Skip to main content

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.

Filter by
Sorted by
Tagged with
26 votes
2 answers
18k views

Text categorization: combining different kind of features

The problem I am tackling is categorizing short texts into multiple classes. My current approach is to use tf-idf weighted term frequencies and learn a simple linear classifier (logistic regression). ...
elmille's user avatar
  • 361
21 votes
3 answers
316 views

Does click frequency account for relevance?

While building a rank, say for a search engine, or a recommendation system, is it valid to rely on click frequency to determine the relevance of an entry?
Rubens's user avatar
  • 4,107
10 votes
5 answers
19k views

How to create a good list of stopwords

I am looking for some hints on how to curate a list of stopwords. Does someone know / can someone recommend a good method to extract stopword lists from the dataset itself for preprocessing and ...
PlagTag's user avatar
  • 333
10 votes
2 answers
422 views

Extract canonical string from a list of noisy strings

I have thousands of lists of strings, and each list has about 10 strings. Most strings in a given list are very similar, though some strings are (rarely) completely unrelated to the others and some ...
lacton's user avatar
  • 201
9 votes
1 answer
3k views

How can you build a model that extracts data out from receipts?

I'm trying to build a model that is capable of identifying information on receipts and invoices. I have used google cloud vision api for text extraction from the receipt but the problem is it just ...
user_12's user avatar
  • 347
8 votes
5 answers
2k views

Best way to search for a similar document given the ngram

I have a database of about 200 documents who's ngrams I have extracted. I want to find the document in my database that is most similar to a query document. In otherwords, I want to find the document ...
okebz's user avatar
  • 113
8 votes
1 answer
4k 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 ...
Spurious's user avatar
  • 181
7 votes
1 answer
5k views

Can we compare a word2vec vector with a doc2vec vector?

I have set of categories and I want to compare a document vector with word vector of categories to find best matching category. Is it possible to compare a word vector with document vector? If yes, ...
SHASHANK GUPTA's user avatar
6 votes
2 answers
981 views

Why do popular search engines not follow the usual AND, OR logic for queries?

I am teaching myself Information Retrieval from Christopher Manning's book (PDF link: http://nlp.stanford.edu/IR-book/pdf/01bool.pdf). I tried Exercise 1.13: "Try using the Boolean search features on ...
user avatar
6 votes
3 answers
212 views

Can we quantify how position within search results is related to click-through probability?

Suppose, for example, that the first search result on a page of Google search results is swapped with the second result. How much would this change the click-through probabilities of the two results? ...
zihaolucky's user avatar
6 votes
1 answer
133 views

Evaluating the performance of a machine learned recommendation system

I have a set of resumes $R=\{{r_1,...,r_n\}}$, which I've transformed to a vector space using TF-IDF. Each resume has a label, which is the name of their current employer. Each of these labels comes ...
Data's user avatar
  • 467
5 votes
1 answer
7k views

Difference between paragraph2vec and doc2vec

Is paragraph2vec the same as Doc2vec or is every approach different?
Malek Djelassi's user avatar
5 votes
1 answer
3k views

semi-structured text parsing using machine learning

I am looking for a method to parse semi-structured textual data, i.e. data poorly formatted but usually having a visual structure of a matrix which may vary a lot in content and number of items in it, ...
mic's user avatar
  • 513
5 votes
1 answer
1k views

TS-SS and Cosine similarity among text documents using TF-IDF in Python

A common way of calculating the cosine similarity between text based documents is to calculate tf-idf and then calculating the linear kernel of the tf-idf matrix. TF-IDF matrix is calculated using ...
kgkmeekg's user avatar
  • 153
5 votes
1 answer
123 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 ...
Robin's user avatar
  • 1,337
4 votes
4 answers
1k views

How can conclusions be drawn from recommendation systems evaluation?

From my research, a recommendation system are a subclass of information filtering system that seek to predict the "rating" or "preference" that a user would give to an item. And basically exists many ...
John Newman's user avatar
4 votes
4 answers
1k 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 "...
Carol.Kar's user avatar
  • 187
4 votes
1 answer
103 views

How is "relevance" defined in information retrieval outside the context of systems with user feedback?

I've seen information retrieval systems that return some results from a query, and then the user rates these results as either "relevant" or "not relevant". What can you do if you do not have user ...
DataGuy's user avatar
  • 53
4 votes
2 answers
863 views

Building a tag-based recommendation engine given a set of user tags?

Basically, the idea is to have users following tags on the site, so each users has a set of tags they are following. And then there is a document collection where each document in the collection has a ...
Wasiim Ouro-sama's user avatar
4 votes
1 answer
2k views

Information Extraction from Free-form text to create Transactions

I'm working on a use case where the user will be provided a text box to enter the details of the transaction application. For Example user might enter the below text and I have to parse the data and ...
pydnltk's user avatar
  • 41
4 votes
1 answer
98 views

Why are there currently no content-based evaluation metrics for information retrieval?

Consider the problem of learning to rank for Google-like searching - i.e., learning to return a good ordering of URL's when given a query. Most (if not all) current evaluation metrics for this problem ...
Matt's user avatar
  • 821
4 votes
2 answers
3k views

Document similarity: Vector embedding versus BoW performance?

I have a collection of documents, where each document is rapidly growing with time. The task is to find similar documents at any fixed time. I have two potential approaches: A vector embedding (...
Alec Matusis's user avatar
4 votes
1 answer
136 views

Visualizing F-score differences in information extraction

I have several corpora and NLP systems (including a few merge ensembles of output of these systems combined in unions and intersections) with which I have extracted the annotation span sets {(begin, ...
horcle_buzz's user avatar
4 votes
1 answer
1k views

Detect sensitive data from unstructured text documents [closed]

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 ...
user971961's user avatar
4 votes
4 answers
244 views

Extract 2 pieces of information from a string - what to use?

