Sunday, October 25, 2009

Most Efficient Food in Cafe World

2009-Nov-23 Updated with new foods. Changed net income to reflect the 15 coin charge for cleaning the stove.

2009-Oct-31 Updated with crab bisque, halibut and peking duck.

My kids like this game. I needed a way to make it more interesting. Here is the list of food they can make, in order of efficiency.
food                     cost   income  net  hours   minute secosnds  net/seconds
bacon cheeseburger         15   52      22              5       300        0.07
overstuffed peppers      1300 4300    2985    12              43200        0.07
kung pao stir fry         600 1600     985     4              14400        0.07
king crab bisque         1300 6685    5370    24              86400        0.06
chips and guacamole        10   36      11              3       180        0.06
super chunk fruit salad    35  100      50             15       900        0.06
atomic buffalo wings      350  960     595     3              10800        0.06
buttermilk pancakes       250  400     135             45      2700        0.05
tony's classic pizza      400 1300     885     5              18000        0.05
chicken gyro and fries     45   88      28             10       600        0.05                               
voodoo chicken salad      700 2675    1960    12              43200        0.05
herbed halibut            700 4500    3785    24              86400        0.04
crackling peking duck     900 3600    2685    18              64800        0.04
jumbo shrimp cocktail      65  148      68             30      1800        0.04
savory stuffed turkey     700 3600    2885    22              79200        0.04
tikka masala kabobs       215  360     130     1               3600        0.04
spagetti and meatballs    450 1375     910     8              28800        0.03
spitfire roasted chicken  600 3200    2585    24              86400        0.03
french onion soup         175  615     425     4              14400        0.03
triple berry cheesecake   400 1650    1235    12              43200        0.03
caramel apples             90  300     195     2               7200        0.03
homestyle pot roast      1800 5750    3935    48             172800        0.02
staked steak              300 2010    1695    24              86400        0.02
pumpkin pie               200 1060     845    12              43200        0.02

Friday, October 23, 2009

Forest Options of ps Command

Some computer system that I use have a ptree (or process tree) command. It is very nice to see processes and their children. In fact, I am disappointed when working on systems without ptree. And then I learned about the forrest option of the ps command.

ps faux

Wonderful. Makes me happy. RTFM!

Wednesday, October 21, 2009

United States' Official Repository of Foreign Place-names (more entity extraction fun) - This is a fantastic resource if you need a list of place names. You can download a file containing names covering the whole world.

Friday, October 16, 2009

Names in Non-English Languages (continuing a theme)

The title is horrible but clear, at least to me. I only have one link so far, but it's a good one.
  • - There's an election coming up in Thailand on December 23rd and the streets are lined with election posters. As a bit of an i18n geek, I find it interesting that the posters almost all make the candidates' first names at least twice as big as their last names. If you're also an i18n geek, your reaction might well be: "it must be because Thais write their family name first, followed by their given name". But you would be wrong. Thais have a given name and a family name; the given name is written first, and the family name last.

Monday, October 12, 2009

Entity Extraction Links (also Named entity recognition)

  • Websites
  • Software
    • Ruby
    • - Originally by Eric Anderson, some of that code still remains. If you’re not into this version, check his out at See Hypomodern::FlexAttributes for usage information.
  • - Calais is a rapidly growing toolkit of capabilities that allow you to readily incorporate state-of-the-art semantic functionality within your blog, content management system, website or application.
  • - Open Source Information Extraction from The University of Sheffield; ANNIE is an open-source, robust Information Extraction (IE) system which relies on finite state algorithms. ANNIE consists of the following main language processing tools: tokeniser, sentence splitter, POS tagger, named entity recogniser.
  • - Jeff Dalton's List of Java Open Source NLP and Text Mining tools
  • - GATE as an architecture suggests that the elements of software systems that process natural language can usefully be broken down into various types of component, known as resources
  • - AutoMap is a text mining tool that enables the extraction of network data from texts. AutoMap can extract three types of information: content analytic (words and frequencies), semantic networks, and meta-networks.
  • - SRA developed NetOwl®, a suite of rich text mining tools, to discover and extract the knowledge found in free-form text documents and turn it into actionable information. NetOwl has been refined over more than a decade of research and development. Our team of researchers and engineers continue to expand NetOwl’s capabilities to keep pace with evolving information needs.
  • - Out of the box, Inxight ThingFinder automatically identifies and extracts more than 35 key entities - such as people, dates, places, companies or other things - from any text data source, in multiple languages. This ability to automatically identify and classify relevant entities makes ThingFinder one of the most powerful text analysis and extraction tools on the market. Using Inxight ThingFinder, developers can maximize and extend the value of their applications by enabling end-users to quickly find the most important pieces of information within large volumes of documents.
  • - UIMA enables applications to be decomposed into components, for example "language identification" => "language specific segmentation" => "sentence boundary detection" => "entity detection (person/place names etc.)". Each component implements interfaces defined by the framework and provides self-describing metadata via XML descriptor files. The framework manages these components and the data flow between them. Components are written in Java or C++; the data that flows between components is designed for efficient mapping between these languages.
  • - Named entity recognition (NER) (also known as entity identification and entity extraction) is a subtask of information extraction that seeks to locate and classify atomic elements in text into predefined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
  • - Entity Extraction is the process of automatically extracting document metadata from unstructured text documents. Extracting key entities such as person names, locations, dates, specialized terms and product terminology from free-form text can empower organizations to not only improve keyword search but also open the door to semantic search, faceted search and document repurposing. This article defines the field of entity extraction, shows some of the technical challenges involved, and shows how RDF can be used to store document annotations. It then shows how new tools such as Apache UIMA are poised to make entity extraction much more cost effective to an organization.
  • - How Entity Extraction is Fueling the Semantic Web Fire; short commentary on Apache UIMA and a few other tools.