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Data transformations in hierarchical classification

I am building a hierarchical text classifier using the Local Classifier Per Parent Node (LCPN) approach with the 'siblings' policy as described in the PDF: E.g. if we have the classes 1.1, 1.2, 2.1, ...
3
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0answers
102 views

How to implement hierarchical labeling classification?

I am currently working on task of eCommerce product name classification, so I have categories and subcategories in product data. I noticed that using subcategories as labels delivers worse results (84%...
2
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1answer
17 views

Classifying one particular class of documents from the rest

I am trying to build a classifier that would classify if a document is a document about sports or not. I have enough samples of sports document to train a classifier on, however I can't imagine how I ...
2
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2answers
423 views

How to extract and classify data from a column in excel?

I have a column in an Excel sheet that contains a lot of data separated by || delimiters. The data can be classified to some classes like Entity, IFSC codes, ...
2
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0answers
661 views

What is the minimum number of times a word needs to appear in word2vec training corpus for quality results?

When training a word2vec model with, eg, gensim, you can specify the minimum times a word needs to be seen (with the parameter min_count). The default value for this seems to be 5. Are there any ...
1
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3answers
24 views

Need some info regarding string matching algorithms?

Let me explain a scenario to better explain my question, Assume I am working in a credit-card related company in which people uploads their receipts every month, I want to check if that person bought ...
1
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0answers
19 views

how to resize image without changing DPI in opencv for detecting text and feeding into OCR?

i resized the image using open cv and it changed the dpi of the image from 300 dpi to 90 dpi . What is the correct way to resize image without changing its dpi in open cv . if we feed the resized ...
1
vote
2answers
25 views

Text classification for data with multiple labels per observation

I have a dataset of tweets that has been labeled by multiple people. So the columns look something like: Tweet_ID, Coder_1_Classification, Coder_2_Classification, etc. The idea is to build a tweet ...
1
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0answers
21 views

PDF/Text to csv table

I have very little python experience but I have been wanting to get into data science and thought I would start with pdf/text mining. Because it's something I need right now anyway. I have a list of ...
1
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0answers
21 views

Embedding representation for a document?

Is averaging sentence embeddings, the right way to get representation for documents. Say I have a list of sentence embeddings representing symptoms. A data point looks like these: x|S1,S2,S3 --> Y|D1,...
1
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0answers
15 views

How do I identify specific parts of a PDF document?

I have a bunch of medical records that I have to input manually. I would like to automate this but all of the records are in different formats. What is the best strategy to build a deep learning model ...
1
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1answer
86 views

How to match a word from column and compare with other column in pandas dataframe

I have the below dataframe ...
1
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0answers
27 views

Fuzzy matching of author names

We are trying to figure out what is the best approach for us to train a ML model to identify Authors. We have structured metadata of authors (given name, surname. etc) and the task is to train a model ...
1
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0answers
77 views

python - Identify variable in similar sentences

I'm looking to solve the following problem: I have a list of similar sentences as my dataset, and I want to be able to type a new sentence, which is also similar to the sentences in my dataset and ...
1
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0answers
44 views

Word classification in the context

I'm trying to solve a 'negation-like' classification problem, where I need to classify whether a certain word within the context has negative or positive label. For example, how to identify whether a ...
1
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0answers
18 views

Supervisory information through side output in convolutional neural network

I am trying to implement this paper https://ieeexplore.ieee.org/document/7828014 Here they have mentioned text local (edge) and global regions as supervisory information. Side output is generated ...
1
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0answers
13 views

Ordering quotes in a list based on user input and text analysis

A little bit of context: I have a website that has many quotes. These quotes are organized automatically by Solr into lists of quotes, so e.g. there is a list called 'Smart Quotes' that includes ...
1
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0answers
82 views

Categorize text as Body, Heading in a loosely formatted document

Given a semi-structured document with only texts and images, and some style properties present on the text, What is the best possible way to classify the text present in the document to any formal ...
1
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0answers
548 views

Multiclass classification with many classes and wide range of sample sizes

I'm working on a free text classification problem with over 100 classes in the training data. There is huge variation in the sample sizes of the classes: ranging from 1 to around 6000. I am using a ...
1
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0answers
563 views

