt">LD</th>
<th id="logdiceaf_tt">LDaf</th>
<th id="delta_tt" title="Delta to log-Dice score in reference corpus. ⚠: If the collocate is not within the top 200 of the reference corpus, a reference value of min(lD)-0.1 is assumed.">Δ</th>
<th id="af_win" title="Positions around the target word that are selected by the auto-focus function are marked with ◾. Positions at which the collocate appears at least once are marked with ◽."><span class="regular"><%= loc 'af_window' %></span></th>
<th title="PMI³ restricted to left neighbour">l-PMI³</th>
<th title="PMI³ restricted to right neighbour">r-PMI³</th>
<th title="nPMI restricted to left neighbour">l-nPMI</th>
<th title="nPMI restricted to right neighbour">r-nPMI</th>
<th id="rawfreq_tt" title="raw frequency sum of collocation within window">raw</th>
<th><%= loc 'collocate_ca' %></th>
</tr>
% }
</thead>
<tbody>
<tr>
<td align="right"></td>
<td align="right"></td>
<td align="right"></td>
<td align="right"></td>
<td align="right"></td>
<td align="right"></td>
<td align="right"></td>
<td align="right"></td>
<td align="right"></td>
<td align="left"> </td>
<td align="right"></td>
<td align="right"></td>
<td align="right"></td>
<td align="right"></td>
<td align="left"> </td>
</tr>
</tbody>
</table>
</div>
<!--
<div style="clear:both" ></div>
<div style="float: right; overflow: hidden" id="extra"><button onClick="showCollocatorSOM()"> </button></div>
-->
</div>
<div id="tabs-4" style="display: flex; padding:5px; flex-flow: row wrap;">
<div id="info">
<h3><%== loc 'about' %></h3>
%= include(loc('abouttext'))
% if($training_args && (@$lists)[0]) {
<h3><%= loc 'training_parameters' %></h3>
% if($training_args =~ /-type\s*3/) {
<p>Calculations are based on a word embedding model trained with an extension of <a href="https://github.com/wlin12/wang2vec/">wang2vec</a> using the following parameters:</p>
<div class="mono"><%= $training_args %></div>
% } else {
<p>Calculations are based on a word embedding model trained with <a href="https://code.google.com/p/word2vec/">word2vec</a> using the following parameters:</p>
<div class="mono"><%= $training_args %></div>
% }
% }
<h3>Source Code</h3>
<ul>
<li><a href="https://korap.ids-mannheim.de/gerrit/plugins/gitiles/ids-kl/dereko2vec">dereko2vec</a></li>
<li><a href="https://korap.ids-mannheim.de/gerrit/plugins/gitiles/ids-kl/derekovecs">derekovecs</a></li>
</ul>
<h3><%== loc 'references' %></h3>
%= include 'references'
</div>
</div>
</div> <!-- tabs -->
</div> <!-- topwrapper -->
<div style="clear: both;"></div>
</div>
<div class="footer">
<span class="footertext">
%= include(loc('footer'))
</span>
</div>
</body>
</html>