Questions tagged [information-retrieval]

Information Retrieval is an area of study concerning with retrieving documents, information or metadata from a collection of unstructured or semi-structured data.

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Find specific topics with topic modelling

I am looking for a way to classifiy text automatically by specific topics, i don´t have labeled data. Is this a possible/usual method of achieving this? If not, what would be better? Topic Modelling ...
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2answers
33 views

Targeted information extraction / focused extractive summarization

I have a large collection of project manuals, each with a large number of pages. Each manual contains some form of summary paragraphs, although these are not necessarily similar in structure or format ...
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Data extraction from documents using NLP and ML [closed]

How do you extract data from documents? As an example, consider an application form which I would like to extract data from. Such as applicant name, application number, etc. The thing is, I wasn't ...
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21 views

Text Mining with Pubmed Widget Orange

When I was running the text mining I did not have an issue for 57 different searches. I was able to retrieve all of the records regardless of how many there were. Until these 2 errors popped up. I ...
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35 views

Extraction of skills from Resume Using Machine Learning

I have gone through the previous questions regarding 'Resume Parsing' and 'Extraction of skills'. They didn't help me as my data is not structured. The resumes I am dealing are neither properly ...
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4answers
41 views

Best way to combine two similar document

I have f.ex.: two news-articles that report the same event. However, these two text are similar BUT not the same. I would like to combine these two texts creating one text that contains only the most "...
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1answer
15 views

Dissimilarity Matrix of non-metric proximity data

we currently have a coding exercise, where we are asked to implement Constant Shift Embedding (Paper). This in itself is not a big problem. For the algorithm, all you need is a symmetric non-zero ...
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54 views

How to implement Semantic Search in R or Python

I have a task to provide semantic searching capabilities. For example, if I have a dataset of resume and if I search for "machine learning" than it should return me all resumes which have data science-...
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100 views

Doc2vec most similar document to a query string

I'm working on a project and I created doc2vec representation of different academics which include their patents and publications etc. For each publication and patent I have information such as title ...
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1answer
79 views

Detect sensitive data from unstructured text documents

I know this question is broad, but I need an advice to know if it's possible to achieve what I want to do. The problem is that I have around 2500 documents with sensitive data being replaced by four ...
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0answers
16 views

Why use standard tf weight over tf-idf? [closed]

Why you would use this over tf-idf? Are results better for this one?
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1answer
187 views

Can macro F1 score be greater than micro F1 score?

I am reading about evaluation metrics, and it seems that micro scores are more useful. But I was wondering about scenarios where macro F1 score is greater than micro F1 score, and if this is at all ...
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14 views

Extarct information of of text such as font from pdf using python

I need to extract the information of text from the raw PDF,such as 1.Font size of text 2.Font used Is there any predefined libraries in python to extract the above information
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369 views

Word embeddings for Information Retrieval - Document search?

What are good ways to find for single sentence (query) the most similiar document (text). I asked myself if word vectors (weighted average of the documents) are suitable to map a single sentence to a ...
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1answer
30 views

Algorithm for document retrieval in QA system

I am working with question answering and machine reading comprehension system. I want to match questions and documents (around 100,000 docs) in database. I've used tf-idf but it accuracy is about 55% ...
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0answers
36 views

How to approach training a machine to read a form

After many rewrites I'm still not entirely thrilled with how I've presented this.... please delete if inappropriate. Background As part of my job, we record observations on underwater paper and then ...
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1answer
140 views

What is NLP technique to generalize manually created rules in text?

Let's say we have a free text containing key-value entities. Example: "... patient's tumour has width 6 cm and height 5 cm" Then an expert comes, marks it as important, thus we do have the rule for ...
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1answer
15 views

TextInformationRetrieval content based

I need to know how to avoid spam document(file with repeated keywords) weighting while ranking the top k documents.
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37 views

Reconciling time-based data when data source clock drifts

How can I reconcile time-based data when the clock on the data source tends to drift and the data may be infrequently retrieved? I measured the clock to be about 30 minutes behind after 15 hours. ...
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1answer
72 views

Capturing movement importance - logistic regression output

I'm studying some event for a set of objects that can be plotted on a square $[0, 100] ^ 2$. I have used logistic regression to calculate probabilities that event occur for different objects and the ...
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59 views

Using ontology to infer labels for process model

I'm trying to implement a specific type of process mining, that has been presented in this thesis [link]. It is based on HMMs and generates a process model in form of a directed graph, where: Nodes ...
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23 views

Efficient search for a Triples data [closed]

I have a text file which consists of ~10k triples in the format, Let say I need to extract all the relevant triples for the query "Tom and Jerry likes to play football", with this I am extracting NP(...
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10 views

Understanfing OpenIE 5 output

I used your Open IE 5 to extract the triples and got the following result, Text Input By the algorithmic approach known as LevenbergMarquardt backpropagation algorithm, the error is decreased ...
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1answer
37 views

mathematical accurate definition of the binary independence model

I have a hard time understanding the exact mathematical meaning behind the binary independence model. On wikipedia we can see the following definition or similarly in the book from Manning and ...
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1answer
50 views

Classifying whether a comment or review is a complaint or appreciation of product and extracting the Topic?

