akcube · akcube · Jan 11, 2026
diff --git a/assets/indices/contentIndex.json b/assets/indices/contentIndex.json
diff --git a/assets/indices/linkIndex.json b/assets/indices/linkIndex.json
diff --git a/content/blog/activity-selection-huffman-encoding.md b/content/blog/activity-selection-huffman-encoding.md
@@ -187,12 +187,4 @@ The following video was referenced while making this diary and is the source of
 # References
 These notes are old and I did not rigorously horde references back then. If some part of this content is your's or you know where it's from then do reach out to me and I'll update it. 
 1. Professor [Kannan Srinathan's](https://www.iiit.ac.in/people/faculty/srinathan/) course on Algorithm Analysis & Design in IIIT-H
-2. [Huffman Codes: An Information Theory Perspective - Reducible](https://youtu.be/B3y0RsVCyrw?si=5kFqRPa_XsGxpqBr)
-
----
-
-## Related Reading
-
-- [More Greedy Algorithms! Kruskal's & Disjoint Set Union](/blog/more-greedy-algorithms-kruskal-s-disjoint-set-union)
-- [Set Cover & Approximation Algorithms](/blog/set-cover-approximation-algorithms)
-- [DP as DAGs,  Shortest path on DAGs & LIS in O(nlogn)](/blog/dp-as-dags-shortest-path-on-dags-lis-in-o-nlogn)
+2. [Huffman Codes: An Information Theory Perspective - Reducible](https://youtu.be/B3y0RsVCyrw?si=5kFqRPa_XsGxpqBr)
diff --git a/content/blog/chain-matrix-multiplication.md b/content/blog/chain-matrix-multiplication.md
@@ -117,11 +117,4 @@ In this DP solution, we cannot simply construct a DAG structure and find the lon
 Last time, we were able to reduce the space complexity of our DP by realizing that the DP only relied on the states of the DP solution exactly **one** level below the current level. However, here we realize that this is sadly not the case. The solution at some node $[i, j]$ is very much reliant on every level below it. 1D row optimization etc does not seem to be of much use here. There is also no monotonicity that can be exploited to make the linear computation at some node logarithmic similar to how we did with LIS. Hence I do not think there is a better way to solve this problem.
 # References
 These notes are old and I did not rigorously horde references back then. If some part of this content is your's or you know where it's from then do reach out to me and I'll update it. 
-1. Professor [Kannan Srinathan's](https://www.iiit.ac.in/people/faculty/srinathan/) course on Algorithm Analysis & Design in IIIT-H
-
----
-
-## Related Reading
-
-- [DP as DAGs,  Shortest path on DAGs & LIS in O(nlogn)](/blog/dp-as-dags-shortest-path-on-dags-lis-in-o-nlogn)
-- [A Deep Dive into the Knapsack Problem](/blog/a-deep-dive-into-the-knapsack-problem)
+1. Professor [Kannan Srinathan's](https://www.iiit.ac.in/people/faculty/srinathan/) course on Algorithm Analysis & Design in IIIT-H
diff --git a/content/blog/covered-calls-strategy.md b/content/blog/covered-calls-strategy.md
@@ -34,11 +34,4 @@ The premiums received from selling call options are generally considered short-t
 ## Share Holding Power Reduction
 If the stock price fluctuates significantly, even if it remains flat over the long term, the covered call strategy may result in a gradual reduction in the number of shares held due to the exercise of call options. This can lead to realizing losses, despite the overall position being flat.
