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How to process text files with RapidMiner
 
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In this video I process transcriptions from Hugo Chavez's TV programme "Alo Presidente" to find patterns in his speech. Watching this video you will learn how to: -Download several documents at once from a webpage using a Firefox plugin. - Batch convert pdf files to text using a very simple script and a java application. - Process documents with Rapid Miner using their association rules feature to find patterns in them.
Views: 35994 Alba Madriz
How to Build a Text Mining, Machine Learning Document Classification System in R!
 
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We show how to build a machine learning document classification system from scratch in less than 30 minutes using R. We use a text mining approach to identify the speaker of unmarked presidential campaign speeches. Applications in brand management, auditing, fraud detection, electronic medical records, and more.
Views: 166174 Timothy DAuria
2. Text Mining Webinar - Create a Document
 
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This is the second part of the text Mining Webinar recorded on October 30 2013 (https://www.youtube.com/edit?o=U&video_id=tY7vpTLYlIg). This part describes all ways and nodes to create a Document data in KNIME, from reading documents from a folder (PDF, SDML,TXT, WORD DOC, RSS Feeds, etc...).
Views: 3815 KNIMETV
3. Entity Analysis in Unstructured Data
 
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RES.LL-005 D4M: Signal Processing on Databases, Fall 2012 View the complete course: http://ocw.mit.edu/RESLL-005F12 Instructor: Jeremy Kepner Historical evolution of the web and cloud computing. Using the exploded (D4M) schema. Analyzing computer network data. Analyzing computer network data. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 2539 MIT OpenCourseWare
Data Mining for Sales Prediction in Tourism Industry
 
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This video shows the demonstration of “Data Mining for Sales Prediction in Tourism Industry”. The app will provide you the forecast of sales in tourism industry. The app is based on the method called data mining. The application uses the user review to predict the sales. The reviews can be fed by uploading the excel sheets or the data of comments given by the users. Then a bar graph is created to predict the sales, using the submitted data of reviews and as well as the number of bookings. For more information on this project, visit http://nevonprojects.com/data-mining-for-sales-prediction-in-tourism-industry/ We provide Product Delivery and Customer Support Worldwide, so enter your country details on the website for the pricing details. CHECK OUT COLLECTION OF SOME OF OUR OTHER ““PHP Programming Language based Projects” 1. Online Bakery Shop System Php: https://youtu.be/GCbUHCP68D8 2. Online Herbs Shopping Php: https://youtu.be/PR5bGCtFxgA 3. Matrimonial Portal Project Php: https://youtu.be/q-WoDDC8dKk 4. Sentiment Based Movie Rating System Php: https://youtu.be/Nn-GyDvzKqE 5. Online Diagnostic Lab Reporting System Php: https://youtu.be/z-t5j2x4V0U Music - Landras Dream by Audionautix is licensed under a Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) Artist: http://audionautix.com/ To subscribe this channel click the link https://www.youtube.com/channel/UCisTN-GbgzzLRXftgnCJGKg?sub_confirmation=1 “Nevon Express” is our other channel, watch it at https://www.youtube.com/channel/UCJbZbcQI5PNDvP4TSZUkHRQ
Views: 700 Nevon Projects
Tutorial K-Means Cluster Analysis in RapidMiner
 
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Examines the way a k-means cluster analysis can be conducted in RapidMinder
Views: 46921 Gregory Fulkerson
Any Words Related Screenshot Convert to Text Words_Hindi
 
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Hello Friends, me upko iss video me bataya he kistra up any words related screen shot ko text me convert Kar shakta he, Any Words Related Screenshot Convert to Text Words, kistra up ek simple sa app ko download karke text me convert Kar shakte he, agar mera video aacha lagta he to mera channel ko subscribe kijie :- https://www.youtube.com/channel/UCyOZOFBj2_3psEtaCT_N7Mw Application :- https://play.google.com/store/apps/details?id=com.textify.free ======================================================================== Watch More Videos:- 1. How to Make Amazing Video Intro in Mobile_Hindi :- https://youtu.be/67c9pPMI2q8 2. How to Create Unlimited Email Without Registration :- https://youtu.be/gJW5DK88_yI ======================================================================== *Please Share, Support & Subscribe* ======================================================================== Facebook :- https://www.facebook.com/Technical-Prodip-471454759919895/ YouTube :- https://www.youtube.com/channel/UCyOZOFBj2_3psEtaCT_N7Mw Website :- https://www.technicalprodip.blogspot.com ======================================================================== Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. ======================================================================== About :- Thanks For Watching Technical Prodip Channel Video. Everyday Upload New Video. Where You Find Technical Video, Free Online Money Earning, Letats New Update & Amazing Application. Subscribe Our Channel : )
Views: 34 Technical Prodip
Video tutorial for crowdsourcing PDF data mining in Crowdcrafting
 
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This video shows how you can import from Dropbox PDF files into Crowdcrafting, to crowdsource the analysis of the PDF documents with just a few clicks.
A usefull OCR and keyword extraction software
 
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OCR and keyword extraction and Google and...
Views: 94 Trung Hiếu Lâm
Advanced Topics Presentation - IBM Watson Health and Text Analytics
 
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References: Text Analytics – The Most Powerful Weapon In Your Arsenal! - http://www.edvancer.in/introduction-text-analytics/ Watson – A System Designed for Answers - http://www-03.ibm.com/innovation/us/engines/assets/9442_Watson_A_System_White_Paper_POW03061-USEN-00_Final_Feb10_11.pdf Parallel Distributed Text Mining in R Stefan Theussl1 - http://statmath.wu.ac.at/~theussl/conferences/abstracts/ifcs_2009-abstract_A.pdf Transform clinical and operational decision making with IBM Content and Predictive Analytics for Healthcare - https://www-01.ibm.com/software/ecm/offers/programs/icpa.html IBM Watson and Medical Records Text Analytics - http://www-01.ibm.com/software/ebusiness/jstart/downloads/MRTAWatsonHIMSS.pdf IBM Watson: How it Works - https://www.youtube.com/watch?v=_Xcmh1LQB9I Open architecture helps Watson understand natural language - https://www.ibm.com/blogs/research/2011/04/open-architecture-helps-watson-understand-natural-language/ Unstructured Information Management Architecture SDK - https://www.ibm.com/developerworks/data/downloads/uima/ Open architecture helps Watson understand natural language - https://www.ibm.com/blogs/research/2011/04/open-architecture-helps-watson-understand-natural-language/ The Impact of Cognitive Computing on Healthcare - http://mihin.org/wp-content/uploads/2015/06/The-Impact-of-Cognitive-Computing-on-Healthcare-Final-Version-for-Handout.pdf Why IBM’s Watson Health buys let us peek behind the curtain to the future of healthcare - http://medcitynews.com/2016/03/watson-health-future-of-healthcare/ Glassdoor – IBM Data Scientist IBM Watson - http://ibmwatson237.weebly.com/advantages--disadvantages.html IBM Watson Engagement Advisor: Advantages and Disadvantages - http://infotechwea.blogspot.com/2013/05/ibm-watson-engagement-advisor.html IBM Watson -- How to replicate Watson hardware and systems design for your own use in your basement -https://www.ibm.com/developerworks/community/blogs/InsideSystemStorage/entry/ibm_watson_how_to_build_your_own_watson_jr_in_your_basement7?lang=en
Views: 1260 Emanuel Vela
text mining, web mining and sentiment analysis
 
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text mining, web mining
Views: 1613 Kakoli Bandyopadhyay
Pdf to text document using automater
 
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Use automated in mac to easily convert pdf to texts in less than a minute
Views: 89 George Costan
Week 4 - Twitter API KNIME Workflow
 
