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0answers
6 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
39 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
10 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
9 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
12 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 ...
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0answers
7 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
35 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
30 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
30 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 ...
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1answer
69 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
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1answer
57 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
49 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
21 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
30 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
262 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 ...
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0answers
11 views

relevance feedback - (Pseudo relevance feedback)

While studying relevance feedback(Pseudo relevance feedback), I have learn that the model can go horribly wrong for some queries. Can anyone give reasons why this is?
0
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0answers
32 views

Rocchio algorithm - relevance feedback

I am studying the Rocchio alorithm. I understand how it works. And typically we set Positive feedback is more valuable than negative feedback (so, set β < γ; e.g. γ = 0.25, β = 0.75). And many ...
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1answer
60 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
48 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
108 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
27 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
46 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
108 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?
0
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0answers
33 views

User intent identification in web search queries using unlabeled data

Given a list of unlabeled search queries, is it possible to say which query is related to a certain topic? For example, if we want to select the queries where the intent of the user is to download or ...
2
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0answers
19 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 ...
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0answers
38 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
90 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
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1answer
189 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
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1answer
132 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 ...
1
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1answer
76 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
207 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
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0answers
59 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
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0answers
56 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
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1answer
26 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
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3answers
250 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 ...
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0answers
80 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 ...
0
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3answers
148 views

Is there any dataset or api that gives a list of infrequent words? [closed]

I'm actually working on an information retrieval project, and I want to extract words that are of significance from a sentence. This is somewhat opposite to stopwords. In a sentence like: He was a ...
3
votes
1answer
415 views

A parellel between LSA and pLSA

In the original paper of pLSA the author, Thomas Hoffman, draw a parallel between pLSA and LSA data structures that I would like to discuss with you. Background: Taking inspiration the Information ...
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0answers
93 views

Using sentiment lexicons or all words processing for sentiment analysis?

I am learning sentiment analysis to apply it to twitter real time data to predict user's mood. I ponder about using which alternative way to do that data mining job. Use all words to process and ...
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0answers
29 views

Evaluation and Testsets for NNMF

I am trying to evaluate my recommender system which uses Non-negative Matrix Factorization. Some things that I evaluate are How does the size of the feature matrix affect the recommendations How ...
3
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1answer
2k views

Euclidean Distance b/t unit vectors or cosine similarity where vectors are document vectors

I was reading Similarity Measures and suddenly my whole world was falling apart. I have implemented a search engine using clustering techniques. For clustering, I used k means which uses Euclidean ...
2
votes
2answers
240 views

How do you predict a continuous value from many booleans & a continuous value?

Hello: I am a computer science student working as a research assistant in an undergrad IR lab, feeling spectacularly out of my element. Given an input of a single continuous value and a vector of ...
2
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0answers
76 views

Software library for Hidden Markov Modeling of a large text database

Given we have a large database of texts (e.g. product descriptions) and we want to extract multiple types of information (e.g. brand, release date, features, price, etc.) what's a good library to ...
7
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2answers
302 views

Understanding and applying sentiment analysis

I was just having been assigned a project of conducting sentiment analysis for some document collections. By Googling, a lot of sentiment-related research has popped up. My questions are: What are ...
3
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0answers
307 views

Similarity calculations for arrays

First of all, my apologies if I mess up the terminology. I've been out of math for several years, so I'm certain I'm going to use terms incorrectly. Also, though I concentrated mathematics in college, ...
5
votes
1answer
297 views

Choosing a measure of similarity to quantify similarity between individuals on a set of personality scales

I have a bunch of users. Each user has a number of personality attributes, such as "fitness level" or "eco-consciousness", rated on a scale from 1 to 5. I want to calculate how similar two users are, ...
2
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0answers
154 views

How to to calculate the topic distribution of a document

I have a simple (may be stupid) question. I want to calculate Kullback–Leibler divergence on two documents. It requires probability distribution of each document. I do not know how to calculate ...
3
votes
1answer
649 views

Using latent Dirichlet allocation for information retrieval

I am working on understanding various document ranking algorithms like (TF-IDF, LSI, language models, etc) by actually implementing them. I want to understand LDA and using various resources to ...
4
votes
2answers
403 views

How to compute term frequency and find clusters in a dataset composed of strings?

I am currently looking for some Information Retrieval techniques. I have a SQL database table containing strings. It has 1000 records, each being a random sentence I picked from random web sites. I ...
3
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2answers
1k views

Comparing cosine similarities for tf-idf vectors for documents with different length

I'm computing cosine similarities between 2 vectors. These vectors are information retrieval query and document representations respectively. They have been computed using tf-idf weights. Since my ...