The amazon specifically instant video product metadata and


Assignment -

The Amazon specifically "Instant Video product" metadata and reviews:

Needs to review and analyze 2 datasets regarding Amazon Instant Video products. The reviews dataset contains user reviews of Amazon Instant Video products along with other relevant information (see set-I below). The Meta dataset contains data about the Amazon Instant Video products themselves (set-II below).

Set-I: Reviews data description

  • reviewerID - ID of the reviewer
  • asin - ID of the product
  • reviewerName - Name of the reviewer
  • helpful - Helpfulness rating of the review
  • reviewText - Text of the review
  • overall - Rating of the product
  • summary - Summary of the review
  • unixReviewTime - Time of the review (unix time)
  • reviewTime - Time of the review (raw)

Set-II: Meta data description

  • asin - ID of the product
  • title - Name of the product
  • price - Price in US dollars (at time of crawl)
  • imUrl - URL of the product image
  • related - Related products
  • salesRank - Sales rank information
  • brand - Brand name
  • categories - List of categories the product belongs to

Requirement: Write up should not be more than 300 words (don't need to be fancy, just basic bullet pointers would be helpful)

Introduction: This section introduces your problem, why it is important, who cares, and the overall plan for approaching your problem.

Background/Related Work: This section discusses relevant literature for your project.

Approach: This section details the framework of your project. Be specific, which means you might want to include equations, figures, plots, etc.

Experiment: This section begins with what kind of experiments you're doing, what kind of dataset(s) you're using, and what is the way you measure or evaluate your results. It then shows in detail the results of your experiments. By details, we mean quantitative evaluations (show numbers, figures, tables, etc) or qualitative results (show images, example results, etc).

Conclusion: What have you learned? Suggest future ideas.

References: If you borrowed the idea from another work, please give credit.

Supplementary Material is not counted toward your 6-8 page limit and is a required part of your submission. Examples of items to place in your supplementary material: Source code. Cool videos, interactive visualizations, demos, etc.

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Dissertation: The amazon specifically instant video product metadata and
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