2DV515 A01

• A recommendation system that uses Euclidean distance as similarity measure.
• Can find similar users.
• RESTful web service in the program language Java.
• Use Euclidean distance as similarity measure.

2DV515 A02

• Implement K-means Clustering with Pearson similarity.
• Runs the algorithm on the blog data set with 5 clusters.
• Present the result as a list of clusters and their assignments in a web application.
• The iteration shall stop after a specified number of iterations (100).
• RESTful web service in the program language Java.

2DV515 A03

• Implement a basic search engine that index all pages in the Wikipedia data set.
• Search queries shall only contain single words.
• Results shall be ranked using the word frequencey metric.
• Implement the search engine as a web application using a RESTful web service.
• The user shall input the search queries in a web client, and display the search results returned from the server.
• Display the top 5 search results with page and rank score.
• RESTful web service in the program language Java.

2DV515 A04

• Classifies some data sets using different machine learning algorithms.
• In the program language Java with the library WEKA.
• Used Logistic and MultilayerPerceptron.
• In the Neural Network classifier is a single hidden layer = 72 nodes.

2DV515 PROJECT

• Scrape and store raw HTML for at least 200 pages.
• Done with Jsoup in Sts tool Eclipse.
• Database is Sqlite light.