First of all, I am a complete newbie in regard to data science and I am not asking for the complete solution but some guidance as to what I should read up to achieve my task (what algorithms, ...
kyriakos's user avatar
  • 141
4 votes
1 answer
558 views

Why keep vocabulary and posting list separate in a search engine

I am taking a class in information retrieval. We learned that the index of a search engine has (possibly among other things): A vocabulary mapping terms to their statistics (frequency, type, ...) and ...
icehawk's user avatar
  • 141
4 votes
1 answer
112 views

metric learning and information retrieval

I am interested in parsing semi-structured text. Assume that I have a text with labels of the kind: year_field, year_value, identity_field, identity_value, ..., address_field, address_value, and so on....
mic's user avatar
  • 513
3 votes
1 answer
976 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 ...
user avatar
3 votes
2 answers
213 views

non query-based document ranking

We have ~500 biomedical documents each of some 1-2 MB. We want to use a non query-based method to rank the documents in order of their unique content score. I'm calling it "unique content" because our ...
DACW's user avatar
  • 131
3 votes
1 answer
400 views

Evaluating a IR system (Precision and Recall)

I am studying by now IR system, in the field of valuation of IR system outputs related to a specific query but I need some help to understand it properly. My book states that when an IR system has ...
Angelo Giannuzzi's user avatar
3 votes
1 answer
144 views

Tokenizing words of length 1, what would happen if I do topic modeling?

Suppose my dataset contains some very small documents (about 20 words each). And each of them may have words in at least two languages (combination of malay and english, for instance). Also there are ...
Jeffrey04's user avatar
  • 241
3 votes
1 answer
604 views

Finding the top K most similar sets

I have a database containing sets of words. So for example, I have a database that has: {happy, birthday, to, you} {how, are, you} ... Given a query set, lets ...
okebz's user avatar
  • 113
3 votes
1 answer
4k views

Data sets for evaluating text retrieval quality [closed]

I'm searching for data sets for evaluating text retrieval quality. TF-IDF is a popular similarity measure, but is it the best choice? And which variant is the best choice? Lucenes Scoring for example ...
Erich Schubert's user avatar
3 votes
1 answer
439 views

Evaluation metric for Information retrieval system

I am currently reading Semantic Product Search paper published by Amazon. They are using two evaluation subtasks matching and ranking. In matching, they tune the model hyperparameters to maximize ...
Sayali Sonawane's user avatar
3 votes
1 answer
682 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 ...
ludgo's user avatar
  • 133
3 votes
1 answer
83 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 ...
individualtermite's user avatar
3 votes
1 answer
124 views

Origin of the Boolean Model of Information Retrieval

Simple question, but I can't really find the answer to that: Who "invented" Boolean Retrieval? Of course, I assume that the concept grew over time, but is there a paper or publication that ...
TiMauzi's user avatar
  • 81
3 votes
1 answer
70 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 ...
RossDeVito's user avatar
2 votes
1 answer
2k views

how to evaluate top n recommendation system with movie lens dataset?

Based on my research a recommendation system are a subclass of information filtering system that seek to predict the "rating" or "preference" that a user would give to an item. And I'm currently ...
John Newman's user avatar
2 votes
1 answer
166 views

How "similarity" is measured in image retrieval?

I know what content based image retireval is. I have read this and this as one of them says: "given a query images, get a rank list that are most similar to the query image, based on the content ...
David's user avatar
  • 131
2 votes
1 answer
270 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 $n$ ...
WoofDoggy's user avatar
  • 343
2 votes
2 answers
1k views

How to rank documents using Bag of words approach

I want to cluster the documents I get for Google scholar search using the Bag of words model. I thought of using Java as the language. Assume for the keyword k, Google scholar gives me 50 results. If ...
dave's user avatar
  • 21
2 votes
1 answer
424 views

Why is accuracy not a useful measure for information retrieval problems?

I have been studying about information retrieval and recommender systems. While reading about it I found that accuracy not a useful measure in information retrieval. I understand that, accuracy might ...
ilved17's user avatar
  • 41
2 votes
1 answer
351 views

How to determine the "total number of relevant documents" in calculatiion of Recall in Precision and Recall if it's not known? Can it be estimated?

On Wikipedia there is a practical example of calculating Precision and Recall: When a search engine returns 30 pages, only 20 of which are relevant, while failing to return 40 additional relevant ...
Banik's user avatar
  • 131
2 votes
1 answer
88 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 ...
jakes's user avatar
  • 95
2 votes
1 answer
128 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 ...
mani's user avatar
  • 121
2 votes
1 answer
100 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 ...
hagope's user avatar
  • 121
2 votes
1 answer
2k views

extract names in a list of names

I have been provided with a text cleaning task and I am assuming this involves some amount of natural language processing. I have a collection of names which does not have any specific pattern and ...
StatguyUser's user avatar
2 votes
1 answer
418 views

What metrics must i use in my data(unstructured) preprocessing research?

i am currently working on preprocessing unstructured data (emails,logs,bug reports and irc chats). i wish to prove preprocessing improves the content quality. are there metrics available to prove ...
Hemaa mathavan's user avatar
2 votes
2 answers
1k views

Approaches to Bag-Of-Words Information Retrieval

I'm interested in an overview of the modern/state-of-the-art approaches to bag-of-words information retrieval, where you have a single query $q$ and a set of documents which you hope to rank by ...
Set's user avatar
  • 121