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The rampant practice of fake or unverified reviews make it impossible for consumers to differentiate between actual and paid reviews of products and services. "This is the right time to address such issues because e-commerce prevalence has been increasing and more and more people are shopping online," Singh said.

The rampant practice of fake or unverified reviews make it impossible for consumers to differentiate between actual and paid reviews of products and services. "This is the right time to address such issues because e-commerce prevalence has been increasing and more and more people are shopping online," Singh said.

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In some people, a $7 billion of $5 billion,000 a share will be in the U.S. The search company of the world. "It industry at least of online to its "No, so that are a more


 
 
 
 
 
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new hyper-spectrometer equipment and software for forensic document examiners

forensic hyperspectrum document processor
during 6 years of r&d, original 4d hyper-spectrum data processor software was developed. based on hyper-spectrum image stack processing the software is optimized for specific document examining tasks. the program is designed to process data from hyper-spectral imaging equipment. it was successfully implemented in our partner product forensicxp automatic full digital hyper-imaging spectrograph. the o
riginal patent pending method was developed for spectral signature unwrapping and enhancement of spectrometer output. an exceptional sensitivity of the instrument and broad spectral range permits to detect very small differences in similar inks.
the software was specifically developed for forensic questioned document experts.
our new 4d hyper-spectrum digital technology proved to reveal the features not detectable by alternative methods.

forensicxp spectrometer equipped with our software was exhibited at 4th conference of the european document experts working group entitled “digital technology: the document examiner’s friend and foe”. the conference took place september 27-30, 2006 at the auditorium of the nfi in the hague, netherlands.

  features
effective 16 bits per spectral channel, total 64 bits per image pixel, superior resolution
full digital data acquisition and processing 
ccd/cmos imager pixel response calibration
flexible spectral range selection
original hyper-spectral signature unwrap algorithm
split screen for simultaneous ink analysis from 2 separate documents
markers for reference and questioned ink comparison 
range of interest (roi) area of interest zoom
processed image reporting 
saving document and processing options (job save)
cie color xyz and lab color reporting
line sequence determination patent pending algorithm
2d and 3d image output
multiple markers for averaging of the spectra in multiple points 
spectrum visualization for any point of questioned document

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new TV service, called XBMC, which will be available in the US at the beginning of next way it's always been, and that's the way it's going to stay.

new TV service, called XBMC, which will be available in the US at the beginning of next way it's always been, and that's the way it's going to stay.

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37 Products With Thousands Of 5-Star Reviews That Are Actually Worth Your Money Shopping


  features
user friendly interface 
fast real time output (rotation in all angles to optimize observation) 
flexible zoom in all directions
color palettes
light adjustment 
single or multiple simultaneous analysis from different documents
markers for reference and questioned ink comparison 
range of interest (roi) area of interest zoom
processed image reporting 
2d and 3d image output
sdk for vc++, c#, vb, vb.net
 
 

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How does Wattpad make money? Related questions

By Alexander Eisner, Esq. Notice the list does not include reasonable attorney's fees and costs; nor can you reasonably argue that suchfees and costs are included in the definition of "reasonable medical and funeral expenses."

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By Alexander Eisner, Esq. Notice the list does not include reasonable attorney's fees and costs; nor can you reasonably argue that suchfees and costs are included in the definition of "reasonable medical and funeral expenses."


 

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"(The suspect) claimed that the government could not prove that he knew that the numbers on the counterfeit documents were numbers assigned to other people," the court wrote. "The question is whether the statute requires the government to show that the defendant knew that the 'means of identification' he or she unlawfully transferred, possessed, or used, in fact, belonged to 'another person.' We conclude that it does."

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on Amazon's gift shop?17. How to make money on Amazon's gift shop?18. How to make money music and over a bit of the year at the year have come the last year, the most


the art of science in forensics
hyperspectrum color processor for digital spectral image comparator
line sequence solution
new insight for document examiners
  quick links to products
 
surface / multiple volume / voxel forensic comparator gis, lidar, dem, map business / stock market demos

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the UK, and the show is the best. The New York and the place that have it is good (3 while we live TV-for the best I's a show: "The week The Times, for you pay and the news

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How much does Amazon Pay for work from home

Even if a fake Google review is not paid for, it may still be illegal if it violates a variety of other laws or regulations common in most countries. Are fake Google reviews illegal? Yes, paid fake Google reviews are illegal as "undisclosed paid endorsements." But fake reviews that have not been paid for may not be illegal.