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Week 4 - Twitter API KNIME Workflow No authentication from your account. I already provided in the workflow. Follow the demonstration and make the changes for your assignment 2.
Views: 1029 Zirun Qi
Variable Importance using Target Shuffling
 
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This is the recording of Dean Abbott's talk at KNIME Summit 2016 with title "Variable Importance using Target Shuffling". Slides available at https://www.knime.org/files/summit2016/slides/Abbott--Variable%20Importance%20using%20Randomization_FINAL.pdf
Views: 1320 KNIMETV
Text Mining Term Assessment with Groupby in KNIME
 
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Using the groupby function to compute the percentage of documents associated with positive or negative sentiment in the IMDB movie review data
Views: 1147 Dean Abbott
Reading From A Text File Knime
 
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Data Access in KNIME: File Reader
Views: 83 Binom Teknoloji
Multilingual Text Mining: Lost in Translation, Found in Native Language Mining - Rohini Srihari
 
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There has been a meteoric rise in the amount of multilingual content on the web. This is primarily due to social media sites such as Facebook, and Twitter, as well as blogs, discussion forums, and reader responses to articles on traditional news sites. Language usage statistics indicate that Chinese is a very close second to English, and could overtake it to become the dominant language on the web. It is also interesting to see the explosive growth in languages such as Arabic. The availability of this content warrants a discussion on how such information can be effectively utilized. Such data can be mined for many purposes including business-related competitive insight, e-commerce, as well as citizen response to current issues. This talk will begin with motivations for multilingual text mining, including commercial and societal applications, digital humanities applications such as semi-automated curation of online discussion forums, and lastly, government applications, where the value proposition (benefits, costs and value) is different, but equally compelling. There are several issues to be touched upon, beginning with the need for processing native language, as opposed to using machine translated text. In tasks such as sentiment or behaviour analysis, it can certainly be argued that a lot is lost in translation, since these depend on subtle nuances in language usage. On the other hand, processing native language is challenging, since it requires a multitude of linguistic resources such as lexicons, grammars, translation dictionaries, and annotated data. This is especially true for "resourceMpoor languages" such as Urdu, and Somali, languages spoken in parts of the world where there is considerable focus nowadays. The availability of content such as multilingual Wikipedia provides an opportunity to automatically generate needed resources, and explore alternate techniques for language processing. The rise of multilingual social media also leads to interesting developments such as code mixing, and code switching giving birth to "new" languages such as Hinglish, Urdish and Spanglish! This phenomena exhibits both pros and cons, in addition to posing difficult challenges to automatic natural language processing. But there is also an opportunity to use crowd-sourcing to preserve languages and dialects that are gradually becoming extinct. It is worthwhile to explore frameworks for facilitating such efforts, which are currently very ad hoc. In summary, the availability of multilingual data provides new opportunities in a variety of applications, and effective mining could lead to better cross-cultural communication. Questions Addressed (i) Motivation for mining multilingual text. (ii) The need for processing native language (vs. machine translated text). (iii) Multilingual Social Media: challenges and opportunities, e.g., preserving languages and dialects.
Views: 1466 UA German Department
RapidMiner Tutorial (part 9/9) Association Rules
 
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This tutorial starts with introduction of Dataset. All aspects of dataset are discussed. Then basic working of RapidMiner is discussed. Once the viewer is acquainted with the knowledge of dataset and basic working of RapidMiner, following operations are performed on the dataset. K-NN Classification Naïve Bayes Classification Decision Tree Association Rules
Views: 31170 RapidMinerTutorial
Build A Classification Model In Random Forests
 
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http://www.salford-systems.com This 15-minute video tutorial will teach you everything you need to know to build your first classification model using Random Forests. Random Forests is a bagging tool that leverages the power of multiple alternative analysis, randomization strategies, and ensemble learning to produce accurate models, insightful variable importance ranking, and laser-sharp reporting on record-by-record basis for deep data understanding.
Views: 28606 Salford Systems
Crypto Mining Pool Settings and Setting Up Free Miner Outage Mobile Text Message Notifications
 
