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6 views

Calculating parameters for a custom ranking algorithm with no training data

On my site, we want to be able to sort search results for books by hot they are. When a book is added to the site its hotness is set to number of hours since the epoch, purchases, reviews and ...
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0answers
24 views

Are there differences between Delta TF-IDF and TF-IDF?

Are there differences between both algorithm or not ? i mean if i implement for ex Delta TF-IDF in a project instead of ...
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1answer
18 views

What are distinctive terms?

Here $n$ is the number of distinctive terms in document $d$. What is the meaning of distinctive? My guess is that it's terms that remain after filtering document from terms that aren't necessary, ...
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0answers
12 views

Picking a right classification metric

I have a classification problem that I ended up with only true positives (TP). Now, I would like to measure my classification but I wonder what kind of metric I should pick for the evaluation. Let ...
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0answers
40 views

Is precision in recommender system related to mean average error (MAE)?

A recommender system is being evaluated while increasing the neighborhood size. The highest precision was achieved between 10-15 neighbors(users) while the lowest MAE was in the range from 30-40 ...
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0answers
10 views

parsing semi-structured textual data poorly matrix formatted

I have found many approaches in the literature that could deal with my problem (which is parsing poorly formatted textual data having a matrix structure but whose content may vary, headers being ...
2
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0answers
90 views

Search in a graph of medical records

I have a hierarchical order of a disease list. Just for example: Respiratory system disease 1.1. Asphyxia neonatorum 1.2. Croup 1.3. Lower respiratory tract disease 1.4. Bronchial disease ...
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0answers
9 views

Modeling 2-D data as vector

As part of my class project i had to use decision tree classification on a training set which contains a set of matrices where each row is a vector recorded at a particular time stamp and each row ...
1
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1answer
54 views

Vector Space Model for Online News Clustering

I am trying to automatically cluster news articles based on their content. I need this algorithm to be online and simply group news articles related to the same story as they arrive. The common ...
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0answers
11 views

Context-aware information retrieval?

I was asked a puzzle lately and so I decided to cheat and find the answer on Google. The puzzle was asked to me in a different language than English, so I had to think about the main context and then ...
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0answers
78 views

Difference between Weighted Average Entropy and Adjusted Mutual Information (for evaluating Clustering)

I was advised by my team leader to use this weighted average entropy to evaluating the performance of my dbscan clustering algorithm, and its mathematical formulation is: Scikit provides what many ...
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0answers
31 views

choosing best value for N when using N-Gram approach

the question is quite general, but I am doing a research related to supervised machine learning to classify two set of characters into two categories. in fact, I want to compute some measures of ...
0
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1answer
39 views

Measure precision

This is used in information retrieval. I have an algorithm that uses a sample set to predict a yes / no. I think the correct term is binomial. Yes this document is about sports or no this document ...
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2answers
88 views

Correct Evaluation of Random Forest on fixed training/test set

I have to test the performance of Random Forest on the same dataset (text classification) with about 118.000 instances of which about 1/3 is used for training and 2/3 is used for testing. The division ...
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0answers
5 views

Get positions/values from heat costs bill

for a project I need to extract values from customers yearly heat costs bill. The customer takes a photo of the bill and the program should extract the values heating period of the billing, type of ...
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0answers
100 views

Using relative frequency for Euclidean and cosine distance (dissimilarity)

How to calculate the Euclidean distance (dissimilarity) between two documents, e.g., D1 and D2 using relative frequency? Here is an example of both cosine and Euclidean distance between two ...
2
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2answers
80 views

Weighting words based on position in text

I'm currently working on semantic analysis and had a question about text organization and structure. Are there any algorithms, or statistical / machine-learning models that weight the importance of a ...
0
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0answers
13 views

Search for similar documents on growing term-base

Could you please recommend any approach (if it exists) for similar document search considering the following: It's necessary to provide term base explicitly. This is a dictionary of specific named ...
5
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1answer
103 views

In inverse theory, how do I transform the averaging kernel matrix to a new grid?

Rodgers and Connor (2003) describe how measurements by remote sounders can be properly compared, taking into account differences in averaging kernels and error covariances. They make the assumption ...
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0answers
14 views

Information retrieval performance measures for unknown test collection?

I am evaluating a web search relevance feedback algorithm. The algorithm uses Bing API as source for its result sets. To evaluate the algorithm I will be conducting a user study. In the end I will ...
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0answers
22 views

Can LSA find correlations between multiple words?

I need to find correlations between multiple terms (say, 3 or 4) in a single-term search index. I'm trying to figure out if LSA fits to the problem. Am I right that LSA is no more than a term-to-term ...
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0answers
17 views

Evaluation of IR approach without test collections

I am trying to evaluate an information retrieval approach. More specifically, it's a query expansion algorithm, based on topic distribution in retrieved documents. I want to evaluate my approach ...
0
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0answers
37 views

maximize mean F1 score in multilabel information retrieval problem

I have a multilabel text classification problem where each observation will have one or more labels associated to it. The metric I want to maximize is mean F1 score. Are there standard ways to ...
1
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1answer
38 views

How do I perform an IDF calculation?

