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<html>
<head>
<title>Textstellar</title>
<style>
body {
background-color: #1d1d1d;
color: whitesmoke;
font-family: sans-serif;
margin: 0 auto;
width: 800px;
text-align: center;
}
h1 {
margin: 0.5em 0;
}
.navbar {
display: flex;
justify-content: space-around;
align-items: center;
padding: 0.5em 1em;
background-color: #3a3a3a;
border-radius: 0.25em;
font-size: 1em;
}
.navbar a {
color: whitesmoke;
text-decoration: none;
}
.navbar a:hover {
text-decoration: underline;
}
.box {
display: flex;
/* justify-content: space-around; */
/* align-items: left; */
padding: 0.5em 1em;
background-color: #3a3a3a;
border-radius: 0.25em;
font-size: 0.9em;
}
</style>
</head>
<body>
<h1>Textstellar <a href="https://www.monash.edu/business/research/our-research/soda-labs"><img style="width: 11%;" src="assets/soda_cup_title_black_bg.png"></img></a></h1>
This page does not exist. Please click on one of the sections below 👇
<br><br>
<nav class="navbar">
<a href="https://textstellar.com/geopolitical_security">Geopolitical Security</a>
<a href="https://textstellar.com/thriving_communities/living_in_communities">Thriving Communities / Living in Communities</a>
<a href="https://textstellar.com/climate_change">Climate Change</a>
</nav>
<br>
<!-- <div class="box">
How does it work? Given a definition for "X" (a list of reference sentences capturing X), which could be a theme, challenge, or a concept, it finds the top-K related items based on their semantic similarity. The reference sentences could be either handcrafted, or GPT-3 prompted
It applies this to finding relevant research outcomes (and researchers) that are most salient for a given excercise (Semantic Ranking).
Then it performs unsupervised clustering for topic discovery using Topic Coherence to automatically guide the optimal cluster selection process.
Finally, it a generates a 2D "night sky" visualization of these latent topics.
</div> -->
</body>
</html>