Methods for string classifications

I have a list of some 100 millions of strings, each of different length. Examples: nsdgnlnesef ngmrlxkvgrmksefsfnlj <...
1
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0answers
348 views

Section/Topic segmentation in HTML and plaintext documents

GROBID (https://github.com/kermitt2/grobid) is terrific for fine-grained (section, chapter) segmentation of PDF files, but I need to do the equivalent for HTML and plaintext files. I've tried ...
1
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0answers
194 views

Generating a text training dataset from a grammar

I want to generate documents based on a grammar to build a custom training database. What are the tools and techniques to generate random texts based on a given grammar. More specifically, I would ...
0
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0answers
14 views

Preprocessing text so that two words without a separating space (or hyphen separated) are detected

Let's say I have a text corpus with inconsistently written bi-grams. An example would be "bi gram", "bi-gram", "bigram". Is there any standard text preprocessing method to normalize all these as the ...
0
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0answers
13 views

Needed: Java library to calculate text readability/complexity

In principle the same as this but for Java (and ideally for multiple languages) (e.g. flesch reading ease, smog index, flesch kincaid grade, coleman liau index, automated readability index, dale chall ...
0
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0answers
19 views

How would I define a model that computes “trainable edit distance” \ string similarity for Entity Linking

I want to compute a measure of string similarity based on "edit distance". Classic solutions for edit distance predefine the cost of each editing operations, and use a combination of atomic operations ...
0
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0answers
23 views

Looking for a good text autoencoder model (for text reconstruction)

I am looking for a simple and good model that can learn to encode and reconstruct text sentences to use it in some downstream task. I tried a tensorflow seq2seq model here, but it doesn't do ...
0
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0answers
5 views

Finding relevant pain points in feedbacks(open text)

I have employee feedback and need to find the appropriate pain points out of their feedback. Need help with the approach and analysis. I have provided a couple of examples below. Note: The feedbacks ...
0
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1answer
33 views

How to utilize dictionary data set for text classification?

I have a dataset similar to newsgroup20 for classification. With the training dataset, I have a dictionary data set that explains some jargons in the training dataset. These both are different data ...
0
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0answers
419 views

Semantic Similarity in Universal Sentence Encoder

I am currently using Universal Sentence Encoder to embed certain sentences which I would then feed to a deep learning model to do some prediction, but just to test whether the universal sentence ...
0
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0answers
39 views

Map predictions to real text

I have read the paper "Learning to Read by Spelling" by Gutpa et al. They present a method for visual text recognition without using any paired supervisory data. In chapter 4 they describe how to ...
0
votes
1answer
523 views

Extracting structure and content from invoices

Lately, I have been largely inspired by this https://rossum.ai/, which is able to extract text from invoice documents. Do you have any ideas on how this could be implemented? It's clear that they ...
0
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0answers
74 views

Make use of multiple labels in doc2vec: Setting up the data

I am trying to implement the doc2vec algorithm with a rather small sample size: ca. 120 documents with a total of 25000 unique words. My ...
0
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0answers
14 views

Do double quotes, dots and commas modify the forget weights in LSTM if retained?

I am trying to implement custom NER with LSTM. In the pre processing steps is it required to remove the punctuation marks like double quotes, dots and commas? Do they add any significance if retained? ...
0
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0answers
223 views

Implementing back translation as a data augmentation for text classification

Since back translation English->other language -> English seems like quite a useful data augmentation technique , I wanted to experiment with it. E.g. it occurred to me that languages from very ...
0
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1answer
83 views

What methods to create singular content classification from inconsistent inbound info?

I am attempting to aggregate professional profile info from multiple sources, imposing a consistent taxonomy. Specifically, the current problem is how to impose a preferred taxonomy on profiles with ...
-1
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1answer
18 views

Identifying specific words in text

Let's say I have the following text" Is that another kitten playing in the shoes in the top right? I would like my code to extract kitten from that text. Is ...
-1
votes
1answer
74 views

Text standardisation for manually entered data

I am working on a project that involves dealing with manually entered text data. I have a dataset of customs records where the customs officers manually enter the name and address of companies ...
-1
votes
1answer
52 views

What is the best solution to find the readability of texts?

I want to find the readability of texts. Can I use a classification method for that? For example, by collecting some basic, intermediate, and advanced texts as training sets and then finding the ...