Questions tagged [natural-language-processing]
Natural language processing (NLP)
160
questions
1
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1answer
80 views
Meta text processing concept
I understand that text processing could be done in various ways on top of operating systems:
Shell utilities for processing a file (and/or a file name): tr, ...
3
votes
1answer
53 views
Phrase generation approaches
In generating reports, sometimes there is a need to produce quite involved phrases in one of natural languages given numerical or boolean parameters.
To get a feel of it, it is enough to take a look ...
0
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1answer
142 views
N-gram language model question
I have this question I found regarding n-gram modelling in the Speech and language processing text book:
...
21
votes
1answer
839 views
Compression of domain names
I am curious as to how one might very compactly compress the domain of an arbitrary IDN hostname (as defined by RFC5890) and suspect this could become an interesting challenge. A Unicode host or ...
0
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0answers
6 views
Contingency Table Confusion NLP
Hello for the contingency table: [true positive, false negative, false positive, true negative]. I am having a hard time remembering the difference between these terms because all the terms are ...
3
votes
1answer
4k views
How to calculate an accurate estimated reading time of text?
I suppose the calculation should not be done by only two factors (average reading speed/words per minute, and word count). But at least by a third parameter, that in my opinion should measure the ...
0
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1answer
40 views
CYK result de-transformation
Suppose we have a rules derived from a treebank.
And in order to get a syntax tree of a given sentence we use the cyk algorithm.
In order to use the cyk we should convert the rules into chomsky normal ...
2
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0answers
20 views
Question about word embeddings in a specific language model - GPT-2
How were the GPT-2 token embeddings constructed?
The authors mention that they used Byte Pair Encoding to construct their vocabulary. But BPE is a compression algorithm that returns a list of ...
0
votes
1answer
24 views
Which algorithm for predicting the next word(s) based on previous words, given a sentence?
I want to input some words, and out comes the next word(s). Neural nets are really hot at the moment, and I'm afraid of throwing a neural net at something, when one is not really needed. Or... maybe ...
0
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0answers
17 views
What classifier can recognize differences in two text strings immediately?
I'm playing around with the TextBlob library for python. It has in it a NaiveBayesClassifier as well as a ...
0
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0answers
36 views
More information about the 10 types of information that can be useful for WSD (Word Sense Disambiguation)
Agirre and Martinez (Knowledge Sources for Word Sense Disambiguation) distinguish ten different types of information that can be useful for WSD (Word Sense Disambiguation):
Part of speech (POS) ...
3
votes
0answers
45 views
Explain the process of formation of word senses in WordNet
Regarding the word sense disambiguation problem, read the following fact written on Knowledge-based Word Sense Disambiguation using Topic Models:
Note that although WordNet is the most widely used ...
1
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0answers
40 views
What are open problems in computer science? [closed]
I should prepare some paper for a colloquium (kinda student-task) and it should cover the following points:
(1) at least one notable discovery in theoretical informatics (or computer science)
(2) at ...
0
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0answers
7 views
Query about an equation in GAN-NMT paper
So i was studing the paper Adversarial Neural Machine Translation by Lijun Wu1, Yingce Xia2, Li Zhao3, Fei Tian3, Tao Qin3, Jianhuang Lai1,4 and Tie-Yan Liu.
The link to the paper is : https://arxiv....
0
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0answers
18 views
Understanding Multi-headed attention
Recently I came across the concepts like Attention and Transformer architecture. After studying the papers and many blogs, I understood the concepts, but recently one doubt is coming in my mind and ...
1
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0answers
27 views
CYK algorithm - how to handle unknown terminals given in a sentence to parse?
There is a given treebank which we derive the Probabilistic context free grammar.
I wonder how do one handles with a given sentence which includes terminals that don't exist in the derived rules?
Is ...
0
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0answers
105 views
How does Google's Superpod work?
I was looking for the best natural language quenstion answering system and chatbots when I found Google's Superpod described here. I googled for how Superpod works but I have found any important ...
1
vote
1answer
257 views
How does SpaCy make its dependency tree?
