A Glance at PLuTO’s IPTranslator Patent Translation Tool

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Today we’ll give you a quick overview of PLuTO‘s IPTranslator tool. This tool provides a simple and unobtrusive way to access customizable machine translations tailored for use while you patent search.

At the Intellogist Blog, we’ve been continually fascinated about the state of machine translation for patent documents. We examined the Future of Patent Translations (Human or Machine?). We’ve taken a look at two specialized machine translation tools: Patent Translate and 2lingual. We’ve conducted a more comprehensive comparison between the machine translation capabilities of Google vs. Bing (second part found here). We’ve discussed expert human patent translation services with Sonja Olsen and Lisa Louis at Landon IP in a two part profile, considering what advantages human translation still retains over machine translation.

So today, sit back and enjoy the latest chapter in our patent translation tale: a look at the very capable IPTranslator!

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Free Machine Translation Round-up: Patent Translate and 2lingual

[tweetmeme source=”Intellogist” only_single=false] As we’ve proved in past posts, machine translations aren’t always accurate, especially for translations of patent documents.  In a previous post,  Landon IP’s Director of Translation Services Sonja Olson summed up the problem with machine translations: “machine translation will get the gist of the document, but it will lose the nuance.  Machine translation can plug words together, but it can’t understand the sentence as a whole.” Machine translations can be useful for browsing documents for relevance during the search process, but professional human translations should be used for filing or legal purposes.

Today, we’ll take a look at two machine translation tools that can be used for initial prior art search purposes: 2lingual for non-patent literature (NPL) and Patent Translate for patent documents on Espacenet.  Both tools utilize the machine translation functions of Google Translate.

After the jump, we’ll look at how 2lingual and Patent Translate can help you expand your prior art search and evaluate non-English patent documents for relevance!

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Sobotong: Search for Non-Patent Literature in Multiple Languages and Formats Simultaneously

[tweetmeme source=”Intellogist” only_single=false]Patent searchers need to be mindful to branch out past English-language patents during a prior art search.  Relavent prior art may come in any format and in any language, so searchers  need to utilize techniques and resources to access prior art in any and all available languages and formats.  Sobotong is a new bilingual search engine that can help searchers identify non-patent literature prior art in both multiple languages and formats.  A recent post from the Beyond Search blog gave a brief review of the Sobotong bilingual search engine,  which was created by Qiang Wang.  Although the Sobotong website offers some unique search options that may help the user identify multilingual relavent prior art, the site also suffers from one main problem: Sobotong utilizes machine translation when conducting the multilingual searches.  Professional patent searchers who fluently speak multiple languages will always be able to conduct more thorough searches than a system utilizing free machine translation services to conduct a multilingual search.

After the jump, learn about the unique features of Sobotong that allow the user to identify prior art in multiple languages and formats, and find out the down side of using a multi-lingual search platform!

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Google Translate vs. Bing Translator, Part 2: Chinese and Japanese Machine Translations

[tweetmeme source=”Intellogist” only_single=false] Last week, we compared the language options and interface features of Google Translate and Bing Translator (powered by Microsoft Translator), and we looked at examples of German and Korean patent document abstracts, translated from their original languages to English by both translation services.  We then compared the text of both translations for each abstract using a text comparison feature from the file history tool Patent Workbench®, where text that is present in the Google translation but absent from the Bing translation is highlighted in strike-through red, text that is unique to the Bing translation is highlighted in underlined green, and text common to both translations is displayed as normal black text.

After the jump, we’ll look at two more examples of Chinese and Japanese abstracts, translated by both Google Translate and Bing Translator to English.  We’ll also get some input from Sonja Olson,  Landon IP’s Director of Translation Services, on which translation service she thinks produces better machine translations for patent documents.
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Google Translate vs. Bing Translator, Part 1: Which Produces Better Patent Machine Translations?

[tweetmeme source=”Intellogist” only_single=false]  Sonja Olson,  Landon IP’s Director of Translation Services, summed up the main problem with machine translations for patent documents in a previous blog post:

Machine translation will get the gist of the document, but it will lose the nuance.  Machine translation can plug words together, but it can’t understand the sentence as a whole.

Sonja suggested that “if you need to know if a document contains information on a topic, you can go with a machine translation.  If you need to know how that topic relates to the document overall, then go with a professional translation.”

So, users should be forewarned, neither of the free translation services discussed in this post should be used as a substitute for professional human translations.  As you’ll see in the following tests, neither translations (from German to English and Korean to English) for Google Translate nor Bing Translator are entirely coherent.  Although the user can get an overall idea of the content of the documents from these machine translations, both Google and Bing translations would never be acceptable in any legal or official context.

Google Translate and Bing Translator (powered by Microsoft Translator) are useful, however, for evaluating the general content of a patent document during a prior art search.  Which free service produces a better machine translation of a patent document?  Continue reading as we compare the two services!

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The Future of Patent Translations: Human or Machine?

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The EPO recently partnered with Google to offer free machine translation of patents into multiple languages on espacenet.  According to an EPO news release from March 24, 2011, “the EPO will use Google Translate technology to offer translation of patents on its website into 28 European languages, as well as into Chinese, Japanese, Korean and Russian.”   This news made me wonder: what is the future of human translation of patent documents?  Can professional translators compete with the speed and lower prices of machine translation services?

I decided to ask an expert, Sonja Olson, Director of Translation Services at Landon IP.  If anyone would know how human translation compares to machine translation, Sonja would know.  I also found some useful articles that highlighted the importance of professional input in the patent translation process, especially if the document will be used for legal purposes.  Read on to see what insights the journal articles and my conversation with Sonja provided about the future of patent translation!

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Will cloud computing radically change patent search products?

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First, let me say that I think “patents on the cloud” is a radical idea, and something that may create some changes in patent information products.  Read on for a summary of Alexandria, a new product that provides “patents on the cloud,” and my analysis of this new approach!

I recently spoke to Mike Baycroft of Fairview Research, Inc., the company that has lately acquired IFI and launched a new patent information product, Alexandria, billing the service as “Patents on the Cloud.”  Alexandria is a database of patent information hosted on the Amazon Elastic Compute Cloud, ready to license.   For those who haven’t followed the jargon, the “cloud” refers to cloud computing, and it basically means that you can get a lot of stuff, like data and software, directly from the delocalized network (or “cloud”) of sources that make up the internet, rather than having to load it on your own local servers.

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