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Get a handy PDF version of the How to Mine Ethereum on Your PC guide at: http://blog.cryptocurrencygear.com/ethereum-mining-guide-pdf Tired of refreshing your miner page to check that they are still up? This video will walk you through setting up your miner pool settings (using Etheremine.org for this example) and using a free IFTTT automation applet to send Text messages directly to your phone any time a miner goes down! The IFTTT applet that you need to configure is linked here: https://ifttt.com/applets/58148089d-send-an-sms-when-a-new-gmail-is-from-a-specific-email-address More great crypto mining content to come. Let me know of any questions / comments / feedback to make things better. Thanks! You can support my channel by picking up some gear for your favorite crypto (like the hats and shirts I rock) at https://cryptocurrencygear.com Donations are also welcomed and very appreciated: Eth - 0x3cE75Eca5Ffa84748B43C999D3375CF2c2561550 BTC - 15JeyWEoxN26J2arKbaz8Jp1Q3r3jELwve LTC - LVEb8m4TMcagcJ3VX6xkFWnk6JFJ5YySEf Thanks! Big Shout out to Lee at IMineBlocks and Omar at Crypt0snews who inspired me to make videos and give back to the community so please check out their channels as well.
Views: 744 Crypto Currency
Using the Natural Language API with C#
 
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Mete Atamel (@meteatamel) shows how you use the Natural Language API with C#. See the relevant codelab for more details: https://codelabs.developers.google.com/codelabs/cloud-natural-language-csharp
Views: 1794 Google Cloud Platform
Smart Resume Parsing System using Data mining approach
 
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The video is about the Various techniques which are used in the project
Views: 1168 Tanmaie Nandurkar
Mail Mining Outlook add in guide
 
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Mail Mining is a freeware Outlook add in that helps you dynamically rank email, control email alerts and file messages efficiently. Mail Mining makes you more productive.
Views: 5730 BrightEye Eran
Twitter Sentiment Analysis
 
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This tutorial shows how to conduct text sentiment analysis in R. We'll be pulling tweets from the Twitter web API, comparing each word to positive and negative word bank, and then using a basic algorithm to determine the overall sentiment. We'll then create several charts and graphs to organize the data. Updated code: http://silviaplanella.wordpress.com/2014/12/31/sentiment-analysis-twitter-and-r/ https://github.com/mjhea0/twitter-sentiment-analysis https://gist.github.com/mjhea0/5497065 TwitteR docs - http://cran.r-project.org/web/packages/twitteR/twitteR.pdf
Views: 64857 Michael Herman
Textual Analysis Tool
 
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Simple textual analysis tool. Retrieves text from Google searches and PDF files and runs textual analysis. Can also perform semantic textual analysis. In its extended version the tool can gather news and other type of data from multiple sources and perform various types of textual analysis which can be used in investments. Parameters are takes from MS Excel (*.xlsx) files.
Usando Text Mining para analizar el Quijote - Parte 1
 
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Este es el primer video de mi clase de aplicaciones de cadenas de markov. En el cual uso tecnicas de text mining para constuir un grafo de las palabar que aparecen en el quijote. El tutorial esta creado en el lenguaje de programación R y el ide Rstudio. En este primer video de la serie aprenderemos como cargar un libro y como remover espacios en blanco, puntuaciones y otros filtros comunes. https://www.dropbox.com/s/o6t72jr9ctpu129/quijote.txt?dl=0 http://rpubs.com/chzelada/368112 ===Suscribete a nuestro canal en youtube=== http://www.youtube.com/chzelada ===Siguenos en Facebook=== http://www.facebook.com/wikimatematica http://www.facebook.com/academatica ===Visitas nuestros sitios=== http://www.academatica.com
Views: 658 Academatica
How to run the text mining (tm) package in R
 
