This document discusses sentiment analysis and how it can be applied using Apache Solr and UIMA. It provides an overview of sentiment analysis and defines key concepts. It then describes how Solr can be used to build search indexes and how UIMA can be used to integrate natural language processing tools for tasks like entity extraction and sentiment analysis. The document concludes with proposing a sentiment analysis application that uses various NLP techniques within Solr and UIMA to classify sentiment in text.
YouTube Link: https://youtu.be/tSjR7bk1Y9U
** Python Certification Training: https://www.edureka.co/python **
This Edureka PPT on 'How To Make A Chatbot In Python' will help you understand how you can use Chatterbot library in python to make a chatbot from scratch. Following are the topics discussed:
What Is A Chatbot?
ChatterBot In Python
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Python Tutorial Playlist: https://goo.gl/WsBpKe
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PatentTransformer is developed based on BERT and GPT-2 , which are the-state-of-the-art deep learning technology for the language models such as NLP (Natural Language Processing), NLU (Natural Language Understanding), and NLG (Natural Language Generation). PatentTransformer implements transfer learning exploiting pre-trained BERT and GPT-2, which are the unsupervised language model on a large corpus, and fine-tuned domain-specific language model on downstream tasks with much fewer data for patent claims.
A study states that people are now spending more time in messaging apps than social networking applications. Messaging apps are in trend and chatbots are the future. Learn everything about the chatbots from history to types to working, right here.
YouTube Link: https://youtu.be/tSjR7bk1Y9U
** Python Certification Training: https://www.edureka.co/python **
This Edureka PPT on 'How To Make A Chatbot In Python' will help you understand how you can use Chatterbot library in python to make a chatbot from scratch. Following are the topics discussed:
What Is A Chatbot?
ChatterBot In Python
Trainer For The Chatbot
Use Case - Flask Chatbot
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
PatentTransformer is developed based on BERT and GPT-2 , which are the-state-of-the-art deep learning technology for the language models such as NLP (Natural Language Processing), NLU (Natural Language Understanding), and NLG (Natural Language Generation). PatentTransformer implements transfer learning exploiting pre-trained BERT and GPT-2, which are the unsupervised language model on a large corpus, and fine-tuned domain-specific language model on downstream tasks with much fewer data for patent claims.
A study states that people are now spending more time in messaging apps than social networking applications. Messaging apps are in trend and chatbots are the future. Learn everything about the chatbots from history to types to working, right here.
Solr is an open source, widely used, popular IR machine. It can be used for simple sentiment analysis and sentiment retrieval tool. Its multi-language analyzers together with UIMA (Unstructured Information Management Architecture) framework can be extended for sentiment extraction. Each sentence passes through a series of pluggable annotators. Entity and its associated polarity are detected for each sentence. Polarity of each sentence is stored into Solr index. Persistent model files can be created from training data and accessed at run time.
Kaz Sato, Evangelist, Google at MLconf ATL 2016MLconf
Machine Intelligence at Google Scale: Tensor Flow and Cloud Machine Learning: The biggest challenge of Deep Learning technology is the scalability. As long as using single GPU server, you have to wait for hours or days to get the result of your work. This doesn’t scale for production service, so you need a Distributed Training on the cloud eventually. Google has been building infrastructure for training the large scale neural network on the cloud for years, and now started to share the technology with external developers. In this session, we will introduce new pre-trained ML services such as Cloud Vision API and Speech API that works without any training. Also, we will look how TensorFlow and Cloud Machine Learning will accelerate custom model training for 10x – 40x with Google’s distributed training infrastructure.
Integrate the most advanced text analytics into your predictive models - Mean...MeaningCloud
Discover the new MeaningCloud Extension for RapidMiner.
MeaningCloud webinar, April 27th, 2017.
