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Dogpile Dictionary

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©1996-2017 Roedy Green of Canadian Mind Products

Disclaimer

This essay does not describe an existing computer program, just one that should exist. This essay is about a suggested student project in Java programming. This essay gives a rough overview of how it might work. I have no source, object, specifications, file layouts or anything else useful to implementing this project. Everything I have prepared to help you is right here.

This project outline is not like the artificial, tidy little problems you are spoon-fed in school, when all the facts you need are included, nothing extraneous is mentioned, the answer is fully specified, along with hints to nudge you toward a single expected canonical solution. This project is much more like the real world of messy problems where it is up to you to fully the define the end point, or a series of ever more difficult versions of this project and research the information yourself to solve them.

Everything I have to say to help you with this project is written below. I am not prepared to help you implement it; or give you any additional materials. I have too many other projects of my own.

Though I am a programmer by profession, I don’t do people’s homework for them. That just robs them of an education.

You have my full permission to implement this project in any way you please and to keep all the profits from your endeavour.

Please do not email me about this project without reading the disclaimer above.

This project is similar technically to the Bookstore Referral Project and the commercial Dogpile search engine that works by asking several other search engines to do its work for it in parallel.Your project, should you decide to take it, is to automate this process. There are several tasks:
  1. Find all the online dictionaries and write code to scan them and convert the information into a standard format. The dictionary entries will be constantly changing and the dictionary formats too will be more slowly changing. You will thus likely look words up online rather than batch convert the dictionaries, though that two may be feasible, if you have a central server. For a start, deal only with dictionaries organised with the <dl><dt></dt><dd></dd></dl> HTML (Hypertext Markup Language) glossary tags.
  2. Given the particular translation task, select a subset of dictionaries to use.
  3. Based on the user’s past success and the general population’s past success, rank the dictionaries so that you try the best first. You might consider using parallel tasks to help you, potentially running on many different servers.
  4. If that search fails, try an intermediate language. You get a combinatorial explosion here, so I don’t think using a 3 step process with two intermediate languages would be feasible.
  5. Package this up much like the Bookstore Referral Applet. The code must be frequently updated, so ensuring users get the freshest code is quite important. Unfortunately Applets may not talk to multiple foreign servers, so it may be simplest to make this an application.
  6. Maintain a local cache of words already looked up so you can find them quickly without going to the Internet.
  7. Devise code to peel off standard suffixes and prefixes when you can’t find a word, to get at the root which may be in one of the dictionaries.

I debated whether to warn you that this project, done properly, is trickier than it first looks. Just the same, it needs to be done, even if done badly. Working prototypes may encourage more serious attempts. I am working on this myself. I have written a prototype for Esperanto-English that at present uses but a single dictionary. Have a look at my Esperanta Tradukilo Vortope.

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