What does tf.nn.embedding_lookup function do?

tf.nn.embedding_lookup(params, ids, partition_strategy=’mod’, name=None) I cannot understand the duty of this function. Is it like a lookup table? Which means to return the parameters corresponding to each id (in ids)? For instance, in the skip-gram model if we use tf.nn.embedding_lookup(embeddings, train_inputs), then for each train_input it finds the correspond embedding? Answer Yes, this function is … Read more

Identify and extract URLs from text corpus

I’m working on a project that requires POS Tagging of paragraphs. The text contains lot of URLs which contain various punctuation marks such as . ?. This affects the accuracy of the sentence tokenization. So I decided to clean the data by removing/replacing all the URLs. And thought regular expressions would be handy in doing … Read more

Reduce the length of words in a sentence

This function’s goal is to reduce the length of a sentence to exactly max_length characters by cutting each word in the sentence to a length of minimum 4 characters, if cutting each word to 4 characters isn’t enough the the sentence is returned anyway. All sentences are free of special characters and words are separated … Read more

Formatting output

This code has loops under loops which affects the performance badly. Please help me to optimize the code to improve its performance. private void processPlainOutputFormat() { // we reached the end of corpus processing.Process all Documents from corpus Iterator<Document> documentIterator = getCorpus().iterator(); // method which create a header string String header = getHeaderString(getFeaturesList()); List outputList … Read more

“Toy” human-language detection software

I’ve written a small program to detect the human language of a document or text fragment. I tried to stick to good design principles and I tried to make it pretty robust. I would be generously described as an intermediate programmer so I’m sure there are things that are bad-smellish that didn’t even register with … Read more

Interpreting tweets about football

I am trying to process the football tweets and extract information like goals, cards, corners, player name, team name. I write the code which works, but I may be missing some better python functionalities which can reduce my code or make it better. # encoding=utf-8 import json import re, math import pandas as pd from … Read more

Reduce run time of NLP approximate matching code

The code below matches a list of features to a large corpus and returns the sub-query match with a score above 80. The challenge is the list of features on the full data-set is > 5,000 and comparing to multiple documents. Therefore is taking too long to work using the fuzzywuzzy package. Per the Spyder … Read more

Simple natural language classifier

This program estimates the likelihood for a string to belong to a certain natural language by computing the cosine similarity between an input string’s and several natural languages’ letter frequency, and it allows the storage of a prediction as a list in a .txt file. I would like to know whether improvements (both formal and … Read more

Syllabification function for Turkish words

I wrote an NLP script for processing Turkish language. Yesterday I added syllabication but I wonder if it could be done better. It is kinda hard-coded, so I would like to know if I can improve it. Here is the syllabication part. def syllabicate(self, word): “”” :param word: The word to be syllabicated :return: The … Read more