More information and contents of the webinar https://www.meaningcloud.com/blog/recorded-webinar-integrate-the-most-advanced-text-analytics-into-your-predictive-models
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Advanced Virtual Assistant Based on Speech Processing Oriented Technology on ...ijtsrd
With the advancement of technology, the need for a virtual assistant is increasing tremendously. The development of virtual assistants is booming on all platforms. Cortana, Siri are some of the best examples for virtual assistants. We focus on improving the efficiency of virtual assistant by reducing the response time for a particular action. The primary development criterion of any virtual assistant is by developing a simple U.I. for assistant in all platforms and core functioning in the backend so that it could perform well in multi plat formed or cross plat formed manner by applying the backend code for all the platforms. We try a different research approach in this paper. That is, we give computation and processing power to edge devices itself. So that it could perform well by doing actions in a short period, think about the normal working of a typical virtual assistant. That is taking command from the user, transfer that command to the backend server, analyze it on the server, transfer back the action or result to the end user and finally get a response if we could do all this thing in a single machine itself, the response time will get reduced to a considerable amount. In this paper, we will develop a new algorithm by keeping a local database for speech recognition and creating various helpful functions to do particular action on the end device. Akhilesh L "Advanced Virtual Assistant Based on Speech Processing Oriented Technology on Edge Concept (S.P.O.T)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33289.pdf Paper Url: https://www.ijtsrd.com/computer-science/realtime-computing/33289/advanced-virtual-assistant-based-on-speech-processing-oriented-technology-on-edge-concept-spot/akhilesh-l
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Content management has been called a mature discipline, but emerging technologies like machine learning, cloud services, consumer friendly interfaces, and the block chain promise new capabilities that we need to be prepared to embrace in order for our organizations to successfully navigate the industry's digital transformation.
https://www.youtube.com/watch?v=VwC_Ko6Wk-0&list=PLyJdWuUHM3igOUt49uiFqs-6DCQAgJ1vs&index=2
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Machine learning has been widely used by various industries in 2023. The software development industry can take great advantage of machine learning in 2024 as well.
It has great potential to revolutionize various aspects of software development including task automation, boosting user experience, and easy software development and deployment.
How to use Artificial Intelligence in Times of Crisis
How to use Artificial Intelligence in Times of Crisis
In this session we will discuss three real, tangible use cases for leveraging artificial intelligence and applied machine learning models to solve problems in times of crisis. We will walk through problem discovery, design, development and deployment of solutions that can change the world.
In this talk,we will cover 3 specific use cases:
Use of open datasets to solve the world's problems – a list of open datasets will be provided that the attendees can take away
Helping Educators deliver value and engage with students (building bots for classrooms) – a free tutorial that the attendees can take after the session to get hands on experience building a classroom bot
The Power of Voice to create a simpler and hands-free interface to even the most complicated applications – a list of voice-dev resources will be provided for those who want to dive into the world of Amazon Alexa
Tour de France Azure PaaS 6/7 Ajouter de l'intelligenceAlex Danvy
Nous assisterons probablement à une rupture générationnelle entre les apps avec de l'intelligence artificielle et celles sans. Ces dernières, comme les applications en mode caractères à l'arrivée des interfaces graphiques, auront du mal à perdurer.
Azure met à dispositions 3 approches pour ajouter de l'IA dans une app, avec un niveau de difficulté graduel, de l'outil ne nécessitant aucune compétence particulière à celui dédié aux Data Scientistes.
Solr is an open source, widely used, popular IR machine. It can be used for simple sentiment analysis and sentiment retrieval tool. Its multi-language analyzers together with UIMA (Unstructured Information Management Architecture) framework can be extended for sentiment extraction. Each sentence passes through a series of pluggable annotators. Entity and its associated polarity are detected for each sentence. Polarity of each sentence is stored into Solr index. Persistent model files can be created from training data and accessed at run time.
Kaz Sato, Evangelist, Google at MLconf ATL 2016MLconf
Machine Intelligence at Google Scale: Tensor Flow and Cloud Machine Learning: The biggest challenge of Deep Learning technology is the scalability. As long as using single GPU server, you have to wait for hours or days to get the result of your work. This doesn’t scale for production service, so you need a Distributed Training on the cloud eventually. Google has been building infrastructure for training the large scale neural network on the cloud for years, and now started to share the technology with external developers. In this session, we will introduce new pre-trained ML services such as Cloud Vision API and Speech API that works without any training. Also, we will look how TensorFlow and Cloud Machine Learning will accelerate custom model training for 10x – 40x with Google’s distributed training infrastructure.
