IR Project for Course
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This will traverse the Web as a linked graph from the starting --url finding all outgoing links (<a> tag): it will store each outgoing link for the URL, and then repeat the process for each or them, until --limit URLs will have been traversed. The output will be a JSON file with all incoming and outgoing link information
This project helps to cluster data sets from Bing API into clusters using "k-means" algorithm. The second part of the project was to build a Naive Bayes Classifier . It was build using a training data set. Then given a new data set it can classify to which class , the input data belongs. The third part of the project was to build a composite Classifier and Cluster.
"Tweet Search and Ranker" , would take a "tweet corpus" as input and display the best tweets for a given query. The tweets with best "tf-idf" score were displayed at the top. The other part of the project involved Ranking the Users in the corpus using the classic "Page Rank" algorithm. The top 50 users with the Highest Page Rank were displayed.
This is a search engine which can answer Boolean Queries, Phrase Queries and Wild Card Queries.