Essay Assignment
Topic: Recommender Systems
Overview: The purpose of this assignment is to explore the processes associated with Recommender Systems.
Automated recommendations have become a pervasive feature of our online user experience, and due to their practical importance, recommender systems also represent an active area of scientific research. Along with the availabilit y of new knowledge sources, including both structured and unstructured data that contain user -generated content, comes a steady stream of new systems that leverage such information to make better predictions. Recently, recommender systems have also emerged in the biomedical sciences and the objectives are the same in these applications, to predict ratings for missing items.
1. Recommender systems. What is a recommender system? Describe the purpose and explain how this application wor ks to help businesses serve their target market more effectively. Also, please explain the ways in which a recommender system differs from a customer or product-based system.
2. Contrast with traditional systems. Please explain how a recommender system differs from a typical classification or predictive modeling system. For example, logistic regression is perhaps the most widely used statistical model for classificatio n. It is more preferable to CF because of the ensemble feature, ability to handle missing data, and it is generally robust to noise and outliers.
3. Collaborative filtering (CF). Please outline one method of collaborative filt ering. Please discuss why it works in the context of recommender systems and describe what its limitations are in practice. What modern techniques/systems are available to overcome these limitations? For example, memory-based algorithms can group every user with similar interests and identify the neighbors of a new user or currently active user to anticipate the preferences of new i tems that would be of interest.
Include the following critical elements in your essay:
1) Recommender systems: Describe the purpose and explain how this application works to help businesses serve their target ma rket more effectively. Also, please explain the ways in which a recommender system differs from a customer or product-based system.
2) Contrast with traditional systems: Explain how a recommender system differs from a typical classification or predictive modeling system.
3) Collaborative filtering: Outline one method of collaborative filt ering. Discuss why it works in the context of recommender systems and describe what its limitations are in practice.
Format your assignment according to the give formatting requirements:
1. The answer must be double spaced, typed, using Times New Roman font (size 12), with one-inch margins on all sides.
2. The response also includes a cover page containing the title of the assignment, the course title, the student's name, and the date. The cover page is not included in the required page length.
3. Also include a reference page. The references and Citations should follow APA format. The reference page is not included in the required page length.