Integrate the most advanced text analytics into your predictive models - Mean...MeaningCloud
Discover the new MeaningCloud Extension for RapidMiner.
MeaningCloud webinar, April 27th, 2017.
More information and contents of the webinar https://www.meaningcloud.com/blog/recorded-webinar-integrate-the-most-advanced-text-analytics-into-your-predictive-models
www.meaningcloud.com
Advanced Virtual Assistant Based on Speech Processing Oriented Technology on ...ijtsrd
With the advancement of technology, the need for a virtual assistant is increasing tremendously. The development of virtual assistants is booming on all platforms. Cortana, Siri are some of the best examples for virtual assistants. We focus on improving the efficiency of virtual assistant by reducing the response time for a particular action. The primary development criterion of any virtual assistant is by developing a simple U.I. for assistant in all platforms and core functioning in the backend so that it could perform well in multi plat formed or cross plat formed manner by applying the backend code for all the platforms. We try a different research approach in this paper. That is, we give computation and processing power to edge devices itself. So that it could perform well by doing actions in a short period, think about the normal working of a typical virtual assistant. That is taking command from the user, transfer that command to the backend server, analyze it on the server, transfer back the action or result to the end user and finally get a response if we could do all this thing in a single machine itself, the response time will get reduced to a considerable amount. In this paper, we will develop a new algorithm by keeping a local database for speech recognition and creating various helpful functions to do particular action on the end device. Akhilesh L "Advanced Virtual Assistant Based on Speech Processing Oriented Technology on Edge Concept (S.P.O.T)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33289.pdf Paper Url: https://www.ijtsrd.com/computer-science/realtime-computing/33289/advanced-virtual-assistant-based-on-speech-processing-oriented-technology-on-edge-concept-spot/akhilesh-l
The Impact of Emerging Technology on Digital TransformationRichard Esplin
Keynote given by John Newton, CTO at Alfresco, during Alfresco DevCon 2018.
Content management has been called a mature discipline, but emerging technologies like machine learning, cloud services, consumer friendly interfaces, and the block chain promise new capabilities that we need to be prepared to embrace in order for our organizations to successfully navigate the industry's digital transformation.
https://www.youtube.com/watch?v=VwC_Ko6Wk-0&list=PLyJdWuUHM3igOUt49uiFqs-6DCQAgJ1vs&index=2
Top 5 Machine Learning Tools for Software Development in 2024.pdfPolyxer Systems
Machine learning has been widely used by various industries in 2023. The software development industry can take great advantage of machine learning in 2024 as well.
It has great potential to revolutionize various aspects of software development including task automation, boosting user experience, and easy software development and deployment.
How to use Artificial Intelligence in Times of Crisis
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In this session we will discuss three real, tangible use cases for leveraging artificial intelligence and applied machine learning models to solve problems in times of crisis. We will walk through problem discovery, design, development and deployment of solutions that can change the world.
In this talk,we will cover 3 specific use cases:
Use of open datasets to solve the world's problems – a list of open datasets will be provided that the attendees can take away
Helping Educators deliver value and engage with students (building bots for classrooms) – a free tutorial that the attendees can take after the session to get hands on experience building a classroom bot
The Power of Voice to create a simpler and hands-free interface to even the most complicated applications – a list of voice-dev resources will be provided for those who want to dive into the world of Amazon Alexa
Tour de France Azure PaaS 6/7 Ajouter de l'intelligenceAlex Danvy
Nous assisterons probablement à une rupture générationnelle entre les apps avec de l'intelligence artificielle et celles sans. Ces dernières, comme les applications en mode caractères à l'arrivée des interfaces graphiques, auront du mal à perdurer.
Azure met à dispositions 3 approches pour ajouter de l'IA dans une app, avec un niveau de difficulté graduel, de l'outil ne nécessitant aucune compétence particulière à celui dédié aux Data Scientistes.
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The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
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https://arxiv.org/abs/2306.08302
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https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
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But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
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In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
5. What is Sentiment Analysis?
A linguistic analysis technique that identifies
The movie is great.