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Link to the article http://goo.gl/w24W2 . Link to the script http://goo.gl/gpUYR
Views: 17441 resinnovstation
Lecture 6 - Trend Detection In Twitter Social Data (Analyzing Big Data With Twitter)
 
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http://blogs.ischool.berkeley.edu/i290-abdt-s12/ Lecture 6: Kostas Tsioutsiouliklis on Twitter Trends and how to compute them Lecture notes: http://blogs.ischool.berkeley.edu/i290-abdt-s12/files/2012/08/Kostas_Trends_Sept_13_2012.pdf Course: Information 290. Analyzing Big Data with Twitter School of Information UC Berkeley Prof. Marti Hearst Course description: How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered. This is a hands-on project course in which students are expected to form teams to complete intensive programming and analytics projects using the real-world example of Twitter data and code bases. Engineers from Twitter will help advise student projects, and students will have the option of presenting their final project presentations to an audience of engineers at the headquarters of Twitter in San Francisco (in addition to on campus). Project topics include building on existing infrastructure tools, building Twitter apps, and analyzing Twitter data. Access to data will be provided.
Data Access in KNIME: File Reader
 
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This video shows how to read text files. Example workflows on how to use the Table Reader node can be found on the EXAMPLES server within the KNIME Analytics Platform (www.knime.org) under 01_Data_Access/01_Common_Type_Files Previous: - "Annotations and comments" https://youtu.be/AHURYB_O8sA Next: - How to read a .table formatted files https://youtu.be/tid1qi2HAOo
Views: 6524 KNIMETV
Extract Facebook Data and save as CSV
 
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Extract data from the Facebook Graph API using the facepager tool. Much easier for those of us who struggle with API keys ;) . Blog Post: http://davidsherlock.co.uk/using-facepager-find-comments-facebook-page-posts/
Views: 206756 David Sherlock
WordStat - Frequencies Page
 
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Overview of the frequencies page of WordStat content analysis and text mining software
Membuat Program Untuk Mengunggah File Dengan Format PDF, Tokenisasi, Stopword Removal Dan Stemming
 
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Dewi Rahayuni 16.01.63.0035 Indriani 14.01.53.0129 Siti Adha Zuliani 14.01.53.0108
Views: 77 Dewi Rahayuni
How To Use Extract Data & Text From Multiple Text Files Software
 
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To download, please go to http://www.sobolsoft.com/extractdata/
Views: 679 Peter Sobol
Create a review analyzer with Watson Discovery
 
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https://github.com/IBM/watson-second-opinion This video is based on the code in the github link above: Create a Node.js app that takes the reviews from an online shopping website, Amazon, and feeds them into the Watson Discovery service. The reviews are enriched, and analyzed with Watson's natural language understanding to give each a sentiment analysis of -1 to 1. From -1 being the most negative to 1 being the most positive, this app normalizes the sentiments written within the reviews to give the user an aggregated view of the language within the reviews. This way, the customer can have a way to decide between two products that have similar review ratings.
Views: 120 Horea Porutiu
How PDF2Data service works (invoice processing and data extraction software)
 
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See how PDF2Data extracts data from documents. PDF2Data can be used for invoice processing, data extraction, text extraction etc... Please, see video in HD quality. http://www.cloudforpeople.com
Views: 1913 cloud4people
111. web scraping - getting google search data | Python | Hindi
 
