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Amazon Commerce reviews set Data Set
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Abstract: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.

Data Set Characteristics:  

Multivariate, Text, Domain-Theory

Number of Instances:

1500

Area:

Physical

Attribute Characteristics:

Real

Number of Attributes:

10000

Date Donated

2011-06-11

Associated Tasks:

Classification

Missing Values?

N/A

Number of Web Hits:

86408


Source:

Dataset creator and donator: ZhiLiu, e-mail: liuzhi8673 '@' gmail.com, institution: National Engineering Research Center for E-Learning, Hubei Wuhan, China


Data Set Information:

dataset are derived from the customers’ reviews in Amazon Commerce Website for authorship identification. Most previous studies conducted the identification experiments for two to ten authors. But in the online context, reviews to be identified usually have more potential authors, and normally classification algorithms are not adapted to large number of target classes. To examine the robustness of clasification algorithms, we identified 50 of the most active users (represented by a unique ID and username) who frequently posted reviews in these newsgroups. The number of reviews we collected for each author is 30.


Attribute Information:

attribution includes authors' lingustic style such as usage of digit, punctuation, words and sentences' length and usage frequency of words and so on


Relevant Papers:

Sanya Liu, Zhi Liu, Jianwen Sun, Lin Liu, 'Application of Synergetic Neural Network in Online Writeprint Identification', JDCTA: International Journal of Digital Content Technology and its Applications, Vol. 5, No. 3, pp. 126 ~ 135, 2011
Jianwen Sun, Zongkai Yang, Pei Wang, Sanya Liu, 'Variable Length Character N-Gram Approach for Online Writeprint Identification,' mines, pp.486-490, 2010 International Conference on Multimedia Information Networking and Security, 2010



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