The movie stars Mr. X
The movie is horrible.
opinion early in a piece of text.
8. Human can easily understand
emotions.
Can a machine be trained to do it?
What is Sentiment Analysis?
9. SA offers organizations ability to monitor in
real time and act accordingly
Marketing managers, PR Firms, campaign
managers, politicians, equity investors, on
line shoppers are direct beneficiaries
http://www.tweetfeel.com
http://www.nytimes.com/interactive/us/pol
itics/2010-twitter-candidates.html
10.
11. Document-Level
supervised/non supervised learning
Sentence-Level
supervised learning
Feature-Based Sentiment Analysis
All NP in corpus and Polarity
Sentiment Lexicon Acquisition
WordNet
12. Open-source Java based search
engine
Provides document indexing w/
arbitrary fields and fast search
Several relevance and ranking
algorithms
13. 1. Create an index
2. Add ‘document’ representations of
items
3. Construct queries
4. Ask for results (will be scored )
14. IndexWriterConfig config = /* configure */ ;
Directory dir = FSDirectory.open(indexFile);
IndexWriter w = new IndexWriter(dir, config);
for (ItemInfo item: getItems()) {
Document doc = new Document();
doc.add(new Field("title", item.title));
doc.add(new Field("tags", item.tags));
w.add(doc);
}
w.close();
16. PyLucene is Python implementation
Lucy is in C w/ bindings for other langs
Lucene.NET
SOLR provides search server (with REST
API) on top of Lucene
18. Linguistics module
Stems, Lemmas and Synonyms
multi language capability
CJKAnalyzer, UIMA Analyzers
UIMA integration
UpdateProcessorChain
Why Solr ?
19. Why Solr ?
Extract domain specific entities
and concepts
Time and Cost
Solr Set Up – 5 mins
UIMA Annotators - 5 days
Enrich text, write to dedicated field
20. Tagging entities in review text
Applications:
I wasn't really in the market for another tablet, but my girlfriend ended
up getting one for me so she got me on this one. I would like to say that
this tablet reminds me of the first Motorola Droid smartphone that came
out several years back. The phone jam packed a ton of bells & whistles
into its hardware and software to give a lot of bang for your buck. This
is what it feels like amazon has done with the Kindle Fire 8.9. They have
put a lot of advanced hardware and innovative software, so for the
average user, specially someone who absorbs a lot of media, you get a
lot for the price. But just because you get a lot for the price, doesn't
mean it is without its flaws.
22. Digital SLR with Full 1080p HD Video
There are many preprogrammed scene modes
that make this a very easy camera to use.
The picture quality is beyond belief, and
even better for the price.
Price:
Usecase
23. Why UIMA ?
UIMA Framework manages components
and data flow – No coding
Deploy pipeline of analysis engines
AEs wrap NLP algorithms
Person
Place
organization
Language
Detection
Aggregate analysis engine
Sentence
Annotator
POS
Annotator
NER
25. NLP+UIMA
Use POS in query understanding
boosting terms
Synonym expansion
Extract concepts/entities
Faceting using entities
Identify places in query
and use spatial queries
26. Ideas: Sentiment Analysis App
Identify Subjective Sentences from text
Remove noisy sentences
– Regex, conditional probability
Graph min cut – LingPipe
Subjectivity Lexicons
Discard Facts and Objective Sentences
31. Data transformation or post processing
UpdateProcessorFactory
LogUpdateProcessorFactory
UIMAUpdateProcessorFactory
UpdateRequestProcessorChain
◦ Pipe line of UpdateRequestProcessors
Huge explosion today of sentiments. PR firms, etc r Direct beneficiary of SA technology
Classify sentences into 2 principal classes subjective, objective
Positive, negative neutral, naïve bayes
Overall this review is very positive about smart phone, sentiment score
Using hierarchical classification, neutrality is determined first, and sentiment polarity is determined second, but only if the text is not neutral.
No matter how you choose to import data, there is a final config point within solr that allows manipulation of the imported data before it get indexed. Updaterquesthandler put documents on an update request processor chain.