 ## Risk-Adjusted Return Considerations
-While some people argue that covered call strategies may offer superior risk-adjusted returns, meaning higher returns per unit of risk taken, this claim is subject to debate and may depend on the specific market conditions and underlying assets involved.
-
----
-
-## Related Reading
-
-- [Efficient-Market-Hypothesis](/blog/efficient-market-hypothesis)
-- [What is the Stock Market?](/blog/what-is-the-stock-market)
+While some people argue that covered call strategies may offer superior risk-adjusted returns, meaning higher returns per unit of risk taken, this claim is subject to debate and may depend on the specific market conditions and underlying assets involved.
diff --git a/content/blog/derivatives-options.md b/content/blog/derivatives-options.md
@@ -157,11 +157,3 @@ The Indian National Stock Exchange (since July 2018 expiry contracts), uses phys
 4. [Physical Delivery - Investopedia](https://www.investopedia.com/terms/p/physicaldelivery.asp)
 5. [Policy on settlement of compulsory delivery derivative contracts — Update Oct 2019 - Zerodha](https://zerodha.com/z-connect/general/policy-on-settlement-of-compulsory-delivery-derivative-contracts-update-oct-2019)
 6. [Physical delivery of stock F&O & their risks - Zerodha](https://zerodha.com/z-connect/general/physical-delivery-of-stock-fo-their-risks)
-
-
----
-
-## Related Reading
-
-- [Covered Calls Strategy](/blog/covered-calls-strategy)
-- [Efficient-Market-Hypothesis](/blog/efficient-market-hypothesis)
diff --git a/content/blog/dp-as-dags-shortest-path-on-dags-lis-in-o-nlogn.md b/content/blog/dp-as-dags-shortest-path-on-dags-lis-in-o-nlogn.md
@@ -190,12 +190,4 @@ int lis(int arr[], int n) {
 # References
 These notes are old and I did not rigorously horde references back then. If some part of this content is your's or you know where it's from then do reach out to me and I'll update it. 
 1. Professor [Kannan Srinathan's](https://www.iiit.ac.in/people/faculty/srinathan/) course on Algorithm Analysis & Design in IIIT-H
-2. [Huffman Codes: An Information Theory Perspective - Reducible](https://youtu.be/B3y0RsVCyrw?si=5kFqRPa_XsGxpqBr)
-
----
-
-## Related Reading
-
-- [Levenshtein Edit Distance](/blog/levenshtein-edit-distance)
-- [Chain Matrix Multiplication](/blog/chain-matrix-multiplication)
-- [A Deep Dive into the Knapsack Problem](/blog/a-deep-dive-into-the-knapsack-problem)
+2. [Huffman Codes: An Information Theory Perspective - Reducible](https://youtu.be/B3y0RsVCyrw?si=5kFqRPa_XsGxpqBr)
diff --git a/content/blog/getting-rid-of-short-form-content.md b/content/blog/getting-rid-of-short-form-content.md
@@ -1,7 +1,7 @@
 ---
 author: Kishore Kumar
 date: 2024-06-25 14:25:53+0530
-doc: 2024-06-05 05:06:01+0530
+doc: 2025-05-18 17:07:02+0530
 title: Getting Rid of Short-Form Content
 ---
 Social media platforms are universally competing to capture all our time and attention by spamming us with brain-rot short form content... and it's working. And unlike other forms of addiction, it's not even true that we get dopamine hits from consuming short form content. More often than not, we don't even realize the amount of time that was passed consuming tidbits of random brain rot. YouTube for example randomly starts on the shorts page and users don't even realize they're scrolling through shorts until much later. Below we'll quickly outline a few software fixes we can implement at the moment to try to purge short form content from our life. Needless to say, if you're an iOS user, please chuck your phone. 

diff --git a/content/blog/levenshtein-edit-distance.md b/content/blog/levenshtein-edit-distance.md
@@ -155,11 +155,3 @@ The single row optimized dp code for calculating the Levenshtein distance betwee
 These notes are old and I did not rigorously horde references back then. If some part of this content is your's or you know where it's from then do reach out to me and I'll update it. 
 1. Professor [Kannan Srinathan's](https://www.iiit.ac.in/people/faculty/srinathan/) course on Algorithm Analysis & Design in IIIT-H
 2. [How do Spell Checkers work? Levenshtein Edit Distance - Creel](https://youtu.be/Cu7Tl7FGigQ?si=pFru3JaBAeKStvtz) (Excellent channel, do check him out. Has a lot of unique amazing content!)
-
-
----
-
-## Related Reading
-
-- [Chain Matrix Multiplication](/blog/chain-matrix-multiplication)
-- [A Deep Dive into the Knapsack Problem](/blog/a-deep-dive-into-the-knapsack-problem)
diff --git a/content/blog/more-greedy-algorithms-kruskal-s-disjoint-set-union.md b/content/blog/more-greedy-algorithms-kruskal-s-disjoint-set-union.md
@@ -161,11 +161,4 @@ Below are links to `C++` implementations of both the fully equipped Disjoint Set
 # References
 These notes are old and I did not rigorously horde references back then. If some part of this content is your's or you know where it's from then do reach out to me and I'll update it. 
 1. Professor [Kannan Srinathan's](https://www.iiit.ac.in/people/faculty/srinathan/) course on Algorithm Analysis & Design in IIIT-H
-2. [Disjoint Set Union - cp-algorithms](https://cp-algorithms.com/data_structures/disjoint_set_union.html)
-
----
-
-## Related Reading
-
-- [Set Cover & Approximation Algorithms](/blog/set-cover-approximation-algorithms)
-- [DP as DAGs,  Shortest path on DAGs & LIS in O(nlogn)](/blog/dp-as-dags-shortest-path-on-dags-lis-in-o-nlogn)
+2. [Disjoint Set Union - cp-algorithms](https://cp-algorithms.com/data_structures/disjoint_set_union.html)
diff --git a/content/blog/set-cover-approximation-algorithms.md b/content/blog/set-cover-approximation-algorithms.md
@@ -131,10 +131,4 @@ Note that $n_t$ is the number of elements left at the $i^{th}$ iteration. Theref
 This **must** mean that the algorithm will terminate after $t=k\ ln(n)$ iterations. Our algorithm picks exactly 1 set per iteration. This also implies that if our optimal answer is $k$, our greedy strategy will pick at most $k \ ln(n)$ sets. Hence we have successfully managed to put a bound on the approximation.
 # References
 These notes are old and I did not rigorously horde references back then. If some part of this content is your's or you know where it's from then do reach out to me and I'll update it. 
-1. Professor [Kannan Srinathan's](https://www.iiit.ac.in/people/faculty/srinathan/) course on Algorithm Analysis & Design in IIIT-H
-
----
-
-## Related Reading
-
-- [DP as DAGs,  Shortest path on DAGs & LIS in O(nlogn)](/blog/dp-as-dags-shortest-path-on-dags-lis-in-o-nlogn)
+1. Professor [Kannan Srinathan's](https://www.iiit.ac.in/people/faculty/srinathan/) course on Algorithm Analysis & Design in IIIT-H
diff --git a/content/blog/what-is-the-stock-market.md b/content/blog/what-is-the-stock-market.md
@@ -39,12 +39,3 @@ Soon, the Dutch East India Company took this concept to the next level. Instead
 2. [Explained | The Stock Market | FULL EPISODE | Netflix](https://www.youtube.com/watch?v=ZCFkWDdmXG8&t=4s)
 3. [Wikipedia - Euronext Amsterdam](https://en.wikipedia.org/wiki/Euronext_Amsterdam)
 4. [How The Economic Machine Works by Ray Dalio](https://www.youtube.com/watch?v=PHe0bXAIuk0)
-
-
----
-
-## Related Reading
-
-- [Derivatives - Options](/blog/derivatives-options)
-- [Efficient-Market-Hypothesis](/blog/efficient-market-hypothesis)
-- [Stock Multiples](/blog/stock-multiples)
diff --git a/publisher-v2/config.yaml b/publisher-v2/config.yaml
@@ -25,7 +25,6 @@ filters:
 
 # Feature Flags
 features:
-  enable_related_reading: true
   optimize_images: true
 
 # Image Optimization Settings

diff --git a/publisher-v2/link_processor.py b/publisher-v2/link_processor.py
@@ -14,7 +14,6 @@ class LinkProcessor:
 
     def __init__(self, config: Dict):
         self.config = config
-        self.enable_related = config['features'].get('enable_related_reading', True)
 
     def parameterize_title(self, title: str) -> str:
         """Convert note title to URL-safe slug"""
@@ -120,53 +119,6 @@ def process_images(self, content: str) -> Tuple[str, Set[str]]:
 
         return processed_content, image_deps
 
-    def generate_related_section(self, frontmatter: Dict, note_slug: str, already_linked: Set[str] = None) -> str:
-        """
-        Generate Related Reading section from frontmatter
-
-        Args:
-            frontmatter: Note frontmatter dict
-            note_slug: URL slug of current note (to avoid self-reference)
-            already_linked: Set of note names already linked in content (to avoid duplicates)
-
-        Returns:
-            Markdown string for related section
-        """
-        if not self.enable_related:
-            return ""
-
-        related = frontmatter.get('related', [])
-        if not related:
-            return ""
-
-        if already_linked is None:
-            already_linked = set()
-
-        # Filter out self-references, already-linked notes, and convert to links
-        related_links = []
-        for item in related:
-            # Extract note name from wikilink format
-            note_name = item.strip('[]').split('|')[0]
-            slug = self.parameterize_title(note_name)
-
-            # Skip self-references
-            if slug == note_slug:
-                continue
-
-            # Skip notes already linked in content
-            if note_name in already_linked:
-                continue
-
-            related_links.append(f"- [{note_name}](/blog/{slug})")
-
-        if not related_links:
-            return ""
-
-        section = "\n\n---\n\n## Related Reading\n\n"
-        section += "\n".join(related_links)
-        section += "\n"
-
-        return section
 
 
 def main():
@@ -206,21 +158,6 @@ def main():
     print("After processing images:")
     print(processed)
     print(f"\nImage dependencies: {images}")
-    print("\n" + "="*60 + "\n")
-
-    # Test related section
-    frontmatter = {
-        'title': 'Test Note',
-        'related': [
-            '[[Another Note]]',
-            '[[Deep Dive into Algorithms]]',
-            '[[Complex Note Title]]'
-        ]
-    }
-
-    related_section = processor.generate_related_section(frontmatter, 'test-note')
-    print("Generated related section:")
-    print(related_section)
 
 
 if __name__ == '__main__':

diff --git a/publisher-v2/publisher.py b/publisher-v2/publisher.py
@@ -185,11 +185,6 @@ def process_note(self, note_path: Path) -> bool:
             processed_content, referenced_notes = self.link_processor.process_wikilinks(content)
             processed_content, image_deps = self.link_processor.process_images(processed_content)
 
-            # Add related reading section (uses original frontmatter for 'related' field)
-            # Pass referenced_notes to avoid duplicating links already in content
-            if self.config['features']['enable_related_reading']:
-                related_section = self.link_processor.generate_related_section(frontmatter, slug, referenced_notes)
-                processed_content += related_section
 
             # Process and copy images
             self._process_images(image_deps, note_path)
@@ -337,11 +332,12 @@ def _clean_orphaned_images(self):
             # Match ![alt](/images/name.webp) pattern
             matches = re.findall(r'!\[[^\]]*\]\(/images/([^)]+)\)', content)
             for match in matches:
-                # Add both the referenced file and its base name (for .png fallback)
+                # Add the referenced file
                 referenced_images.add(match)
-                # Also add the .png version if .webp is referenced
-                if match.endswith('.webp'):
-                    referenced_images.add(match.replace('.webp', '.png'))
+                # Also add all related formats (webp, png, jpg) for fallback handling
+                base_name = Path(match).stem
+                for ext in ['.webp', '.png', '.jpg', '.jpeg', '.gif']:
+                    referenced_images.add(f"{base_name}{ext}")
 
         # Get all images in static/images
         existing_images = set()