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In this video, you'll learn about how we can get google search data in our Python program. The language used in this video is Hindi. If you've any problem related to this video, then please let us know in the comment box. Contact us - Facebook - https://facebook.com/programmingcage Email - [email protected] Instagram - techgram_academy Twitter - https://twitter.com/TechgramA our other courses related to Python - ( हमारे पाइथन से संभंधित और कोर्सेज ) 1. Learn web development using Django ( वेब डेवलपमेंट कोर्स Django का प्रयोग करके ) - https://www.youtube.com/playlist?list=PLjC8JXsSUrrj6FIgFL2k7rPdjgllkc3rL 2. Learn GUI development using Tkinter ( Python Tkinter का प्रयोग करके GUI डेवलपमेंट ) - https://www.youtube.com/playlist?list=PLjC8JXsSUrri0XWbCGffJ5to1P40hebu2 3. Complete Basics of Python ( पाइथन प्रोग्रामिंग लैंग्वेज शुरुआत से सीखें ) - https://www.youtube.com/playlist?list=PLjC8JXsSUrriq4lEMtDruOYojZdrMKY6y 4. Python basics in one video ( पाइथन के बेसिक्स एक वीडियो में ) - - https://youtu.be/02-S9L4IetQ
Views: 182 Tech-Gram Academy
K Nearest Neighbor Algorithm (KNN) | Data Science | Big Data
 
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In this video you will learn about the KNN (K Nearest Neighbor Algorithm). KNN is a machine learning / data mining algorithm that is used for regression and classification purpose. This is a non parametric class of algorithms that works well with all kinds of data. The other types of data science algorithms that works similar to KNN are the Support vector machine, Logistic regression, Random forest, decision tree, Neural Network etc. ANalytics Study Pack : https://analyticuniversity.com Analytics University on Twitter : https://twitter.com/AnalyticsUniver Analytics University on Facebook : https://www.facebook.com/AnalyticsUniversity Logistic Regression in R: https://goo.gl/S7DkRy Logistic Regression in SAS: https://goo.gl/S7DkRy Logistic Regression Theory: https://goo.gl/PbGv1h Time Series Theory : https://goo.gl/54vaDk Time ARIMA Model in R : https://goo.gl/UcPNWx Survival Model : https://goo.gl/nz5kgu Data Science Career : https://goo.gl/Ca9z6r Machine Learning : https://goo.gl/giqqmx Data Science Case Study : https://goo.gl/KzY5Iu Big Data & Hadoop & Spark: https://goo.gl/ZTmHOA
Views: 6555 Big Edu
Assistente 2 do software Text Mining Suite - Comparação entre Textos
 
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Este é o 2o Asssitente (Wizard) do software Text Mining Suite. Ele compara textos, apresentando palavras comuns e palavras exclusivas de cada texto.
Views: 245 intextmining
Using ERIC for Systematic Evidence Reviews
 
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This video demonstrates how to conduct a systematic evidence review using the search tools available on the ERIC website at eric.ed.gov.
Views: 681 SearchEduResources
Step 1. Load an input text file (option A)
 
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SiMX TextConverter, Setting Up a Conversion Process Step by Step, Setting Up a Conversion Process Step by Step, Option A (click the input icon). This is a video supplement to the help documentation located at https://sites.google.com/site/simxsoftware/Home
Views: 231 ponimed
Weka Data Mining Tutorial for First Time & Beginner Users
 
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23-minute beginner-friendly introduction to data mining with WEKA. Examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine. Update 7/20/2018: I put data files in .ARFF here http://pastebin.com/Ea55rc3j and in .CSV here http://pastebin.com/4sG90tTu Sorry uploading the data file took so long...it was on an old laptop.
Views: 464999 Brandon Weinberg
How to Extract Text From Image/Pictures | Easiest Method | No software Required
 