I discovered that SpaCy had the ability to make dependency trees. For instance given a question “To whom did the Virgin Mary allegedly appear in 1858 in Lourdes France?”
We can create its dependency ...
1
vote
0answers
25 views
How can I find the perplexity of a text by the perplexity of its sentences?
For a bigram language model, I can calculate the perplexity of sentences of a test document. However, I'm not sure what would be the perplexity of the whole document. Should I get the average of the ...
3
votes
1answer
144 views
Bottom up chart parser adding active arc step
I am following Bottom up chart parsing algorithm from Natural Language Understanding book by James Allen. It is
I couldn't understand the 3rd step. I thought that when active arc is added the dot ...
1
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0answers
38 views
Text Segmentation Problem give Word Frequencies in a Universe
Given a dictionary of words and their frequencies (how many times they appear in a universe and given a string(no spaces, punctuation, etc.). What is the best way to segment into individual words? I ...
2
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0answers
8 views
Are there any neural NLG systems which don't generate in left-to-right order?
For a while, all classification tasks in natural language processing were based on simple RNN's, which operate in a very word-by-word order. Adding gating mechanisms increased ability to "look back", ...
1
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0answers
26 views
Generalization of formal grammars - production rules with more general functions?
Usually formal grammars have production rules in the format N=tNt where simple concatenation function is used for the expansion of the nonterminal. https://www....
1
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1answer
77 views
Show that the Laplace smoothing for bigrams is a valid probability distribution
If we consider any smoothing technique like laplace or delta smoothing. Intuitively we can see that the we are stealing from sequences with non zero probablity and re distribute to sequences with zero ...
2
votes
1answer
102 views
How to represent symbolic knowledge using real numbers - theory about neural networks and natural/analog computing?
One can define the semantics of one definite word using the references to real world entities, relationships with the other words and other concepts and represent all this knowledge about this one ...
4
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2answers
115 views
Measuring the information of a document?
I'd like to measure how much information a document $D$ contains.
Clearly, the New York Times published yesterday contains more information than my diary wrote on the same day. But, I do not know ...
4
votes
0answers
20 views
How to represent sentences with their dependency parses as input to an RNN?
I am working on a task embedding sentences into a lower-dimensional space according to style, both grammatical and lexical. As such, I want to have as input the linear ordering of tokens in each ...
3
votes
0answers
32 views
How to compute the loss and backprop of word2vec skip-gram using hierarchical softmax?
So we are calculating the loss
$$J(\theta) = -\frac{1}{T}\sum_{t=1}^T\sum_{-m \leq j \leq m} \log P(w_{t+j}|w_t;\theta)$$
and to do this we need to calculate
$$P(o|c) = \frac{\exp(u_o^Tv_c)}{\sum \...
1
vote
1answer
96 views
How to transform lambda function to multi-argument lambda function and how to rewrite or approximate terms?
I am trying to do the formal semantics (Montague grammar, abstract categorial grammar) of natural language and encode the sentence John is boss. The type system has ...
2
votes
1answer
22 views
Marginalise edge weights on graph
I have a directed acyclic graph with a score on each edge. The score of a path is defined to be the sum of the scores on the edges along this path. The probability of a path is the score of such a ...
5
votes
2answers
731 views
Estimate entropy, based upon observed frequency counts
Suppose I have $n$ independent observations $x_1,\dots,x_n$ from some unknown distribution over a known alphabet $\Sigma$, and I want to estimate the entropy of the distribution. I can count the ...
1
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0answers
236 views
How can node2vec help find similar “roles” within a graph (nodes whose connections have similar structure within the graph)?
I have a question on the node2vec algorithm described in this paper.
Node2vec is a deep learning algorithm that word2vec to graphs to learn embeddings. The authors claim that it can help find nodes ...
2
votes
1answer
1k views
Subsampling of Frequent Words in Word2Vec
I am reading through the following paper: https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf
Under section 2.3 on page 4 the authors ...
1
vote
1answer
85 views
Question on word probability for hierarchical softmax used in natural language processing
I am reading the following paper: https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf
On page 4 of the paper they describe the ...
