Personal Information
Organização/Local de trabalho
London, United Kingdom United Kingdom
Cargo
VP of Data Architecture at Context Scout
Setor
Technology / Software / Internet
Sobre
Thanks to my PhD in Artificial Intelligence, I am interested in all aspects of
▪️ Knowledge Representation and Reasoning (KRR),
▪️ Statistical Relational Learning (SRL),
▪️ Natural Language Processing (NLP),
▪️ Graph Theory (GT).
My main area of expertise includes
▪️ Production Rule System (PRS) -- Drools,
▪️ Logic Programming (LP) -- Prolog,
▪️ Answer Set Programming (ASP) -- Gringo/Clasp,
▪️ Probabilistic Reasoning -- LPAD/ProbLog/Markov Logic Networks,
▪️ Knowledge Revision -- abductive, inductive and deductive reasoning.
I have work experience in
▪️ Natural Language Processing (NLP)
⟶ NLP libraries (Stanford CoreNLP/ClearNLP/Apache OpenNLP and personal tools),
⟶ Topic Ex...
Marcadores
artificial intelligence
logic programming
statistical relational learning
logic programs with annotated disjunctions
probabilistic inference
bdds
lpads
bdd
prolog
lpad
graphs
approximate inference
semantic web
drools
policy-making
latent topics
subjectivity
sentiment mining
clusters
word2vec
tf-idf
summarisation
centrality
readability
part-of-speech
stemming
ner
n-grams
word clouds
lda
text mining
nlp
knowledge revision
biological networks
alp
deduction
abduction
learning
induction
nonmonotonic
defeasible
ilp
inductive logic programming
probabilistic reasoning
ontologies
production rules system
knowledge representation
cv
physiotherapy rehabilitation for elder people; ms
jquery
web-app
pollutants
servlet
apache
jsp
electric
cxf
thermal
receptors
emilia romagna
bootstrap
highcharts
energy
emissions
epolicy
apache cxf
servlet/jsp
tagliatelle
bolognese sauce
taglietelle al ragù
italian cuisine
italy
italian food
spaghetti bolognese
c
linux
rtai
os
rt
operating systems
real-time
scheduling
edf
earliest deadline first
ai
production rules
production rule systems
cep
complex event processing
jboss
approximated algorithm
probability
ontology development
desciption logic
prs
fp7 project
energy plan
Ver mais
Apresentações
(10)Documentos
(2)Gostaram
(20)Introduction to py2neo
Nigel Small
•
Há 11 anos
Natural language search using Neo4j
Kenny Bastani
•
Há 10 anos
Neo4j - 5 cool graph examples
Peter Neubauer
•
Há 13 anos
Community detection in graphs
Nicola Barbieri
•
Há 9 anos
Building a Graph-based Analytics Platform
Kenny Bastani
•
Há 10 anos
Natural Language Processing with Neo4j
Kenny Bastani
•
Há 10 anos
Document Classification with Neo4j
Kenny Bastani
•
Há 9 anos
Natural Language Processing with Graph Databases and Neo4j
William Lyon
•
Há 8 anos
The art of tokenization
Craig Trim
•
Há 11 anos
Neo4j -- or why graph dbs kick ass
Emil Eifrem
•
Há 15 anos
An overview of Neo4j Internals
Tobias Lindaaker
•
Há 11 anos
Natural Language Search with Neo4j - Kenny Bastani @ GraphConnect NY 2013
Neo4j
•
Há 10 anos
Optimizing Cypher Queries in Neo4j
Neo4j
•
Há 10 anos
Cypher
Max De Marzi
•
Há 12 anos
Natural Language Processing for the Semantic Web
Isabelle Augenstein
•
Há 9 anos
5 Reasons Typography is Powerful
Big Fish Presentations
•
Há 10 anos
Prepared Speech Presentation
Yi-Hung Peng
•
Há 10 anos
Everything I know about software in spaghetti bolognese: managing complexity
JAX London
•
Há 11 anos
Why you should think like a journalist when planning to present
Simon Mossman
•
Há 10 anos
ePolicy - Engineering the POlicy-making LIfe CYcle
Io Partecipo
•
Há 12 anos
Personal Information
Organização/Local de trabalho
London, United Kingdom United Kingdom
Cargo
VP of Data Architecture at Context Scout
Setor
Technology / Software / Internet
Sobre
Thanks to my PhD in Artificial Intelligence, I am interested in all aspects of
▪️ Knowledge Representation and Reasoning (KRR),
▪️ Statistical Relational Learning (SRL),
▪️ Natural Language Processing (NLP),
▪️ Graph Theory (GT).
My main area of expertise includes
▪️ Production Rule System (PRS) -- Drools,
▪️ Logic Programming (LP) -- Prolog,
▪️ Answer Set Programming (ASP) -- Gringo/Clasp,
▪️ Probabilistic Reasoning -- LPAD/ProbLog/Markov Logic Networks,
▪️ Knowledge Revision -- abductive, inductive and deductive reasoning.
I have work experience in
▪️ Natural Language Processing (NLP)
⟶ NLP libraries (Stanford CoreNLP/ClearNLP/Apache OpenNLP and personal tools),
⟶ Topic Ex...
Marcadores
artificial intelligence
logic programming
statistical relational learning
logic programs with annotated disjunctions
probabilistic inference
bdds
lpads
bdd
prolog
lpad
graphs
approximate inference
semantic web
drools
policy-making
latent topics
subjectivity
sentiment mining
clusters
word2vec
tf-idf
summarisation
centrality
readability
part-of-speech
stemming
ner
n-grams
word clouds
lda
text mining
nlp
knowledge revision
biological networks
alp
deduction
abduction
learning
induction
nonmonotonic
defeasible
ilp
inductive logic programming
probabilistic reasoning
ontologies
production rules system
knowledge representation
cv
physiotherapy rehabilitation for elder people; ms
jquery
web-app
pollutants
servlet
apache
jsp
electric
cxf
thermal
receptors
emilia romagna
bootstrap
highcharts
energy
emissions
epolicy
apache cxf
servlet/jsp
tagliatelle
bolognese sauce
taglietelle al ragù
italian cuisine
italy
italian food
spaghetti bolognese
c
linux
rtai
os
rt
operating systems
real-time
scheduling
edf
earliest deadline first
ai
production rules
production rule systems
cep
complex event processing
jboss
approximated algorithm
probability
ontology development
desciption logic
prs
fp7 project
energy plan
Ver mais