I have to make lexical graph with words within a corpus. For that, I need to make a program with word2vec.
The thing is that I'm new at this. I've tried for 4 days now to find a way to use word2vec but I'm lost. My big problem is that I don't even know where to find the code in Java (I heard about deeplearning but I couldn't find the files on their website), how to integrate it in my project...
One of the easiest way to embody the Word2Vec representation in your java code is to use deeplearning4j, the one you have mentioned. I assume you have already seen the main pages of the project. For what concerns the code, check these links:
Github repository
Examples
Related
I am using CoreNlp to get the information extraction from a large text. However, its using the "triple" approach where a single sentence produce many output which is good, but there are some sentences that doesn't make sense. I tried to eliminate this by running another unsupervised NLP and try to utilize function in CoreNlp, yet I stuck at getting word vector form CoreNlp. Can anyone point where do I need to start searching for codes that do the word embedding in CoreNlp? Also I am newbie in java and IT.
There are some open libraries like glove, word2vec, text2vec, but I noticed glove already been used in CoreNlp (correct me if wrong).
since training your own model from scratch might turn out to be a time-consuming task, you could just download pretrained vectors from:
https://nlp.stanford.edu/projects/glove/
however, there is an example with dl4j here that might do to trick:
https://github.com/deeplearning4j/dl4j-examples/blob/master/dl4j-examples/src/main/java/org/deeplearning4j/examples/nlp/glove/GloVeExample.java
I know that this question was asked before - but the answer was not satisfying (in the sense of that the answer was just a link ).
So my question is, is there any way to extend the existing openNLP models? I already know about the technique with DBPedia/Wikipedia. But what if i just want to append some lines of text to improve the models - is there really no way? (If so - that would be really stupid...)
Unfortunately, you can't. See this question which has a detailed answer to the same problem.
I think, that is a though problem because when you deal with texts you have often licensing issues. For example, you can not build a corpus on Twitter data and publish it to the community (see this paper for some more information).
Therefore, often companies build domain specific corpora and use them internally. For example, we did in our research project. Therefore, we built a tool (Quick Pad Tagger) to create annotated corpora efficiently (see here).
Ok i think this needs a separate answer.
I found the Yago database: http://www.mpi-inf.mpg.de/departments/databases-and-information-systems/research/yago-naga/yago//
This database seems to be just fantastic (from the first look). You can download all the tagged data and put it in a database (they already deliver the tools for that).
The next stage is to "refactor" the tagged entities so that opennlp can use it (openNLP uses sth. like this <START:person> Pierre Vinken <END>)
Then you create some text files and train it with the opennlp delivered training tool.
Not 100% sure if this works but i will come back and tell you.
i need some help creating a java project connected to rapidminer. I need to create a new process and a Filter Examples operator in order to filter some text with random words which i cannot do using only Rapidminer. I can't find anywhere how to create that specific operator in java and how to add the text and the random words. Can anyone help? Is there a specific piece of code for this?
Thank you
the standard "How to extend Rapidminer" documentation can be found here:
https://rapidminer.com/wp-content/uploads/2013/10/How-to-Extend-RapidMiner-5.pdf
At Rapidminer Wisdom it was announced that there is a gradle project to make it easier to start. Sadly i have no direct link yet.
The list below are some packages related to classifier among mahout-distribution-0.8.
org.apache.mahout.classifier
org.apache.mahout.classifier.df
org.apache.mahout.classifier.df.builder
org.apache.mahout.classifier.df.data
org.apache.mahout.classifier.df.data.conditions
org.apache.mahout.classifier.df.mapreduce
org.apache.mahout.classifier.df.mapreduce.inmem
org.apache.mahout.classifier.df.mapreduce.partial
org.apache.mahout.classifier.df.node
org.apache.mahout.classifier.df.ref
org.apache.mahout.classifier.df.split
org.apache.mahout.classifier.df.tools
I guess "df" mentioned above means "decision forest". I am not good at mahout and its source code makes me crazy, so I want to find a mahout decision forest example to see how to use these packages just like the HelloWorldClustering code in Chapter 7 Introduction to clustering Mahout in Action.
I have suffered from this problem for a while. I surf a lot of articles on the Internet but still don't find an effective example yet to tell me how to write the code in real project. Can anyone give me an example with code?
I've recently been using Mahout's DecisionForest, and the best resource i've found to help is Mark Needham and Jennifer Smith's example:
http://www.markhneedham.com/blog/2012/10/27/kaggle-digit-recognizer-mahout-random-forest-attempt/
Take a look at that, the GitHub repository is at the bottom of the page.
I have a maven project imported into Eclipse. I'm trying to understand the code pattern (architecture). What is the best way to do this?
will use any UML Eclipse plugin help on this?
will use sequence diagram, help on this?
what plugins should I use?
Please share your opinion.
When I am working with a open source project/codebase I get a high-level view and focus on the core code/logic by checking the package names and structure. I then typically determine how the API works by looking at any example code / documentation contained in the project. If I still need some more help I will draw up some inheritance diagrams, print out interesting classes that I may need to make significant changes to, and try to find more examples of the code being used elsewhere.
I am biased and have been using our recently launched Architexa Eclipse plugin to accomplish the above. I am sure there are others available that do something similar.
I guess you will find some pointers in this SE-Radio podcast: Episode 148: Software Archaeology with Dave Thomas.
Of course, UML can help, but on the other side, it might not as well. For reverse engineering, there is the MoDisco project in Eclipse, which might be useful.