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Google Image Result for. Some questions on Text Analysis : MachineLearning. Hi, I hope this is the right subreddit.

Some questions on Text Analysis : MachineLearning

For a small project I'd like to sift through a large amount of articles and tag them according to category (Interview, News article etc.) and occurrence of a preset of notable items ( Names, Brands ). Linguamatics' I2E Text Mining Platform Chosen by FDA - Linguamatics, a leader in natural language processing (NLP)-based text mining, has announced that the FDA’s Center for Drug Evaluation and Research (CDER) has licensed its I2E text mining platform to support laboratory research efforts on drug safety.

Linguamatics' I2E Text Mining Platform Chosen by FDA -

Financial details of the agreement were not disclosed During the term of the license, CDER will use I2E to mine published literature and drug product labels to answer questions relating to a range of biomedical topics, including drug toxicity mechanisms and disease processes. I2E’s NLP-based querying capabilities, coupled with its scalability and flexibility, mean it is ideally suited to answering many challenging, high value questions in life sciences and healthcare by unlocking knowledge buried in the scientific literature and other textual information. (Read Full Article) AlchemyAPI - Transforming Text Into Knowledge. Psychographic text analysis classifier for values (i.e. worldviews) - Mattias Östmar.

Keywords Alone Are Not Enough: Why Real Text Analytics Matters. LP Insights Real-Time Business Intelligence. Today’s online businesses have no shortage of customer data: chat transcripts, emails, call recordings, CRM notes, web analytics, survey data, social media including blogs, Facebook, and Twitter… But despite the extraordinary amount of data available, translating this information into holistic, accurate, and actionable insights eludes most organizations.

LP Insights Real-Time Business Intelligence

DiscoverText - A Text Analytic Toolkit for eDiscovery and Research. Text Analysis. Google Image Result for. Speed, Scale, Automation and Comprehension: The True ROI of Text Analytics — Nectarine Imp. Natural Language Processing HUB – News about NLP. Good business: Scalable document management lends solid legal footing. Scalable document management is handy when accommodating changing numbers of documents, users and locations. Attensity Pipeline: Social Media Conversations Analyzed, In Real-Time And In The Cloud At Scale. For many companies, understanding what’s being said about them or their products and services in the real-time social media space will only become more important.

Attensity Pipeline: Social Media Conversations Analyzed, In Real-Time And In The Cloud At Scale

Vendors of social and customer analytics solutions are aiming to fill the need: A couple of weeks ago, heavyweight Salesforce said the Twitter firehose will be funneled to its social analytics arm Radian6. Last week, Attensity announced the Attensity Pipeline, which is its foray into providing a semantically annotated social media data stream in real-time, as a cloud service, tapping into the full Twitter firehose as well as public Facebook and Google Plus posts, blogs, forums, and video and review sites.

Converseon Gives Big Data a Human Touch and Added Value. Social data provides important insights into the desires, habits and inclinations of customers.

Converseon Gives Big Data a Human Touch and Added Value

While, many platforms survey customer remarks on social media outlets like Facebook and Twitter, such technology is often limited in its “word-spotting” approach which, taken out of context, may yield results irrelevant to a client’s research aims. Converseon’s new text analytics service ConveyAPI combines the speed, processing capacity and scalability of data software with the accuracy, understanding and analyses of social conversations that only a human touch can provide. ConveyAPI addresses the challenge Dr. Google Image Result for. What can text analytics learn from Crowdsourcing — Nectarine Imp. Or: What we can learn from crowdsourcing Text Analytics can learn a lot from a competing system for getting answers to analytical-like questions.

What can text analytics learn from Crowdsourcing — Nectarine Imp

Crowdsourcing is a voluntary effort where collaboration to solve a problem is key. Text analytics is a sort of involuntary collaboration of multiple voices gathered together in a corpus. Dave’s Adventures in Business Intelligence » Go, Universe, Go! I have been selected to speak at the 2012 SAP BusinessObjects User Conference (twitter tag #SBOUC).

Dave’s Adventures in Business Intelligence » Go, Universe, Go!

My topic this year will be a follow-up of sorts to a topic I did last year called, “Designer Essentials.” In the essentials topic I went over the basic requirements of universe design (setting up a connection, adding tables, building joins, and so on). I also covered additional steps that have to be done in order to ensure the correct results, like making sure all SQL traps are resolved. My session this year covers the next step, which answers the question: Predictive Analytics Use Outside Legal Industry. In the legal industry, the use of analytics has been on the rise.

Predictive Analytics Use Outside Legal Industry

It’s most often used to speed up document review. Using text analytics, a small, representative data set can be used to quickly identify similar documents in a much larger population, allowing for more targeted, faster document review. Outside of the legal industry though, the technology is also gaining momentum and is seen as a great use for big data and cloud technologies. reports on analytics’ use to predict future events or data patterns such as in fraud detection, production management, or by marketing (for analyzing customer retention). It seems in all these scenarios, just as in analytics’ use in the legal review space, the motivator is using technology to cut costs. See the article for further reading here. HStreaming and Friends Lexalytics Text Analytics Solution to deliver a novel of Data. 0 20px 10px Hadoop Summit / Santa Clara, CA (PRWEB) June 13, 2012 Lexalytics, a provider of text analytics and feel and HStreaming, in real-time data analysis platform that is powered by Hadoop, today announced a partnership to deliver a highly scalable, low latency Text Analytics Data Solutions General.

