Show all categories and normalize them

src/data/conferences/facct.yml

@@ -3,7 +3,15 @@
   id: facct25
   full_name:  ACM Conference on Fairness, Accountability, and Transparency
   link: https://facctconference.org/2026/index.html
-  deadline: '2026-01-13 23:59:59'
+  deadlines:
+  - type: abstract
+    label: Abstract Submission
+    date: '2026-01-08 23:59:59'
+    timezone: UTC-12
+  - type: submission
+    label: Paper Submission
+    date: '2026-01-13 23:59:59'
+    timezone: UTC-12
   timezone: UTC-12
   date: June 27 - June 30, 2026
   tags:
@@ -11,10 +19,10 @@
   - machine-learning
   - natural-language-processing
   - computer-vision
-  city: MONTREAL
-  country: CANADA
+  city: Montreal
+  country: Canada
   abstract_deadline: '2026-01-08 23:59:59'
   rankings: 'CCF: , CORE: , THCPL: '
-  venue: Hotel Bonaventure, Montreal, QC, CANADA
+  venue: Hotel Bonaventure, Montreal, QC, Canada
   hindex: 103
   note: ACM FAccT is an interdisciplinary conference dedicated to bringing together a diverse community of scholars from computer science, law, social sciences, and humanities to investigate and tackle issues in this emerging area. Research challenges are not limited to technological solutions regarding potential bias, but include the question of whether decisions should be outsourced to data- and code-driven computing systems. We particularly seek to evaluate technical solutions with respect to existing problems, reflecting upon their benefits and risks; to address pivotal questions about economic incentive structures, perverse implications, distribution of power, and redistribution of welfare; and to ground research on fairness, accountability, and transparency in existing legal requirements.

src/data/conferences/iclr.yml

@@ -11,6 +11,7 @@
   - computer-vision
   - natural-language-processing
   - signal-processing
+  - representation-learning
   country: Singapore
   abstract_deadline: '2024-09-27 23:59:59'
   rankings: 'CCF: N, CORE: A*, THCPL: A'
@@ -58,4 +59,5 @@
   - robotics
   - mathematics
   - reinforcement-learning
+  - representation-learning
   note: Mandatory abstract deadline on Sep 19, 2025. More info <a href='https://iclr.cc/Conferences/2026/Dates#'>here</a>.

src/data/conferences/icml.yml

@@ -22,7 +22,7 @@
   link: https://icml.cc/Conferences/2026/CallForPapers
   deadline: '2026-01-28 23:59:59'
   timezone: UTC-12
-  date: July 6-12, 2026
+  date: July 6-11, 2026
   tags:
   - machine-learning
   deadlines:

src/data/conferences/icomp.yml

@@ -11,4 +11,4 @@
   date: October, 2025
   tags:
   - machine-learning
-  - optimization
+  - optimization-methods

src/data/conferences/ijcnlp_and_aacl.yml

@@ -17,5 +17,5 @@
   pwclink: null
   hindex: null
   tags:
-  - natural language processing
+  - natural-language-processing
   note: Submissions through ARR.

src/data/conferences/nlbse.yml

@@ -17,6 +17,6 @@
   start: 2026-04-12
   end: 2026-04-13
   tags:
-  - natural language processing
+  - natural-language-processing
   - software engineering
   note: Co-located with ICSE 2026

src/data/conferences/ruleml+rr.yml

@@ -24,6 +24,6 @@
   hindex: null
   tags:
   - reasoning
-  - machine learning
+  - machine-learning
   - knowledge representation
   note: 'Part of "Declarative AI: Rules, Reasoning, Decisions, and Explanations". Proceedings published by Springer LNCS. Long papers: up to 15 pages (excluding references) + 2 pages for references; Short papers: up to 8 pages (excluding references) + 1 page for references. Notification: June 26, 2026 (AoE).'

src/data/conferences/www.yml

@@ -36,7 +36,7 @@
   start: 2026-04-13
   end: 2026-04-17
   tags:
-  - machine learning
+  - machine-learning
   - recommendation
   - semantics and knowledge
   - retrieval

src/pages/Index.tsx

@@ -22,22 +22,30 @@ const Index = () => {
   const [searchQuery, setSearchQuery] = useState("");
   const [showPastConferences, setShowPastConferences] = useState(false);
 
-  // Category buttons configuration
-  const categoryButtons = [
-    { id: "machine-learning", label: "Machine Learning" },
-    { id: "lifelong-learning", label: "Lifelong Learning" },
-    { id: "robotics", label: "Robotics" },
-    { id: "computer-vision", label: "Computer Vision" },
-    { id: "web-search", label: "Web Search" },
-    { id: "data-mining", label: "Data Mining" },
-    { id: "natural-language-processing", label: "Natural Language Processing" },
-    { id: "signal-processing", label: "Signal Processing" },
-    { id: "speech", label: "Speech" },
-    { id: "human-computer-interaction", label: "Human Computer Interaction" },
-    { id: "computer-graphics", label: "Computer Graphics" },
-    { id: "mathematics", label: "Mathematics" },
-    { id: "reinforcement-learning", label: "Reinforcement Learning" },
-  ];
+  // Dynamically generate category buttons from conference data
+  const categoryButtons = useMemo(() => {
+    if (!Array.isArray(conferencesData)) return [];
+    
+    // Count occurrences of each tag
+    const tagCounts = new Map<string, number>();
+    conferencesData.forEach((conf: Conference) => {
+      if (Array.isArray(conf.tags)) {
+        conf.tags.forEach(tag => {
+          tagCounts.set(tag, (tagCounts.get(tag) || 0) + 1);
+        });
+      }
+    });
+    
+    // Sort by frequency (most common first) and convert to button format
+    return Array.from(tagCounts.entries())
+      .sort((a, b) => b[1] - a[1])
+      .map(([tag]) => ({
+        id: tag,
+        label: tag.split("-").map(word => 
+          word.charAt(0).toUpperCase() + word.slice(1)
+        ).join(" ")
+      }));
+  }, []);
 
   const filteredConferences = useMemo(() => {
     if (!Array.isArray(conferencesData)) {