maksimekin / covid19-literature-clustering

An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.

Maksim E. Eren is an early career scientist in A-4, Los Alamos National Laboratory (LANL) Advanced Research in Cyber Systems division. He graduated Summa Cum Laude with a Computer Science Bachelor’s at University of Maryland Baltimore County (UMBC) in 2020 and Master’s in 2022. He is currently pursuing his Ph.D. at UMBC's DREAM Lab, and he is a Scholarship for Service CyberCorps alumnus. His interdisciplinary research interests lie at the intersection of machine learning and cybersecurity, with a concentration in tensor decomposition. His tensor decomposition-based research projects include large-scale malware detection and characterization, cyber anomaly detection, data privacy, text mining, Large Language Models, Knowladge Graphs, and High Performance Computing. Maksim has developed and published state-of-the-art solutions in anomaly detection and malware characterization. He has also worked on various other machine learning research projects such as detecting malicious hidden code, adversarial analysis of malware classifiers, and federated learning. At LANL, Maksim was a member of the 2021 R&D 100 winning project SmartTensors, where he has released a fast tensor decomposition and anomaly detection software, contributed to the design and development of various other tensor decomposition libraries, and developed state-of-the-art text mining tools.

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covid19-literature-clustering's Issues

Using SNN graph for clustering

Great work!

Instead of k-means, shared nearest neighbour graph can give more accurate clustering results.
One idea is to use SNN graph and leidenalg to determine the clusters.

here a repo for SNN

https://github.com/amararyal/Python-Shared-Nearest-Neighbor-Clustering-SNN-/blob/master/PythonSNN.py

Not able to callback

AttributeError Traceback (most recent call last)
in ()
10
11 # WIDGETS
---> 12 slider = Slider(start=0, end=20, value=20, step=1, title="Cluster #",callback=input_callback_1)
13 keyword = TextInput(title="Search:")
14

/home/ds/.local/lib/python3.6/site-packages/bokeh/models/widgets/sliders.py in init(self, **kwargs)
68 raise ValueError("Slider 'start' and 'end' cannot be equal.")
69
---> 70 super().init(**kwargs)
71
72 title = String(default="", help="""

/home/ds/.local/lib/python3.6/site-packages/bokeh/model.py in init(self, **kwargs)
232 kwargs.pop("id", None)
233
--> 234 super().init(**kwargs)
235 default_theme.apply_to_model(self)
236

/home/ds/.local/lib/python3.6/site-packages/bokeh/core/has_props.py in init(self, **properties)
245
246 for name, value in properties.items():
--> 247 setattr(self, name, value)
248
249 def setattr(self, name, value):

/home/ds/.local/lib/python3.6/site-packages/bokeh/core/has_props.py in setattr(self, name, value)
280
281 raise AttributeError("unexpected attribute '%s' to %s, %s attributes are %s" %
--> 282 (name, self.class.name, text, nice_join(matches)))
283
284 def str(self):

AttributeError: unexpected attribute 'callback' to Slider, similar attributes are js_event_callbacks