How do I perform an IDF calculation? I am uncertain as to whether IDF should be calculated in per-class level or for the entire document set (that contains multiple classes).
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0answers
32 views

What are the mathematics I need to learn, before I start research in data mining [duplicate]

I usually use text mining, graph mining, Information retrieval, and natural lanuage processing. Also i will use the fundamental concepts of data mining like classification, association and clustering. ...
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0answers
132 views

Build corpus with phrases

I have my documents as: doc1 = beautifull, very good, very bad, you are great doc2 = very bad, good restaurent, nice place to visit I want to make my corpus ...
1
vote
1answer
475 views

Create a matrix of tf-idf values from documents

I have a set of documents like: D1 = "The sky is blue." D2 = "The sun is bright." D3 = "The sun in the sky is bright." and a ...
0
votes
1answer
90 views

Clustering structured data: Assessing the similarity of documents that appear in tree structure

Usually when performing text document clustering, similarities across documents are assessed based on the lexical content of documents. But, in my problem, I wish to consider both the lexical content ...
1
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0answers
93 views

Learning to Rank: query-dependent vs. query-independent features

I've been doing some reading about learning to rank - specifically lambdaMART - and one thing I am confused about is the role of features. When training a model, should one only use query-dependent ...
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0answers
35 views

LexRank damping factor

I am looking into using LexRank to do some text summarization. I am looking at the original paper. One thing that puzzles me is whether a damping factor is used or not. The formulae are all using it, ...
0
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1answer
39 views

Choosing the best set of keywords

I have a dataset of tweets collected using twitter streaming API on a particular topic (say 'football') using around 40 keywords. Now if I'm going to track the same topic (football) in future how do I ...
1
vote
1answer
1k views

“Mean average precision” (MAP) evaluation statistic - understanding good/bad/chance values

I'm evaluating a multilabel classifier. I'm familiar with the Area Under the Curve statistic, which has some nice properties (e.g. chance level is always 50%). But for some applications, it's more ...
2
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1answer
197 views

What is the difference between accuracy and agreement?

According to Manning et al. (p. 155) accuracy is the sum of the diagonal in the confusion matrix divided by the sum of all items. On the other hand, following Artstein and Poesio (p . 558) precisely ...
0
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1answer
73 views

Automatic labeling of training set

I have once meet the following question, given a training set, is that possible to do the automatic labelling? In addition, if this training set consists of plain text files, is that possible to know ...
2
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2answers
183 views

Dataset and papers for baseline [closed]

I'm doing a project about Topic Detection and Tracking in text. I need to perform a baseline so I can compare existing results with mine. I read some papers where they use datasets that are not so ...
1
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1answer
33 views

“Exotic” text representations methods?

I'm looking to the different methods of representing a text into a machine-readable format. However, until now, I only found "Bag of Words" approachs with a lot of variations (boolean BoW, weighted ...
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0answers
50 views

Calculation of normalization constant

This is an equation from the paper "A Content-based Probabilistic Correction Model for OCR Document Retrieval" - Rong Jin, Alex G. Hauptmann , ChengXiang Zhai $$P(w|M_{\text{orig}})= ...
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2answers
210 views

Most important journals in data mining/ML, NLP and IR?

Can you please provide with me with the names of the most important journals in data mining, machine learning, natural language processing and information retrieval?
2
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0answers
27 views

Evaluation of a semi-supervised ranking model

I learned ranking model with graph-based semi-supervised approach, while labeled (just positive) and unlabeled (positive and negative) data is both used in training. With the model, all of the data ...
0
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0answers
43 views

Algorithms for keyphrase clustering

Are there any standard algorithms for keyphrase clustering. There are several algorithms for keyphrase extraction from a corpus. For e.g. this publication reviews some of the popular keyphrase ...
2
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0answers
232 views

Why are ERR (Expected Reciprocal Ranking) scores not normalized?

It seems to me that normalized ERR (Expected Reciprocal Ranking) scores (ERR scores of your ranking algorithm divided by ERR score calculated for the ground truth ranking) are more useful than the ...
0
votes
1answer
322 views

K-Fold Cross validation and F1 Measure Score for Document Retrieval using TF-IDF weighting and some customised weighting schemes

I am developing a search engine system based on the vector space model, and I am confused on what approach I should take to evaluate the system. My case is this: I have a set of indexed documents ...
1
vote
1answer
243 views

Clustering of documents that are very different in number of words

I have a corpus of 643 documents with different sizes and my goal is to cluster them according their topics and label each cluster with semantic name for its main topic. I have tired different ...
2
votes
1answer
94 views

What is the standard procedure for evaluating a user-based CF algorithm with a dataset offline?

I have read some papers and other materials about the evaluation of recommender systems (RS). Most of them discuss the various properties of RS (e.g. accuracy, diversity, etc.), and metrics for ...
2
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2answers
320 views

Other documents features than tf-idf for clustering?

What are other feature representations for documents that are used for clustering textual documents? The only representation I'm aware of is tf-idf. Are there other ones?
1
vote
0answers
72 views

Mutual Information for clustering

I'm working on a document clustering application and decided to use Normalized Mutual Information as one of the measures of effectivenes. But I don't really understand how to implement this in that ...
1
vote
0answers
62 views

MAE/MSE with or without square root

I read some papers about recommender systems and information retrieval, where Mean Absolut Error and Mean Squared Error are mentioned. But I've found some differences between the formal definition of ...
0
votes
1answer
27 views

Discounted cumulated gain

I've a little question regarding the Discounted Cumulated Gain (DCG) (Sorry, I couldn't find the papers of Järvelin and Kekäläinen). Can this evaluation-metric be used when a information retrieval ...
4
votes
3answers
390 views

Summary statistics of the precision-recall curve

From what I understand, one can use the AUC of the ROC curve as a summary statistic of the full curve. Q1. Are there any similar summary statistics that one can use on a single precision-recall ...
1
vote
0answers
95 views

Is that overfitting?

Given a document-term matrix $X$, where $$X(d, t) = \textit{occurrences of 't' in 'd'}$$, it's possible to compute it's Truncated Singular Value Decomposition:$$X_k = U_k \Sigma_k V_k^T$$ Then, for a ...