Skip to content

Commit 4c2cb41

Browse files
sammjainnsammjainn
authored
Merge pull request #16 from Graphlet-AI/sj_fixes
Fix design review issues
2 parents 26b55b9 + 1503acf commit 4c2cb41

File tree

2 files changed

+30
-23
lines changed

2 files changed

+30
-23
lines changed

‎01_index.markdown

+16-17
Original file line numberDiff line numberDiff line change
@@ -3,7 +3,7 @@
33
# To modify the layout, see https://jekyllrb.com/docs/themes/#overriding-theme-defaults
44

55
layout: home
6-
permalink: "/"
6+
permalink: '/'
77
header: Home
88
title: Home
99
head: Graphlet AI
@@ -13,7 +13,6 @@ background: home/bg.png
1313
---
1414

1515
<div class="introduction">
16-
<div style="margin-top: -5%;"></div>
1716
<h2 id="introduction">Knowledge Graph Construction</h2>
1817
<div>
1918
<div>
@@ -104,7 +103,7 @@ background: home/bg.png
104103
</div>
105104
<div style="margin-top: 2%;"></div>
106105
<div>
107-
Recent developments in Large Language Models [LLMs] like <a href="https://chat.openai.com/chat/">ChatGPT</a> and Graph Neural Networks (GNNs) allow us to ETL nodes and edges into XML-like text and sentence encode them using a large language model and then combine them based on semantic inferences made by the LLM in combination with the network topology. LLMs have seen many similar documents as the nodes’ text representation on the world wide web, and if we provide a few clues... they provide state of the art entity resolution for both the blocking and matching stages!
106+
Recent developments in Large Language Models [LLMs] like <a href="https://chat.openai.com/chat/" target="_blank">ChatGPT</a> and Graph Neural Networks (GNNs) allow us to ETL nodes and edges into XML-like text and sentence encode them using a large language model and then combine them based on semantic inferences made by the LLM in combination with the network topology. LLMs have seen many similar documents as the nodes’ text representation on the world wide web, and if we provide a few clues... they provide state of the art entity resolution for both the blocking and matching stages!
108107
</div>
109108
<div style="margin-top: 2%;"></div>
110109
<div>
@@ -206,22 +205,22 @@ background: home/bg.png
206205
<div>
207206
We can build knowledge graphs for any platform, but here are a few tools that are more up our alley to create business value using graphs and networks:
208207
</div>
209-
<li>
210-
<ul>Python tools like <a href="https://pandas.pydata.org/">Pandas</a> and <a href="https://networkx.org/">NetworkX</a>, <a href="https://graph-tool.skewed.de/">graph-tool</a>, <a href="https://networkit.github.io/">NetworKit</a> or <a href="https://www.graphifi.com/easygraph">EasyGraph</a></ul>
211-
<ul><a href="https://www.r-project.org/">R</a> tools like <a href="https://igraph.org/">iGraph</a>, <a href="https://tidygraph.data-imaginist.com/">tidygraph</a> and <a href="https://ggraph.data-imaginist.com/">ggraph</a></ul>
212-
<ul>Big data tools like <a href="https://spark.apache.org/docs/latest/api/python/">PySpark</a>, <a href="https://www.databricks.com/">Databricks</a>, <a href="https://www.dask.org/">Dask</a>, <a href="https://www.snowflake.com/en/">Snowflake</a> or <a href="https://graphframes.github.io/graphframes/docs/_site/index.html">GraphFrames</a></ul>
213-
<ul>GPU-accelerated compute tools like RAPIDS <a href="https://github.com/rapidsai/cugraph">cuGraph</a></ul>
214-
<ul>Property graph databases like <a href="https://neo4j.com/">Neo4j</a>, <a href="https://www.tigergraph.com/">TigerGraph</a>, <a href="https://www.arangodb.com/graph-database/">ArangoDB</a>, <a href="https://www.oracle.com/">Oracle Graph Studio</a> or Oracle Graph Studio</ul>
215-
<ul>Enterprise knowledge graphs that use RDF Triple Stores / SPARQL like <a href="https://www.stardog.com/">StarDog</a> or <a href="https://www.ontotext.com/">Ontotext</a></ul>
216-
<ul>Large knowledge bases like <a href="https://query.wikidata.org/">WikiData Query Service</a></ul>
217-
<ul><a href="https://jupyter.org/">Jupyter</a>, <a href="https://www.databricks.com/">Databricks</a> and <a href="https://www.snowflake.com/en/">Snowflake</a> Notebooks</ul>
218-
<ul>Natural Language Processing (NLP) users of tools such as <a href="https://spacy.io/">spaCy</a>, <a href="https://github.com/flairNLP/flair">FlairNLP</a>, <a href="https://blinkforhome.com/">BLINK</a>, <a href="https://radimrehurek.com/gensim/">Gensim</a> or <a href="https://www.nltk.org/">NLTK</a></ul>
219-
<ul>Network visualization tools like <a href="https://gephi.org/">Gephi</a>, <a href="https://www.graphistry.com/">Graphistry</a> or <a href="https://cambridge-intelligence.com/keylines/">Cambridge Intelligence Keylines</a> / <a href="https://cambridge-intelligence.com/regraph/">ReGraph</a></ul>
220-
</li>
208+
<ul>
209+
<li>Python tools like <a href="https://pandas.pydata.org/" target="_blank">Pandas</a> and <a href="https://networkx.org/" target="_blank">NetworkX</a>, <a href="https://graph-tool.skewed.de/" target="_blank">graph-tool</a>, <a href="https://networkit.github.io/" target="_blank">NetworKit</a> or <a href="https://www.graphifi.com/easygraph" target="_blank">EasyGraph</a></li>
210+
<li><a href="https://www.r-project.org/" target="_blank">R</a> tools like <a href="https://igraph.org/" target="_blank">iGraph</a>, <a href="https://tidygraph.data-imaginist.com/" target="_blank">tidygraph</a> and <a href="https://ggraph.data-imaginist.com/" target="_blank">ggraph</a></li>
211+
<li>Big data tools like <a href="https://spark.apache.org/docs/latest/api/python/" target="_blank">PySpark</a>, <a href="https://www.databricks.com/" target="_blank">Databricks</a>, <a href="https://www.dask.org/" target="_blank">Dask</a>, <a href="https://www.snowflake.com/en/" target="_blank">Snowflake</a> or <a href="https://graphframes.github.io/graphframes/docs/_site/index.html" target="_blank">GraphFrames</a></li>
212+
<li>GPU-accelerated compute tools like RAPIDS <a href="https://github.com/rapidsai/cugraph" target="_blank">cuGraph</a></li>
213+
<li>Property graph databases like <a href="https://neo4j.com/" target="_blank">Neo4j</a>, <a href="https://www.tigergraph.com/" target="_blank">TigerGraph</a>, <a href="https://www.arangodb.com/graph-database/" target="_blank">ArangoDB</a>, <a href="https://www.oracle.com/" target="_blank">Oracle Graph Studio</a> or Oracle Graph Studio</li>
214+
<li>Enterprise knowledge graphs that use RDF Triple Stores / SPARQL like <a href="https://www.stardog.com/" target="_blank">StarDog</a> or <a href="https://www.ontotext.com/" target="_blank">Ontotext</a></li>
215+
<li>Large knowledge bases like <a href="https://query.wikidata.org/" target="_blank">WikiData Query Service</a></li>
216+
<li><a href="https://jupyter.org/" target="_blank">Jupyter</a>, <a href="https://www.databricks.com/" target="_blank">Databricks</a> and <a href="https://www.snowflake.com/en/" target="_blank">Snowflake</a> Notebooks</li>
217+
<li>Natural Language Processing (NLP) users of tools such as <a href="https://spacy.io/" target="_blank">spaCy</a>, <a href="https://github.com/flairNLP/flair" target="_blank">FlairNLP</a>, <a href="https://blinkforhome.com/" target="_blank">BLINK</a>, <a href="https://radimrehurek.com/gensim/" target="_blank">Gensim</a> or <a href="https://www.nltk.org/" target="_blank">NLTK</a></li>
218+
<li>Network visualization tools like <a href="https://gephi.org/" target="_blank">Gephi</a>, <a href="https://www.graphistry.com/" target="_blank">Graphistry</a> or <a href="https://cambridge-intelligence.com/keylines/" target="_blank">Cambridge Intelligence Keylines</a> / <a href="https://cambridge-intelligence.com/regraph/" target="_blank">ReGraph</a></li>
219+
</ul>
221220
</div>
222221
<div>
223222
<div style="margin-top: 2%;"></div>
224-
<h2>Our Principal Consultant, <a href="https://www.linkedin.com/in/russelljurney/">Russell Jurney</a></h2>
223+
<h2>Our Principal Consultant, <a href="https://www.linkedin.com/in/russelljurney/" target="_blank">Russell Jurney</a></h2>
225224
<img align="left" style="margin-left: 0%; margin-right: 2%; width: 17%" src="assets/home/russell_jurney_headshot.jpg" alt="The beautiful face of Russell Jurney. Bald. Shiny." />
226225
<div>
227226
My name is Russell Jurney. I work at the intersection of big data, large networks - property graphs or knowledge graphs, representation learning with Graph Neural Networks (GNNs), Natural Language Processing (NLP) and Understanding (NLU), model explainability using network visualization and vector search for information retrieval.
@@ -237,4 +236,4 @@ background: home/bg.png
237236
Check out my network science portfolio, my blog and my O’Reilly Radar posts.
238237
</div>
239238
</div>
240-
</div>
239+
</div>