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Hi Friends,We may come across the situation when we need to extract text from images, or we may need to convert some scanned copy into text. Converting the scanned copy to text is done using Optical Character Recognition Software which is not free most of time. You need to spend some good amount of money to get them and convert images to text.However paying the hefty price just for a single usage does not seems to be a good idea. In this video, I will show you how to extract text from Image for free using Google Drive! Google Drive provides you the OCR technology and we make use of it to convert images to text. Let us see steps which we need to follow to convert images to text or to convert PDF files to text. On your computer, go to drive dot google dot com.Login with your google account. Click on the New button and select File Upload to upload images file which you want to convert to text. Select the particular image file and it gets uploaded to Google Drive. Once the files gets uploaded, right click on the image file and move towards Open with Google Docs. Now, new tab opens with the image surrounded by the blue border and the corresponding editable text at the bottom. You can resize the blue border, based on the content which you want. Once you are sure about the required content, remove the image from the tab, save the remaining text and close the tab.Once converted, you have an option to edit it in Google Drive, or download it in your preferred format and edit in your computer with your favourite text editor. Please note that the accuracy of the text transcribed may vary depending on the quality of the image being read from the words in it. Clear images with high contrast are likely to give best results. Also, do note that you can only upload a file sized 2MB and below, and only the first ten pages of a PDF file will get converted. If you have a PDF file with tons of pages, do split it into several files before uploading. I hope you liked the information shared on this video. For more such videos,you can subscribe to my channel Tech Curious. Thanks for watching
Views: 315 TechCurious
How to install KNIME Analytics Platform on Mac
 
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This video shows how to install the KNIME Analytics Platform core on Mac, by choosing one of the 4 installation options. - Installation of KNIME Analytics Platform on Linux available at https://youtu.be/wibggQYr4ZA - Installation of KNIME Analytics Platform on Windows available at https://youtu.be/yeHblDxakLk Next: "How to install Extensions in KNIME Analytics Platform" https://youtu.be/8HMx3mjJXiw "Getting around the KNIME Welcome Page" https://youtu.be/Jib9t6hK6Bg
Views: 1606 KNIMETV
Broken Link Finder Demo for Broken Link Building
 
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http://www.brokenlinkbuilding.com industrial-strength broken link prospector from the company that brought you http://linkprospector.citationlabs.com -finds dead and parked pages or sites with links pointed at them -scrapes and assesses the now-dead page and grades their relevance based on your KWs -enables you to reserve opportunities so other prospectors can't see them within our system
Views: 8704 Garrett French CL
Real time Twitter Opinion Mining and Tweet Clustering in Java ( Netbeans)
 
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This work uses SentiStrength Database with an improved algorithm for sentiment analysis in tweets. It also uses advanced pattern matching techniques with automata, weight enhancement of senti words based on preceding terms like "very" "Nice". It reverses the polarity based on negative words before senti words. Not Good is considered as bad. Refer my paper for more details: http://www.ijera.com/papers/Vol2_issue1/BM021412416.pdf
Views: 5744 rupam rupam
how to extract text from website
 
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this tutorial show you how to extract text from any website.
Views: 171 A.B.M. MYDUL ISLAM
How-to No. 24 — Automate saving and recognition of documents attached to incoming emails.
 
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Tired of manual saving of documents received via e-mail? Waste a lot of time on search of a needed document which was received in graphic format? Then you should be interested in ABBYY FineReader 11 Corporate Edition. It can automatically recognize all documents attached to received emails, convert them into searchable pdf and save in appropriate folder! In this screencast it is shown how to — separate emails with needed documents in attachment. — configure Hot Folders for monitoring of an Outlook folder — automatically recognize attached tiff, jpeg, pdf files — convert attached tiff, jpeg, pdf files into searchable pdf — automatically save converted documents in needed folders — Get ABBYY FineReader 11 CE at http://www.finereader.com — Enjoyed this screencast? Like our FB page at http://www.fb.com/ABBYY3A !
Views: 566 yexiTixey
Автоматическое извлечение фактов из текста на примере сервиса Яндекс.Пресс-портреты
 
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Татьяна Ландо (Яндекс) В докладе было в общих чертах рассказано о том, какого рода информацию можно извлекать автоматически из текстов и какие методы для этого используются. Так же был дан обзор задач, связанных с извлечением фактов. Подробнее были рассмотрены технологии, лежащие в основе сервиса Яндекс.Пресс-портреты.
Views: 147 Tatiana Lando

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