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Is there any open source project or free avaliable source where I can query a webpage's category type (like https://www.trustedsource.org/en/feedback/url). I have more than 200K webpage in my dataset.
To me it looks like more of a classification problem which is suitable for Machine Learning. For this purpose you can make your model in popular ML frameworks (such as Keras/TensorFlow and PyTorch) or search for available ones on internet and use your dataset to do a transfer learning.
I could find a project on GitHub (link) that can be a good starting point.
Hi today and happy weekend!
that's interesting to know if a category is used as category pages, since google shows up multiple spots of one domain when it has category pages.
Examples:
danlok(com)
best example to see: bloomberg....
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Assume a site like https://www.wood-database.com/wood-finder/ (our working example). Each page of it has data on a wood species. Assuming we need to sort the woods by a ratio of its data, for example hardness/weight, the site's tools aren't very useful.
What would be useful, though, is passing that data into an excel, which could trivially calculate the ratio and sort.
What ways are there to automatically fill that sheet out? What other tools besides excel could do it?
You should have a look at python, it's perfectly fit for the job. You could use the request library together with beatifulsoup to begin with, then load all data into a Pandas Dataframe and simply export it to excel (standard funtionality of Pandas).
If you really want to scrape the site thoroughly, you could consider using Scrapy (https://scrapy.org/)
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I am a newbie of calabash-android. i did learn how to write scripts for automation testing. please refer me some "books" or "articles" to learn how to write scripts in a optimized way.
I recently started a new job as an automated tester for a mobile app and found the following book a good introduction to the Cucumber framework:
https://pragprog.com/book/hwcuc/the-cucumber-book
It doesn't go into lots of detail about Calabash specifically but does have lots of information on writing tests in general.
Once you have your feature files in place you just write the underlying code (Ruby in my case) to make the app do what you want (ie. touch, swipe).
It's also good to use:
query('*') whilst in the calabash-android console. It dumps out the all the information you need to know for example what ID's and text to check for on any given screen.
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I am looking for training data for text classification into categories like sports, finance, politics, music, etc.
Please guide to references. Hello.
You can get a Reuters corpus by applying at Reuters
You can also get the Technion Text Repository TechnionRepo
If you are building a text classfication system in real time, you would be already having a corpus of documents. One of the assumption in any Classifier is, training data & test data are similar or from the same distribution.
If you are just exploring or building sample usecases in this area, then probably this link might be helpful to get some train data.
http://web.ist.utl.pt/acardoso/datasets/
http://disi.unitn.it/moschitti/corpora.htm
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Hello i haven't been using EAGLE for a while now and had mostly forgot where to get any good and complete library of basic parts like resistors, LEDs, transistors... I have tried to find a library i need on EAGLE web page, but i haven't found any, that would offer quite large amount of basic parts.
If anyone could point me to a library with a good and large set of basic parts he would really save my day.
The Sparkfun Eagle libraries are quite good. Download at https://github.com/sparkfun/SparkFun-Eagle-Libraries
dear you can use "ORCAD" software rather than using EAGLE as it is easy in use and easy availability of its libraries on net.
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I am doing a project in news classification. Basically the system will classifying news articles based on the pre-defined topic (e.g. sports, politic, international). To build the system, I need free data sets for training the system.
So far, after few hours googling and links from here the only suitable data sets I could find is this. While this will hopefully enough, I think I will try to find more.
Note that the data sets I want:
Contains full news articles, not just title
Is in English
In .txt format,not XML or db
Can anybody help me?
Have you tried to use Reuters21578? It is the most common dataset for text classification. It is formated in SGML, but it is quite simple to parse and transform to a txt format.
You can build it, you can write a Python/Perl/PHP script where you run a search, then when you find the answers you can isolate the attributes with regex... I think is the best option. Is not easy but should be fun, finally you can share this dataset with us.