‎_sass/03-layouts/home.scss

+14-6
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,7 @@
22
color: white;
33
text-align: center;
44
font-size: 45px;
5-
padding-top: 20%;
5+
padding-top: 5%;
66
padding-bottom: 2rem;
77
max-width: 80%;
88
margin: auto;
@@ -89,32 +89,40 @@
8989
}
9090
@media screen and (min-width: 1440px) {
9191
.introduction {
92-
background-size: contain;
9392
div {
9493
max-width: 1440px;
9594
}
9695
padding-bottom: 5%;
9796
}
9897
#introduction {
99-
padding-top: 10%;
98+
padding-top: 5%;
10099
}
101100
.problem-definition {
102101
div {
103102
max-width: 1440px;
104103
}
105104
}
106105
}
106+
@media screen and (max-width: 1439px) {
107+
#introduction {
108+
padding-top: 10%;
109+
}
110+
}
111+
@media screen and (min-width: 1101px) {
112+
.introduction {
113+
background-size: contain;
114+
}
115+
}
107116
@media screen and (max-width: 1101px) {
108117
#introduction {
109-
margin-top: 1rem;
110-
padding-top: 2rem;
118+
padding-top: 5%;
111119
}
112120
.introduction {
113121
padding: 2rem;
114122
text-align: justify;
115123
background-repeat: no-repeat;
116124
padding-top: 10%;
117-
padding-bottom: 15%;
125+
padding-bottom: 25%;
118126

119127
div {
120128
background-image: none;

0 commit comments

Comments
 (0)