I need to classify whether a given review or comment is a complaint or appreciation. This is planned to be used in multiple places, product review pages of own site as well as facebook and twitter. ...
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1answer
110 views

Two definitions of DCG measure

I wanted to check the definition of Discounted Cumulative Gain (DCG) measure in the original paper Jarvelin and it seems it differs from the one given in the later literature Wang. Originally, for $n$ ...
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1answer
74 views

Sparse IR with user feedback

I'm considering a problem framing within an information retrieval context. I have a sequence of documents that feature different attributes. In the web context, these would be webpages. One ...
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1answer
183 views

Industrial application(s) of LDA (latent Dirichlet allocation)?

LDA ( Latent Dirichlet allocation) - is quite a popular topic in data-mining. Question What are the industrial systems using LDA or may be some related models ? (May be Google/Amazon/ ... ? ) PS I ...
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24 views

Does recall has different interpretation when comes to classification and information retrieval

Recall Definition In terms of classification The recall is defined as no of positive instances that are correctly detected by the classifier. $$ TP = \frac{TP}{(TP+FN)} $$ In terms of ...
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46 views

How can I train a model to modify a vector by rewarding the model based on the modified vectors nearest neighbors?

I am experimenting with a document retrieval system in which I have documents represented as vectors. When queries come in, they are turned to vectors by the same method as used for the documents. The ...
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1answer
210 views

Information retrieval / slot filling / NLP

Excuse if this has been answered before. I need to extract features and parse from a piece of text and run some analysis. For e.g. "Plot the past 5-year sales of Apple" should give me the following ...
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1answer
860 views

How can you build a model that reads out receipts and invoices?

The objective is to build a model that is capable of identifying information on receipts and invoices that can look completely different. I've had a discussion with my brother about the right ...
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0answers
43 views

How to combine heterogeneous image features extracted with different algorithms for similar image retrieval?

Say I have access to several pre-trained CNNs (e.g. AlexNet, VGG, GoogleLeNet, ResNet, DenseNet, etc.) which I can use to extract features from an image by saving the activations of some hidden layer ...
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128 views

Extracting date, relation and noun phrase from text

A sentence (Segmented from a document) as below: ...
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1answer
249 views

Is recall more important than precision for mass mailings?

Say for example, I built a classification model for a mailing campaign that will be applied to 1M records. The positive class for the model would be customers and the negative records would be non-...
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41 views

Efficient filtering of intersecting sets by cardinality

Suppose we have a set of documents with integer identifiers and an inverted index, which maps words to skip lists of document identifiers with the interface: ...
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1answer
50 views

I have 50 videos. I ask a customer 10 questions. Based on their answers, I send them a set of videos. How do I do it?

This might make you feel like I am looking for a recommender engine, but I am not. A recommender engine works well if accuracy isn't an issue, but in my case, it is. What I have proposed is to ...
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0answers
121 views

ElasticSearch for data scientists [closed]

This is to seek career advice for a data scientist. What pertains within the role of data scientist and what does not regarding ElasticSearch. Does backend development for ElasticSearch using ...
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1answer
93 views

Peformance evaluation of ranking algorithms

I have three questions: How can we assess (or measure) the performance of the ranking algorithms? Are there any specific measures, or performance metrics, for this? More specifically, how can we ...
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1answer
131 views

How to evaluate multi label image retrieval model

I'm using a deep hashing model to search most similar images in a database (most similar to the image given as a query). I'm doing this on the coco dataset which has multiple labels per image. I'd ...
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1answer
628 views

How to extract NER from a Spanish language text file?

I am trying to extract various Named Entities from a Spanish language text file. I tried using nltk but no success. I am working on python2 with nltk 3.x
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2answers
423 views

Confusion with cosine similarity

In information retrieval when we calculate the cosine similarity between the query features vector and the document features vector we penalize the unseen words in the query. Example if we have two ...
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1answer
3k views

Cosine similarity between query and document confusion

I am going through the Manning book for Information retrieval. Currently I am at the part about cosine similarity. One thing is not clear for me. Let's say that I have the tf idf vectors for the ...
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1answer
114 views

Learning to rank: construct absolute ranking using pair-wise ranking approach

I am learning about the "pairwise approach" for learning to rank. As far as I understood, the training output is a partial ranking function $r$ that: given given some query $q$ and two document $d_i$ ...
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1answer
67 views

What model to use for matching two datasets

I've got 500 images of paper receipts scanned and OCR as one dataset. I also have a dataset of transactions from my credit card statement including amount and date. What model is best to match the ...
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1answer
105 views

In what data science applications has the stack exchange dump been used?

Anonymized dumps of the stack exchange data are available here. Do you know projects or article that have been using these data (for social network analysis or information retrieval) ? My little ...
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2answers
104 views

Extract person's academic degree from text

I have a corpus of free form text (emails) and am trying to extract the highest degree (eg. High School, Bachelor, Master's, phD) from each of them. Is stemming the way to go? Or lemmatization? Note ...
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1answer
92 views

ADHoc Information Retrieval

I want to extract the total bill from image receipts. I could extract the entire data present in the image but now I am struck with the problem of extracting only the information that I need. This is ...
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0answers
46 views

Analyzing Web page structure

I'm looking for an algorithm, that classifies a webpage. But not the content. I know the readability algorithm (by arc90) to extract a main text from an webpage. That for instance can decide, wether a ...
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1answer
999 views

Doc2Vec or Word2vec for word embedding

Is there any benefits from using Doc2vec for word embedding ( replacing word2vec ) ? in other hand if I train word2vec and doc2vec with the same dataset will I have the same word vectors ?