Questions tagged [natural-language-processing]

Natural language processing (NLP)

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41 views

Explain better this new inventory for Word Sense Disambiguation

My question is about CSI (Coarse Sense Inventory), described in the paper CSI A Coarse Sense Inventory for 85% Word Sense Disambiguation (C Lacerra, M Bevilacqua, T Pasini, R Navigli). Before the ...
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21 views

Optimal algorithm for making queries to a database

There is a database of, let's say, 500k English two-word combinations (e.g. "clover arc", "minister horse"). I can search for an arbitrary string and I will get a list of the alphabetically first 1000 ...
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1answer
126 views

Similar news detection

How do top news portals detect similar news? For example https://www.bbc.com/news/world-asia-china-51431087, if you go to this webpage, you can see the "More on this story" section at the bottom of ...
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25 views

How to identify measure words in Chinese text?

Measure words (aka classifiers) are used in Chinese to "measure" things, e.g. 三杯牛奶 Three glasses of milk 那个人 That person 一只乌鸦 One crow 一公斤豆腐 A kilo of tofu We don't have an ...
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1answer
39 views

What kind of bigram probability smoothing is this?

I hope it isn't off topic but I need to understand this example. Given the corpus 12 1 13 12 15 234 2526 and smoothing factor of ...
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15 views

What is the main concept of using lexical,linguistic, semantic or syntactic approach in NLP for cyberbullying

Am really in need of some explanation, am working on a nlp cyberbullying detection tool which i will deploy to the web using django framework, however, am stuck on some idea, can someone explain to me....
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1answer
91 views

Is there a meta text processing concept in CS?

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, ...
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8 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 ...
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24 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 ...
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18 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 ...
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1answer
30 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 ...
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39 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) ...
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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 ...
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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 ...
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8 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....
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26 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 ...
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1answer
46 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 ...
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30 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 ...
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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 ...
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1answer
237 views

N-gram language model question

I have this question I found regarding n-gram modelling in the Speech and language processing text book: ...
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29 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 ...
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1answer
150 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 ...
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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 ...
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9 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", ...
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27 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....
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1answer
85 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 ...
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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 ...
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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 ...
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36 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 \...
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1answer
102 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 ...
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1answer
292 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 ...
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263 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 ...
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1answer
23 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 ...
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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 ...
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1answer
93 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 ...
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1answer
41 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 ...
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16 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 ...
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60 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 ...
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32 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. ...
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54 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 ...
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136 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/...
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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 ...
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1answer
194 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
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94 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 ...
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54 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 ...
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1answer
759 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 ...
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1answer
66 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 ...
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87 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 $459^2$, ...
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1answer
31 views

HMM tagger - Baum Welch training

I am trying to implement a trigram HMM tagger for a language that has over 1000 tags. In my training data I have 459 tags. Now if we consider that states of the HMM are all possible bigrams of tags, ...
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1answer
25 views

How to use a logistic regression classifier to estimate the confidence of a rule?

The following is an excerpt from the Estimating LAT Confidence section of this paper: ... Since some LAT detection rules are more reliable than others, we would like to have a confidence value in ...