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Georgetown University


Detailed Course Information


Fall 2017
Sep 28, 2022
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Information Select the desired Level or Schedule Type to find available classes for the course.

COSC 589 - Web Search and Sense-Making
The Web provides abundant information which allows us to live more conveniently and make quicker decisions. At the same time, the growth of the Web and the improvements in data creation, collection, and use have lead to tremendous increase in the amount and complexity of the data that a search engine needs to handle. The increase of the magnitude and complexity of the data has become a major drive for new data analytics algorithms and technologies that are scalable, highly interactive, and able to handle complex and dynamic information seeking tasks in the big data era. How to effectively and efficiently search for the documents relevant to our information needs and how to extract the valuable information and make sense out from “big data” are the subjects of this course. 

The course will cover Web search theory and techniques, including basic probabilistic theory, representations of documents and information needs, various retrieval models, link analysis, classification and recommender systems. The course will also cover programming models that allow us to easily distribute computations across large computer clusters. In particular, we will teach Apache Spark, which is an open-source cluster computing framework that has soon become the state-of-the-art for big data programming. The course is featured in step-by-step weekly/bi-weekly small assignments which composes a large big data project, such as building Google’s PageRank on the entire Wikipedia. Students will be provided knowledge to Spark, Scala, Web search engines, and Web recommender systems with a focus on search engine design and "thinking at scale”. 

3.000 Credit hours
3.000 Lecture hours

Levels: MN or MC Graduate, Undergraduate
Schedule Types: Lecture

Computer Science Department

Must be enrolled in one of the following Levels:     
      MN or MC Graduate

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