0
votes
1answer
39 views
Naive Bayes' Classification and Using the Entire Vocabulary in the Denominator
I am working through the NLP notes for Naive Bayes' classification here: https://web.stanford.edu/~jurafsky/slp3/6.pdf
Below $c$ is the class of the observation and $w_i$ is the $i$th word of a text ...
2
votes
0answers
15 views
How does the Earley parser accept the input string as syntactically correct?
https://en.wikipedia.org/wiki/Earley_parser
An input string of length $n$ is syntactically correct if at least one $(S \rightarrow X_1 ... X_m • 0)$ is in $E_n$. Why is this the case ? The part ...
2
votes
0answers
57 views
Proving the probability of zero occurrences in training using Good-Turing maximum likelihood estimate
Background
Good-Turing (GT) smoothing is used in language models to estimate the counts of words in the test set that have not been seen in the training set.
In GT smoothing, $N_c$ is the count of ...
1
vote
1answer
30 views
How to figure out whether two texts refer to the same object or event
Let's assume there is something happen in the world - Football world cup final. And team-1 beat team-2 with the score 3:2. So there is whole bunch of articles on every website about it, each contains ...
0
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0answers
31 views
Any references/current work on anomaly detection in conversations?
Suppose I have a lot of data on conversations between humans and chatbots (human text, chatbot text, times, media used for chat, etc), and I want to be able to detect anomalies in these conversations. ...
2
votes
1answer
866 views
Semantic natural language processing - from texts to logical expressions? Universal knowledge base?
My question is - is there a semantic natural language processing that tries to understand the meaning of the texts and that tries to derive the consequences of the understood meaning? Is there a ...
1
vote
0answers
40 views
In NLP, tokens not seen in training sample, but you know or don't know what they are
In NLP, do you distinguish tokens that you don't observe in a training sample and still expect that they may occur in a test sample, between
those you know what they are, and
those you don't know ...
2
votes
0answers
53 views
Automatic learning/discovery of logics
Are there efforts to automatically discover new logics? Logics are simple structures - they have formal language, deduction rules, semantics and certain properties that are proved or discarded for ...
3
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0answers
130 views
Semantic parsing with Grammatical Framework - is this possible?
So far I have learned about categorial grammars, type logical grammars and formal semantics of natural language, the relevant tools are Cornell Semantic Parsing Framework https://github.com/clic-lab/...
4
votes
1answer
4k views
Semantic clustering
I have a very specific question about semantic clustering.
I have a list of words/phrases. I want to run an intelligent semantic clustering algorithm on this list. Please let me know what the ...
0
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1answer
187 views
Converting CFG to CNF [closed]
need some help with the following question:
I've watched a few youtube tutorials but I'm struggling to convert this specific CFG
6
votes
1answer
666 views
nlp: phonetic edit distance between a word and the closest of a set of words
Let's say someone is using Dragon Dictation, Google Speech, or some other free form dictation software (it will recognize anything they say to the best of its ability). I have some reasonably large ...
3
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0answers
92 views
How to translate lambda calculus into (first-order, modal) logic, is it possible at all?
It is possible (using formal semantics) to translate natural language sentences into lambda expressions. So, is it possible to translate those lambda expressions into some logic, e.g. into first-order ...
2
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0answers
53 views
Semantic/DRT methods for conversational agents / chatbots / dialogue systems - reference request?
The wiki pages about chabots mention that statistical methods, keyword search and precompiled answers are used for the chatbots. But I feel that there should exist different - semantical approach for ...
1
vote
1answer
59 views
Understanding the geometrical interpretation of word2vec
I'm trying to understand how the $word2vec$ method actually nudges word vectors of similar semantic/syntactic content closer together in the word vector space.
I've read here (Quora answer) that it's ...
1
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0answers
85 views
HMM Baum-Welch training and pruning
I am working on a HMM tagger that should be initialized with some small data and then supposedly improved with Baum-Welch algorithm on the data.
However, the number of states is huge, almost $459^2$, ...