This solution enables companies to quickly analyze large text data and their connection with structured data and unstructured others to view the full analysis. solution unparalleled in the market. Combined solution allows customers to analyze thousands of new documents at the same time and to disclose what is in them in real time. What is noisy text? - Definition from Noisy text is an electronically-stored communication that cannot be categorized properly by a text mining software program.

What is noisy text? - Definition from

In an electronic document, noisy text is characterized by a discrepancy between the letters and symbols in the HTML code and the author's intended meaning. Noisy text does not comply with rules the program uses to identify and categorize words, phrases and clauses in a particular language. API Directory - ProgrammableWeb. UC-enabled "Multimodal Customer Experiences" Copyright (C) Unified-View, All Rights Reserved.June 7, 2012 A recent analysis of contact center applications moving into the "cloud" showed that IVR (self-service) applications was the application that was most frequently shifted off premise to a "cloud" based service.

UC-enabled "Multimodal Customer Experiences"

This highlights how customers will be accommodated with more flexible self-service options as they start using multimodal smart phones and tablets, rather than traditional voice-only telephones. As I suggested in a previous post, mobile customers will now require an integration of various customer service experiences. It will be a combination of how self-service interfaces are designed for smartphones and tablets, as well as how live assistance is accessed and supported when needed.

It also includes proactive, outbound “notifications” and alerts to mobile customers from automated business process applications, and what response options can be given to the mobile recipient. 1. What Customers Really Need. I think, therefore I am an Artificial Intelligence. If All Human Souls posess Conciousness, then (as I have unassailably logically proved symbolically) according to the many experimental results of the Classic Young's Double-Slit Experiment in technical jargon: I.

'Consciousness' is sometimes an unobserved Wave, when a particle is detected (which-way information) can sometimes maintian it's quantum state regardless. II. 'Consciousness' is whether measured (which-way info.) or no can be detected or not correspondingly. III. IV. V. These results are the logical consequences of the data from literally 10s of thousands of experiments studying Young's DS Experiment.

Next this shall be tied to the logical interpretation for 'Consciousness' on Modern Times, using the LHC proton exper. results in technical, precise , logical , jargon. Classification is a few value proposition for text analytics - it allows users to quickly drill into articles of interest and look at trends over time. Setting up a classification scheme can be a lot of work. The common techniques are: Using queries to bucket documents Using a machine learning model based on tagged document sets.

Model-based categorization starts with humans marking content by all of the categories they satisfy. Something like "Buying kimonos while on holiday" should fit into Travel and Fashion. Query-based categorization starts with humans trying out search terms that should define the category and seeing how their retrieval works. Roistr - Semantic Analysis and Text Analytics. Predictive Analytics: NeuralNet, Bayesian, SVM, KNN. Continuing from my previous blog in walking down the list of Machine Learning techniques. In this post, we'll be covering Neural Network, Support Vector Machine, Naive Bayes and Nearest Neighbor. Again, we'll be using the same iris data set that we prepared in the last blog.

Neural Network Neural Network emulates how the human brain works by having a network of neurons that are interconnected and sending stimulating signal to each other. In the Neural Network model, each neuron is equivalent to a logistic regression unit. The tuning parameters in Neural network includes the number of hidden layers, number of neurons in each layer, as well as the learning rate. There are no fixed rules to set these parameters and depends a lot in the problem domain. The learning happens via an iterative feedback mechanism where the error of training data output is used to adjusted the corresponding weights of input. An interesting philosophical kerfuffle. Interesting comments by David Berry at Stunlaw on Object-Oriented Ontology (OOO) based around what is the philosophical purpose of OOO and what are the political questions that arise from a clarification of that philosophical purpose.

What do your online conversations really say? Beyond Goals: Site Search Analytics from the Bottom Up. Avinash Kaushik demonstrated that site search analytics (SSA) is a powerful tool you can use to assess customer intent quantitatively. Insightful analytics blog. Text analytics broadens insight possibilities – Digital Reasoning. Using Google's N-Gram Corpus. Turns out I'm not crazy. Text Analytics for Unstructured Information Management - Information Management Newsletters Article. Popcomm-ontology - A population and community ontology. Call: Journal of Robotics 2012 issue on Cognitive and Neural Aspects in Robotics with Applications. Call for Papers: Special Journal Issue on Cognitive and Neural Aspects in Robotics with Applications 2012 (CNAR’12), Journal of Robotics. Improving the Productivity of Knowledge Workers. The term content classification is best understood in an enterprise information context, defined by the following concepts.

Taxonomy is the hierarchical representation of topics of interest. Brain of mat kelcey. Friday Data Story: Manufacturing Ontologies and Semantic Web. It’s been awhile since I last posted a “Friday Data Story”. These usually present a topic that expand the “data” horizons of software use and also provide a bit more perspective. The topic of “ontologies” has already been discussed on this blog. Navigate to Inforbix Product Data Semantics if you need a reminder as a starting point to today’s post. “Ontology” may sound complex, but it actually represents a simple concept: the semantics of data. The following workshop material caught my attention a few weeks ago, Ontology and Semantic Web for manufacturing . Developing innovative and competitive products in the globalized world requires an orchestrated Product Life Cycle Management (PLM). Optimizing Semantic Search. Home > News > Optimizing Semantic Search If you haven’t applied for a job in the past few years, know that things have changed – significantly.

Sports Are The Semantic Focus In Britain At The BBC And In Brazil At Globo. Terkait – Chrome Widget for semantic analysis of web content. Powered by VIE. Urgent tasks of modern Text Linguistics. Semantic Arts. Text Analytics. Information Interaction.