Category: News

I am very happy to announce this performance update that means that classification will have better accuracy than before.

When I was building a new topic classifier based on the IAB taxonomy I did notice some weird behaviour for classes with much less training data than the others. As I started to investigate this I was able to understand how the overall classification could be improved, not only those with low training data. After weeks of testing different implementations I found a few improvements that significantly gave better results on the test datasets.

In short classifiers are much more robust and less sensitive to imbalanced data.

This update doesn’t affect any api endpoints it will only give you better probabilities.

I might write a short post on the technicalities of this update.

Since uClassify was launched back in 2008 we have seen many technological changes. Last year I modernised the site to use bootstrap as a foundation. Now it’s time to take the api to a more modern format.

Initially the uClassify api only had an XML endpoint, however over the years JSON has become more common and I have been getting more and more requests for REST endpoints with JSON format. The graph below shows google trends ‘json api’ (red) vs ‘xml api’ (blue)

Today I have launched a beta of the JSON REST API, changes may still occur but it will hopefully be finalised during Mars 2016.

You can find the documentation here, please feel free to leave feedback.

The old XML and URL API endpoints will of course continue to work as before.

As a part of the uClassify upgrade I’ve recompiled the local server for 64-bit. This was necessary since I’m working on a huge classifier for sentiment and needed the corpus tool to be able to handle more then what 32-bit pointers could hold.

If you are running a local uClassify server, you can download the 64-bit (and 32-bit) here. The 64-bit server is already used in production for uClassify and should be pretty well tested by now.

You can read more about the local uClassify server here.

Lately we have been getting a lot requests to our sentiment classifier, many are from social media analyst companies. In fact our sentiment analysis is now the most popular classifier at uClassify!

I just wanted to share something that could be usable for you guys. By using our latest Api call, ‘classifyKeywords’ you can see which keywords are the strongest triggers for the positive and negative classes. This could reveal additional valuable information for your clients.

For example, if you use the keyword analysis on a long product review, you could use the keywords to extract the sentences where the product is mentioned in a positive or negative way. Why not highlight it in green or red? Highlighting sentences will give a very good overview for human reviewers.

Here is how an XML request looks like (just swap ‘classify’ for ‘classifyKeywords’):

<?xml version=”1.0″ encoding=”utf-8″ ?>
<uclassify xmlns=”http://api.uclassify.com/1/RequestSchema” version=”1.01″>
<texts>
<textBase64 id=”tweet1″>bm93IHNvbWV0aW1lcyBpIHdvbmRlciB3aGF0</textBase64>
</texts>
<readCalls readApiKey=”YOUR_READ_API_KEY_HERE”>
<classifyKeywords id=”ClassifyKeywords” username=”uClassify” classifierName=”Sentiment” textId=”tweet1″/>
</readCalls>
</uclassify>

You can find more info about ‘classifyKeywords’ here.

The sentiment classifier is described in more detail here.

With the keywords API you can extract relevant/discriminating words from texts, this opens up a lot of possibilities for developers. Keywords can be used to for tag clouds and answer questions such as why a text is classified into a class. Compared to ordinary tag clouds they bring an extra angle as they are not the overall keywords but only for a certain genre. For example you can find out what parts of a text makes it manly using the gender classifier at the same time running it through the mood classifier and finding out keywords that indicate happy parts.

After having tested the keyword API for a while I’ve just made it public in the XML API now. It works exactly like the classify API but  you will get back a list of keywords for each class as well.

In short this is how a call can look:

<?xml version="1.0" encoding="utf-8" ?>
<uclassify xmlns="http://api.uclassify.com/1/RequestSchema" version="1.01">
  <texts>
    <textBase64 id="UnknownText1">bm93IHNvbWV0aW1lcyBpIHdvbmRlciB3aGF0</textBase64>
  </texts>
  <readCalls readApiKey="YOUR_READ_API_KEY_HERE">
    <classifyKeywords id="ClassifyKeywords" classifierName="MySpamClassifier" textId="UnknownText1"/>
  </readCalls>
</uclassify>

Example response:

<?xml version="1.0" encoding="utf-8" ?>
<uclassify xmlns="http://api.uclassify.com/1/ResponseSchema" version="1.01">
  <status success="true" statusCode="2000"/>
  <readCalls>
    <classifyKeywords id="ClassifyKeywords">
      <classification textCoverage="0.96">
        <class className="Legitimate" p="0.12"/>
        <class className="Spam" p="0.88"/>
      </classification>
      <keywords>
        <class className="Legitimate">uclassify jon computer urlai</class>
        <class className="Spam">viagra cheap pills</class>
      </keywords>
    </classifyKeywords>
  </readCalls>
</uclassify>

More info is available in the XML API documentation.

Happy new years!