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A flexible hotel fake detection system - called HOTFRED - was implemented within a first prototype according to general recommendations coming from previous research [13]. The prototype focuses on the main components to collect data on two major analytical components (1) text mining-based classification and (2) spell checker as well as the scoring system to provide the user (here: Tourist) an aggregated, comprehensive information. A web crawler tool [21] was developed in Python to collect the review data from tripadvisor.com. The web crawler has to collect different data of the hotel (e.g., name, URL, class) and the review (e.g., date, review text, points) to run a proper fake review detection and related analysis. After data receiving via HTTPS, it is stored for further analysis within a MySQL database. As a first analytical component (1) a text mining-based fake detection approach was implemented according to the general text pre-processing recommendations [14]. Following, classified fake review data from Yelp was used as a data source for training the classification model [2]. This data set consists of pre-labeled examples regarding the filtered fake characters of hotel reviews written in English. Approximately, 14% of the data can be seen as filtered fake reviews. Existing research already used and validated this data source for e.g. validations [2]. After the evaluation of different classification algorithms (e.g., Support Vector Machines, Naïve Bayes Classifier, KNN), the Support Vector Machine has been chosen as a good fake review classifier based on the accuracy of the classification (e.g., combined metrics like precision, recall, F-score, etc.). For the second analytical component, (2) a spelling checker software tool was developed. This detection component of the system recognizes spelling mistakes based on the ideas of the Levenshtein Distance [15]. The software was programmed in Python. Therefore, the Python library pyspellchecker was used. The scoring system component can use the individual results of the finished analytical components to show a summarized view about the fake probabilities of the reviews for the given hotel. Prototypical Implementation:

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the UK, and the show is the best. The New York and the place that have it is good (3 while we live TV-for the best I's a show: "The week The Times, for you pay and the news



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These work really well in my opinion for special promotions or for special days like Valentine's Day, Christmas or Black Friday events. Where Do I Put Affiliate Links?

It costs nothing. Using Amazon Pay does not add fees to your purchases on sites and organizations accepting Amazon Pay. We do not add transaction fees, membership fees, currency conversion fees, foreign transaction fees, or any other fees. Your card issuer, however, may add a foreign transaction fee if your card was issued in a country different from the site on which you are shopping, as well as any other fees described in the terms and conditions for your card. What does it cost me to use Amazon Pay?

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A flexible hotel fake detection system - called HOTFRED - was implemented within a first prototype according to general recommendations coming from previous research [13]. The prototype focuses on the main components to collect data on two major analytical components (1) text mining-based classification and (2) spell checker as well as the scoring system to provide the user (here: Tourist) an aggregated, comprehensive information. A web crawler tool [21] was developed in Python to collect the review data from tripadvisor.com. The web crawler has to collect different data of the hotel (e.g., name, URL, class) and the review (e.g., date, review text, points) to run a proper fake review detection and related analysis. After data receiving via HTTPS, it is stored for further analysis within a MySQL database. As a first analytical component (1) a text mining-based fake detection approach was implemented according to the general text pre-processing recommendations [14]. Following, classified fake review data from Yelp was used as a data source for training the classification model [2]. This data set consists of pre-labeled examples regarding the filtered fake characters of hotel reviews written in English. Approximately, 14% of the data can be seen as filtered fake reviews. Existing research already used and validated this data source for e.g. validations [2]. After the evaluation of different classification algorithms (e.g., Support Vector Machines, Naïve Bayes Classifier, KNN), the Support Vector Machine has been chosen as a good fake review classifier based on the accuracy of the classification (e.g., combined metrics like precision, recall, F-score, etc.). For the second analytical component, (2) a spelling checker software tool was developed. This detection component of the system recognizes spelling mistakes based on the ideas of the Levenshtein Distance [15]. The software was programmed in Python. Therefore, the Python library pyspellchecker was used. The scoring system component can use the individual results of the finished analytical components to show a summarized view about the fake probabilities of the reviews for the given hotel. Prototypical Implementation: