Named-entity recognition Named-entity recognition (NER) (also known as entity identification, entity chunking and entity extraction) is a subtask of information extraction that seeks to locate and classify elements in text into pre-defined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc. Most research on NER systems has been structured as taking an unannotated block of text, such as this one: Jim bought 300 shares of Acme Corp. in 2006. And producing an annotated block of text that highlights the names of entities: [Jim]Person bought 300 shares of [Acme Corp.]Organization in [2006]Time. In this example, a person name consisting of one token, a two-token company name and a temporal expression have been detected and classified. State-of-the-art NER systems for English produce near-human performance. Problem definition[edit] Certain hierarchies of named entity types have been proposed in the literature. Formal evaluation[edit]
Stanford shows off their federated search tool » Federated Searc 26Jan Blog sponsor Deep Web Technologies built a federated search tool for Stanford University. I was involved with the first prototype and I’m proud of what the Stanford/Deep Web Technologies partnership has accomplished. My involvement with the Stanford federated search tool was multi-faceted. Tags: federated search
World Service Radio Archive Prototype OPAC2.0 – OpenCalais meets our museum collection / auto-tagging and semantic parsing of collection data Today we went live with another one of the new experimental features of our collection database – auto-generation of tags based on semantic parsing. Throughout the Museum’s collection database you will now find, in the right hand column of the more recently acquired objects (see a quick sample list ), a new cluster of content titled “Auto-generated tags”. We have been experimenting with Reuters’ OpenCalais web service since it launched in January. Here’s a brief description of what OpenCalais is in a nutshell from their FAQ - From a user perspective it’s pretty simple: You hand the web service unstructured text (like news articles, blog postings, your term paper, etc) and it returns semantic metadata in RDF format. Whilst we store the RDF triples and unique hash, we are not making use of these beyond display right now. Obviously the type of content that we are asking OpenCalais to parse is complex. The OpenCalais tags generated are as follows –
Mafait.org - project Thinknowlogy - Fundamentally designed Artificial Intelligence How-To: Search the Social Web – Ultimate Toolkit Are you using content marketing as part of your digital strategy to grow your business? If so, you're not alone. According to the Content Marketing Institute, the lion's share of marketers (some 92%) report using content marketing. In the fast moving world of digital strategy, things are always changing. What should you expect in 2014 to change in the world of content marketing? Hana Abaza of Uberflip has put together an infographic detailing five key content marekting trends for the coming year. 1. 2. 3. 4. 5.
Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials Content Manager Submitted by Anonymous on Mon, 04/14/2008 - 15:49. For a general overview of Calais please take a moment to read the About section. If you’d just like to jump in and learn how Calais is relevant to developers, read on. Content and Collection Management This is a big area that covers everything from corporate knowledge management to librarians to collections at museums. Given the range of needs for this group as a whole, we’re simply going to try and point you in some useful directions. What Calais Does Different areas of this site can provide you with much deeper detail, so let’s keep it simple for the time being. Calais enhances your content with rich semantic metadata. Metadata in and of itself is not too interesting. Tag Your Complete Historical Archives in Hours Perhaps you’re a complete convert to the value of tagging your content and are doing a great job with new material – but what about the tens of thousands to millions of pieces of historical content you have already produced?
LingPipe Home How Can We Help You? Get the latest version: Free and Paid Licenses/DownloadsLearn how to use LingPipe: Tutorials Get expert help using LingPipe: Services Join us on Facebook What is LingPipe? LingPipe is tool kit for processing text using computational linguistics. LingPipe is used to do tasks like: Find the names of people, organizations or locations in newsAutomatically classify Twitter search results into categoriesSuggest correct spellings of queries To get a better idea of the range of possible LingPipe uses, visit our tutorials and sandbox. Architecture LingPipe's architecture is designed to be efficient, scalable, reusable, and robust. Latest Release: LingPipe 4.1.2 Intermediate Release The latest release of LingPipe is LingPipe 4.1.2, which patches some bugs and documentation. Migration from LingPipe 3 to LingPipe 4 LingPipe 4.1.2 is not backward compatible with LingPipe 3.9.3. Programs that compile in LingPipe 3.9.3 without deprecation warnings should compile and run in Lingpipe 4.1.2.
Bing Goes The iPhone. Still Great For Porn. Since the dawn of Bing, it’s been exceptionally good at one thing: Finding porn. Its new iPhone app, which launched tonight in the App Store, is no different. By default, the app has a Safe Search setting of “Moderate.” Searching for “porn” this way yields several promising results. However, with just two clicks, any kids can turn off safe search and off they go! I love this for two reasons: 1) The app is rated 4+, yet it’s super simple to gain access to hardcore porn in a few clicks. To be fair, Google’s iPhone app also allows you to search for porn. All that said, the Bing app is actually quite nice. Both images below taken on a search for “porn” with safe search turned off. 700 Free Movies Online: Great Classics, Indies, Noir, Westerns Watch 4,000+ movies free online. Includes classics, indies, film noir, documentaries and other films, created by some of our greatest actors, actresses and directors. The collection is divided into the following categories: Comedy & Drama; Film Noir, Horror & Hitchcock; Westerns (many with John Wayne); Martial Arts Movies; Silent Films; Documentaries, and Animation. Free Comedy & Dramas 125 Korean Feature Films — Free — The Korean Film Archive has put on YouTube over 100 Korean feature films, including Im Kwon-taek’s Sopyonje and Hong Sangsoo’s The Day the Pig Fell Into a Well. collective:unconscious — Free — Five indie filmmakers adapt each other’s dreams for the screen. Free Hitchcock, Noir, Horror & Thriller Films A Bucket of Blood - Free — Roger Corman’s classic comedy/horror film set in Bohemian San Francisco. Find a complete collection of Film Noir movies here and Alfred Hitchcock movies here. Free Kung Fu & Martial Arts Films
Developer Submitted by Anonymous on Mon, 04/14/2008 - 15:50. For a general overview of Calais please take a moment to read the About section. If you’d just like to jump in and learn how Calais is relevant to developers, read on. Developers want… Just the facts, please. What it is Calais is a big initiative with a lot of components. Entities are things like people, places, companies, geographies. What you do with it is up to you. Get a key The Calais API needs a key. Read the documentation The API is extensively documented. Get some tools The Calais team and members of the Calais community have produced everything from Java code samples to working applications to libraries for PHP, Ruby and others. Communicate, ask questions, brag This site has a Showcase to share your creations and Forums to ask questions, answer questions and generally talk.
AutoMap: Project Overview | People | Sponsors | Publications | Hardware Requirements | Software | Training & Sample Data AutoMap is a text mining tool developed by CASOS at Carnegie Mellon. Input: one or more unstructured texts. Output: DyNetML files and CS files. AutoMap enables the extraction of information from texts using Network Text Analysis methods. AutoMap exists as part of a text mining suite that includes a series of pre-processors for cleaning the raw texts so that they can be processed and a set of post-processor that employ semantic inferencing to improve the coding and deduce missing information. AutoMap uses parts of speech tagging and proximity analysis to do computer-assisted Network Text Analysis (NTA). AutoMap subsumes classical Content Analysis by analyzing the existence, frequencies, and covariance of terms and themes. AutoMap has been implemented in Java 1.7. It can operate in both a front end with gui, and backend mode. Main functionalities of AutoMap are: "From Texts to Networks"
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