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5
votes
1answer
75 views
+100

Why does Lucene IDF have a seemingly additional +1?

From the Lucene docs $\text{IDF} = 1 + \log\left(\frac{\text{numDocs}}{\text{docFreq}+1}\right)$ In other references (i.e. wikipedia), IDF is typically calculated as ...
0
votes
1answer
21 views

Average precision when not all the relevant documents are found

I can't find on the Internet a proper source that explains this. I have built a search engine that for a particular query retrieves 5 relevant document out of the 10 relevant documents. When I ...
0
votes
2answers
40 views

What is the best algorithm to find similar text documents?

I have many text documents and I would like to find similar documents to each document within my data set. Is Latent Dirichlet Allocation (LDA) the best way to do that, or are there other algorithms ...
3
votes
0answers
29 views

Heuristics streaming data matching

I have an index composed by thousands of documents. Slightly modified copies of those documents are sent to my application in small chunks, and I need to check, from those chunks, which document has ...
0
votes
0answers
19 views

An IR evalualuation metric that only measures the rank of results?

I am working on a little text clustering problem, and trying to figure out how to evaluate the results. I came up with the following idea that I though fits pretty well with the specifics of the ...
0
votes
0answers
21 views

Understanding the Precision-Recall breakeven point in ranking

Consider an IR system that retrieves all document and rank them in order of relevance. Now, we can calculate Precision and Recall at each rank. Does the breakeven point (recall=precision) always ...
0
votes
0answers
19 views

Test statistics in IR (t-test vs Wilcoxon vs signed test)

I have just read this paper about different test statistics one could use in Information Retrieval (IR), discussing whether Wilcoxon, Sign-test or Student t-test would be more reliable for comparing ...
0
votes
1answer
14 views

Calculation of Cosine Similarity using LSA

I am getting negative cosine similarity value between two documents in Latent Semantic analysis. How should it be treated?
0
votes
0answers
14 views

Can using of Weight function in Latent Semantic Analysis increase the efficiency of the technique?

What type of combination of local & global weight function and what would be the length of the document which can actually increase the efficiency of the LSA.
0
votes
0answers
12 views

Evaluating annotations with gold standard

I want to evaluate the following: I have a gold set with documents wherefore the meta data is annotated; this means for an article i have annotated what the author is, what the title is, etc.. I now ...
0
votes
0answers
9 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 ...
0
votes
0answers
43 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 ...
0
votes
1answer
21 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, ...
0
votes
0answers
17 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 ...
0
votes
0answers
49 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 ...
0
votes
0answers
12 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
votes
0answers
92 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 ...
0
votes
0answers
10 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
vote
1answer
63 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 ...
0
votes
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 ...
0
votes
0answers
107 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 ...
0
votes
0answers
39 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
votes
1answer
41 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 ...
0
votes
2answers
94 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 ...
0
votes
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 ...
0
votes
0answers
110 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
votes
2answers
84 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
votes
0answers
15 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
votes
1answer
104 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 ...
1
vote
0answers
15 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 ...
0
votes
0answers
24 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 ...
0
votes
0answers
19 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
votes
0answers
39 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
vote
1answer
39 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).
0
votes
0answers
33 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. ...
0
votes
0answers
159 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
633 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
97 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
vote
0answers
113 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 ...
0
votes
1answer
41 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
votes
1answer
293 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
votes
1answer
82 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
votes
2answers
202 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
vote
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 ...
0
votes
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}})= ...
1
vote
2answers
241 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
votes
0answers
28 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
votes
0answers
45 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
votes
0answers
280 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 ...